a systematic overview of systematic reviews evaluating interventions addressing polypharmacy

A systematic overview of systematic reviews evaluating interventions addressing polypharmacy

Collaborators.

• Members of the PHARM-DC group : Carmel M Hughes ,  Cynthia A Jackevicius ,  Denis O'Mahony

Affiliations

• 1 Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA.
• 2 Department of Medicine, Brigham and Women's Hospital, Boston, MA.
• 3 Department of Pharmacy, Cedars-Sinai Medical Center, Los Angeles, CA.
• 4 Division of Geriatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA.
• 5 David Geffen School of Medicine at UCLA, Los Angeles, CA.
• PMID: 31612924
• PMCID: PMC7170727
• DOI: 10.1093/ajhp/zxz196

Purpose: To systematically evaluate and summarize evidence across multiple systematic reviews (SRs) examining interventions addressing polypharmacy.

Summary: MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects (DARE) were searched for SRs evaluating interventions addressing polypharmacy in adults published from January 2004 to February 2017. Two authors independently screened, appraised, and extracted information. SRs with Assessment of Multiple Systematic Reviews (AMSTAR) scores below 8 were excluded. After extraction of relevant conclusions from each SR, evidence was summarized and conclusions compared. Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess evidence quality. Six SRs met the inclusion criteria, 4 of which used meta-analytic pooling. Five SRs focused on older adults. Four were not restricted to any specific disease type, whereas 1 focused on proton pump inhibitors and another focused on patients with severe dementia. Care settings and measured outcomes varied widely. SRs examining the impact on patient-centered outcomes, including morbidity, mortality, patient satisfaction, and utilization, found inconsistent evidence regarding the benefit of polypharmacy interventions, but most concluded that interventions had either null or uncertain impact. Two SRs assessing medication appropriateness found very low-quality evidence of modest improvements with polypharmacy interventions.

Conclusion: An overview of SRs of interventions to address polypharmacy found 6 recent and high-quality SRs, mostly focused on older adults, in which both process and outcome measures were used to evaluate interventions. Despite the low quality of evidence in the underlying primary studies, both SRs that assessed medication appropriateness found evidence that polypharmacy interventions improved it. However, there was no consistent evidence of any impact on downstream patient-centered outcomes such as healthcare utilization, morbidity, or mortality.

Keywords: aged; deprescriptions; polypharmacy; review; systematic review.

© American Society of Health-System Pharmacists 2019. All rights reserved. For permissions, please e-mail: [email protected].

Publication types

• Research Support, N.I.H., Extramural
• Systematic Review
• Clinical Trials as Topic*
• Inappropriate Prescribing / prevention & control*
• Medication Therapy Management / organization & administration*
• Patient Acceptance of Health Care / statistics & numerical data
• Patient Discharge
• Patient Transfer / organization & administration
• Polypharmacy*
• Systematic Reviews as Topic
• Treatment Outcome

Grants and funding

• K23 AG049181/AG/NIA NIH HHS/United States
• L30 AG048588/AG/NIA NIH HHS/United States
• R01 AG058911/AG/NIA NIH HHS/United States

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A systematic overview of systematic reviews evaluating interventions addressing polypharmacy

Laura j anderson.

1 Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA

Jeffrey L Schnipper

2 Department of Medicine, Brigham and Women’s Hospital, Boston, MA

Teryl K Nuckols

4 Department of Pharmacy, Cedars-Sinai Medical Center, Los Angeles, CA

Catherine Sarkisian

5 Division of Geriatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA

Michael M Le

6 David Geffen School of Medicine at UCLA, Los Angeles, CA

Joshua M Pevnick

Associated data.

To systematically evaluate and summarize evidence across multiple systematic reviews (SRs) examining interventions addressing polypharmacy.

MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects (DARE) were searched for SRs evaluating interventions addressing polypharmacy in adults published from January 2004 to February 2017. Two authors independently screened, appraised, and extracted information. SRs with Assessment of Multiple Systematic Reviews (AMSTAR) scores below 8 were excluded. After extraction of relevant conclusions from each SR, evidence was summarized and conclusions compared. Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess evidence quality. Six SRs met the inclusion criteria, 4 of which used meta-analytic pooling. Five SRs focused on older adults. Four were not restricted to any specific disease type, whereas 1 focused on proton pump inhibitors and another focused on patients with severe dementia. Care settings and measured outcomes varied widely. SRs examining the impact on patient-centered outcomes, including morbidity, mortality, patient satisfaction, and utilization, found inconsistent evidence regarding the benefit of polypharmacy interventions, but most concluded that interventions had either null or uncertain impact. Two SRs assessing medication appropriateness found very low-quality evidence of modest improvements with polypharmacy interventions.

An overview of SRs of interventions to address polypharmacy found 6 recent and high-quality SRs, mostly focused on older adults, in which both process and outcome measures were used to evaluate interventions. Despite the low quality of evidence in the underlying primary studies, both SRs that assessed medication appropriateness found evidence that polypharmacy interventions improved it. However, there was no consistent evidence of any impact on downstream patient-centered outcomes such as healthcare utilization, morbidity, or mortality.

• Six high-quality systematic reviews of interventions addressing polypharmacy were identified.
• The 2 systematic reviews considering the outcome of medication appropriateness found improvements with use of polypharmacy interventions; however, the underlying evidence assessed in these reviews was of low or very low quality.
• No discernible impact of polypharmacy interventions on more downstream and patientrelevant outcomes (e.g., mortality, symptoms, adverse drug events, hospitalizations) was apparent from the reviewed evidence.

The sickest patients in the community are recently hospitalized elders. A substantial component of their morbidity and mortality is adverse drug events (ADEs). 1–3 Moreover, the oldest, sickest patients are at highest risk for ADEs; they have the most complex and hazardous medication regimens but the fewest social and economic resources and the least physiologic reserve. 4 This dangerous milieu frequently contributes to avoidable healthcare resource utilization, morbidity, and even mortality. 5

As part of a larger plan to create a toolkit of evidence-based practices to improve medication management for recently hospitalized elders, we sought first to systematically review interventions in 3 domains encompassing much of medication management: postdischarge medication reconciliation, polypharmacy, and medication adherence. We address polypharmacy here; findings for the other 2 domains will be published subsequently as separate systematic overviews.

Polypharmacy is a major contributor to ADEs among frail elders, especially among those recently hospitalized. The most common definition of polypharmacy is strictly numerical, referring to the use of multiple medications daily. 6 It has been argued, however, that a specific number of drugs does not indicate appropriateness of therapy, as all drugs may be necessary and appropriate for treatment. 6 Therefore, there has been a shift toward the term inappropriate polypharmacy , which describes treatment where a patient has multiple morbidities and/or a complex condition that is being managed with more than 1 medicine and where the potential harms outweigh the potential benefits. 7

Because polypharmacy is an area of intense interest, interventions addressing polypharmacy have generated hundreds of primary studies and dozens of systematic reviews (SRs). Elucidating the central findings of this literature can be unwieldy due not only to its volume but also because findings may differ by study setting and population, intervention characteristics, outcomes measured, analytic methods, sample sizes, and even differing interpretations. SRs have gained acceptance as a robust methodology to efficiently distill and summarize prior findings. However, because SRs may themselves be subject to the aforementioned concerns, especially in areas in which several SRs have been conducted, some researchers have encouraged the use of systematic overviews of SRs. With dozens of existing SRs on polypharmacy already published, we applied this systematic overview methodology. This approach allowed us to capitalize on both the accepted methodology of systematically evaluating literature and a large body of secondary literature.

Using this approach, we sought to understand and summarize existing evidence regarding the potential of interventions addressing polypharmacy to improve patient-centered outcomes for older adults, specifically after hospitalization. Studies have shown that transitions of care (e.g., into and out of the hospital) are a particularly dangerous time in terms of medication safety due to factors such as discontinuity of care, changes in medication regimens, the rushed nature of the discharge process, and inadequate patient and/or caregiver education. 8 Although this overview provides a foundation for a toolkit targeting the postdischarge period, we considered interventions implemented across all time periods, with the idea that some successful interventions might be reconfigured for the postdischarge period, during which medication management is perhaps most challenging.

The systematic overview was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) statement 9 ; the PRISMA checklist used may be found in the supplementary material at www.ajhp.org ( eAppendix A ). For methodological guidance specific to systematic overviews of SRs, we also referred to published literature explicitly focused on this methodology. 10–13

Data sources and searches

We performed a literature search in February 2017 using the databases MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects (DARE). Two trained researchers developed search terms related to polypharmacy. The searches were limited to English-language articles published from January 2004 through February 2017, with a manual search of prior SR references to identify earlier or unpublished SRs. The search strategies are detailed in eAppendix B .

Selection of SRs

SRs (with or without meta-analyses) were eligible for review if they evaluated interventions addressing polypharmacy in adult patients. For the purposes of this overview, we considered an SR to be a summary of outcomes resulting from a detailed and comprehensive plan and search strategy for relevant evidence derived a priori. 14 We included SRs of studies with any study design and outcome. We excluded reviews focusing exclusively on interventions implemented in low- to middle-income countries due to differences in care practices and healthcare infrastructure. We excluded SRs focused on interventions, conditions, or patients unlikely to inform readmission prevention among older adults, such as those focused on optimizing antipsychotic medications and antiretroviral regimens for patients with HIV infection. However, we did not restrict inclusion to the inpatient setting, as patients from other settings such as skilled nursing facilities and adult care homes may be relevant due to their age and comorbidities.

Two trained reviewers independently screened titles and abstracts using the prespecified inclusion and exclusion criteria. Next, 2 reviewers retrieved and examined full-text publications to determine eligibility. Research team members resolved discrepancies at the title-and-abstract and full-text screening levels by consensus in group meetings.

Quality evaluation

We assessed the methodological quality of each relevant SR using the validated Assessment of Multiple Systematic Reviews (AMSTAR) instrument. 15 The tool contains 11 requisite items that are rated as present or absent, such that each SR may receive a score ranging from 0 to 11. Two reviewers independently applied the instrument. Discrepancies were reconciled through oral discussion. SRs with an AMSTAR score below 8 were excluded from the data synthesis, as that is a commonly applied threshold for high-quality SRs.

Data extraction

For included SRs, 2 research team members independently extracted data related to key characteristics using a standardized data extraction tool. Extracted variables included dates of literature search, number and design of included primary studies, intervention type(s), patient population(s), setting(s), primary outcome measure(s), presence of meta-analytic techniques and any pooled estimates, and major conclusions regarding intervention effectiveness. Reviewers compared extracted data and reconciled discrepancies through oral discussion.

Quality of evidence

We assessed the quality of evidence for each conclusion within each SR by applying Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. 16 We used objective criteria to assign a level of evidence in the following GRADE domains: study design; study quality; consistency; directness; and other modifying factors, including data imprecision and strength of effect estimates. We did not assess the quality of the individual studies within the SRs but reported the risk of bias of studies as documented in the SRs. One author assessed GRADE level of evidence for each SR.

We examined each SR’s major conclusions regarding the effectiveness of intervention strategies for the reported primary outcomes and classified authors’ conclusions into 1 of 4 distinct categories: (1) a positive association between intervention strategy and outcome, (2) a negative association between intervention strategy and outcome, (3) a null association between intervention strategy and outcome, and (4) preclusion from drawing conclusions due to limited or low-quality studies. We also documented whether conclusions were based on quantitative (meta-analytic) or qualitative assessments.

Study selection

Our literature search identified 300 articles ( Figure 1 ). After screening titles and abstracts, we selected 18 citations for full-text SR review. After reviewing the full-text versions of these articles, we identified 11 articles that met the inclusion criteria. 17–27 Of these 11 articles, 1 was an older version of a more recent Cochrane SR 26 and 1 was a peer-reviewed journal version of a Cochrane SR. 27 To avoid redundancy, we classified these 2 articles as duplicates. We then assessed the methodological quality of the remaining 9 SRs. 17–20 , 22 , 24 , 26 , 27 Six of these SRs received an AMSTAR score of 8 or higher. We reported on and synthesized the findings of these 6 SRs. 17–20 , 22 , 24

PRISMA flow diagram.

Study characteristics

Table 1 shows the major characteristics of included SRs . All 6 SRs were published during the period 2014–2017. 17–20 , 22 , 24 Half ( n = 3) of the SRs were published as Cochrane SRs, 17 , 18 , 24 whereas the remainder were published in peer-reviewed journals. 19 , 20 , 22 Four of the SRs included meta-analytic techniques for pooling outcome data. 18 , 19 , 22 , 24 Five SRs restricted study populations to older adults, 17 , 19 , 20 , 22 , 24 whereas 1 included only individuals with gastroesophageal reflux disease taking proton pump inhibitors. 18 Of the 5 SRs focused on older adults, 4 were not restricted to patients of a specific disease type, 17 , 19 , 22 , 24 while 1 focused on patients with severe dementia. 20 The care settings discussed in the SRs varied widely; 2 SRs included only studies in nursing or care homes, 17 , 20 1 included studies in an outpatient setting only, 18 and 3 included studies in mixed settings such as hospitals, care facilities, and outpatient or primary care. 19 , 22 , 24

Summary of Included Systematic Reviews ( n = 6) a

a GRADE = Grading of Recommendations Assessment, Development and Evaluation; RCT = randomized, controlled trial; PPI = proton pump inhibitor; GI = gastrointestinal; RR = relative risk; CI = confidence interval; OR = odds ratio; ADE = adverse drug event; NA = Not applicable;.

All 6 SRs focused broadly on 1 of 2 major categories of polypharmacy interventions: (1) deprescribing 18 , 22 and (2) any intervention aimed at optimizing prescribing. 17 , 19 , 20 , 24 Among the 2 SRs focused on deprescribing, 18 , 22 one focused on the deprescribing of proton pump inhibitors 18 and the other assessed the deprescribing of 1 or more medications. 22 Interventions for the deprescribing of proton pump inhibitors included on-demand deprescribing and abrupt stopping of medication. 18 Deprescribing interventions for 1 or more medications included both patient-specific efforts led by a doctor, pharmacist, nurse, or multidisciplinary team, often incorporating medication review, and generalized education programs aimed at doctors and nurses. 22 Medication optimization interventions implemented in adult care homes consisted of medication review by pharmacists and doctors, multidisciplinary case conferencing, provider education, and clinical decision support. 17 , 20 Interventions aimed at medication optimization in primary and inpatient care settings included pharmacist-led medication review using tools such as the Medication Appropriateness Index and the Screening Tool of Older Persons’ Potentially Inappropriate Prescriptions (STOPP)/Screening Tool), pharmacist-provided patient education, provider education, multidisciplinary team–led medication review, and computerized decision support. 19 , 24

Major study conclusions

Primary outcomes assessed by the SRs were extremely varied ( Table 2 ). The 2 SRs evaluating deprescribing interventions assessed mortality, symptoms, drug use, and patient satisfaction. Page et al. 22 conducted a meta-analysis of 116 studies of patient-specific interventions and reported that mortality was significantly reduced in nonrandomized studies (pooled odds ratio [OR], 0.32; 95% confidence interval [CI], 0.17–0.60) and in randomized studies (pooled OR, 0.62; 95% CI, 0.43–0.88); however, non–patient-specific interventions had a null effect on mortality in both randomized studies (pooled OR, 0.82; 95% CI, 0.61–1.11) and randomized studies (pooled OR, 1.21; 95% CI, 0.86–1.69). The GRADE quality of evidence on which these conclusions were based was low. In the other SR focused on deprescribing, Boghossian et al. 18 reported that on-demand deprescribing of proton pump inhibitors could reduce pill burden, measured as pill use per week per patient (pooled mean difference with intervention versus continued use, –3.79 pills; 95% CI, –4.73 to –2.84 pills) but also noted a statistically significant increase in symptoms (pooled risk ratio [RR], 1.71; 95% CI, 1.31–2.21) and decreased patient satisfaction (pooled RR, 1.82; 95% CI, 1.26–2.65). The quality of evidence for the outcomes of pill burden, symptoms, and patient satisfaction were assessed as moderate, low, and very low, respectively. 18

Major Conclusions Reported in Included Systematic Reviews and GRADE Level of Supporting Evidence a

a The plus and minus symbols denote improved and worsened outcomes, respectively; the equal sign denotes that outcome was assessed and investigators reported no effect; the question mark symbol denotes outcome was assessed and investigators were precluded from drawing conclusions due to limited or low-quality studies.

b Conclusion based on meta-analytic data pooling.

In the 2 SRs that examined the effectiveness of polypharmacy interventions aimed at optimizing prescribing, 17 , 19 , 20 , 24 the primary outcomes assessed varied widely and included mortality, drug use, medication appropriateness, ADEs, and hospitalizations. Neither of 2 SRs assessing the effect on mortality found that interventions reduced it. 17 , 19 Of the 2 SRs reporting on medication appropriateness, 20 , 24 the first used meta-analytic pooling to conclude that polypharmacy interventions, such as pharmaceutical care, have been effective at improving medication appropriateness; however, this conclusion was based on low-quality or very low-quality evidence. 24 The second SR reported that multidisciplinary teams, medication review, and provider education were the most effective intervention components for improving medication appropriateness; quality of evidence for these conclusions was very low. 20 The following additional outcomes were assessed in this subset of SRs, but no evidence for the effectiveness of prescribing-focused polypharmacy interventions was found: medication-related problems, including ADEs 17 , 24 ; drug use 19 ; medication adherence 24 ; quality of life 24 ; and hospitalizations. 17 , 19

Quality evaluations

The quality assessments of the included SRs using the AMSTAR instrument are described in eAppendix C . The median score was 10.5 (interquartile range, 9.5–11.0).

In summary, we found 6 high-quality SRs on interventions addressing polypharmacy, all of which were published after 2013. Five of these SRs focused on older adults. Four SRs focused on interventions that optimized prescribing, whereas 2 concentrated on deprescribing exclusively. Both SRs considering the outcome of medication appropriateness found improvements. However, these SRs were based on low-quality or very low-quality evidence. Furthermore, the clinical significance of improvements in medication appropriateness was noted to be “unclear” in one review. 24 With respect to patient-centered outcomes (mortality, morbidity, and healthcare resource utilization), there was little evidence of benefit except for 1 SR reporting significant reductions in drug use with deprescribing interventions.

The only other SR that presented evidence of more downstream, patient-centered benefit was that of Page et al., which found in a subanalysis that mortality was “significantly reduced when patient-specific deprescribing interventions were applied in [randomized controlled trials].”  22 This SR was notable for its liberal inclusion of primary studies. In all, it considered results from 132 publications describing 116 studies. Upon applying GRADE criteria, the level of evidence for this SR conclusion was assessed as low. In light of this low quality of evidence, we are hesitant to accept this conclusion without further study. Furthermore, in seeking to isolate which specific interventions might reduce mortality, it was disappointing that none of the component studies achieved statistical significance alone or clearly stood out as driving the pooled estimate.

Nonetheless, there is face validity to the idea that patient-specific deprescribing interventions would be more successful than less tailored interventions (e.g., generalized educational campaigns). Face validity is an accepted criterion for determining which predictors to include in a model, and we would advocate for its use in this context of low-quality evidence. Our major practical insight from this overview is a recommendation that provider organizations interested in addressing polypharmacy concentrate first on patient-specific deprescribing interventions. Such specificity might be achieved via clinical decision support, via pharmacy personnel, or by other means. One example of such an intervention is found in the SR by Kroger et al., 20 wherein Verrue et al. 28 found that medication review conducted by pharmacists using the Beers criteria (including 11 patient-specific advisories for potentially hazardous drug–disease and drug–syndrome interactions) resulted in increased medication appropriateness, as measured by several instruments.

Although we are unaware of any other overview of SRs in this area with which to compare our findings, the different component SRs are themselves perhaps the best comparators. The 3 Cochrane SRs, which are known for their excellent methodological standards, all noted the poor quality of existing evidence and the need for more research. The other included SRs tended to include more primary studies but were no more likely to find interventions to be effective.

In organizing and assessing SR-level evidence of polypharmacy interventions, our overview helped to map out existing evidence on the effectiveness of such interventions by population, measured outcomes, and intervention types. Our findings suggest that there is significant interest in interventions to improve polypharmacy, with the published literature assessing a wide variety of patient outcomes. We hope that our work provides decision makers, as well as physicians and other healthcare professionals, with a clear understanding of the evidence available in this area and helps direct readers to more targeted information. Beyond summarizing and enhancing the accessibility of existing literature, our overview highlights the absence of high-quality evidence to inform high-quality SRs. Although our overview identified 6 SRs that employed high-quality methodology, there were few strategies for which high-quality evidence of effectiveness was found.

Our work has several limitations. As with all reviews of existing literature, a central limitation of our review was the quality and scope of existing evidence. Just as SRs often address quality concerns by focusing on high-quality primary literature, we focused on high-quality SRs. Although this quality-based filtering tended to exacerbate scope deficiencies, the included SRs offered a range of strict to lenient methodological perspectives, such that results from a variety of primary studies were incorporated. Furthermore, even though our clinical area of interest involved older adults at care transitions, we included SRs focusing on other care settings. This broad scope was intentional and stemmed from an idea that polypharmacy interventions found to be successful in other (e.g., outpatient) settings might also offer benefit at care transitions. Because few studies in the polypharmacy literature focus on care transitions, limiting a search to this care setting would have required extreme compromises in scope or quality.

A second limitation involved our distance from the primary literature. Although we chose to conduct an overview of SRs to capitalize on prior work, we also recognized that this methodology may miss some of the nuance appreciable in an SR or by conducting primary research. Finally, the fact that all of the identified SRs were published after 2013 suggests that polypharmacy is an emerging area, with a literature base that may still be rapidly evolving. Further high-quality studies are needed to assess the impact of efforts of reduce polypharmacy on patient care, especially among older adults undergoing transitions of care.

Disclosures

This research was supported by the American Society of Health-System Pharmacists (ASHP) Research and Education Foundation and the National Institute on Aging of the National Institutes of Health under awards K23AG049181 (JMP) and R01AG058911 (JMP). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Supplementary Material

Zxz196_suppl_supplemental-appendix-a, zxz196_suppl_supplemental-appendix-b, zxz196_suppl_supplemental-appendix-c, contributor information, carmel m hughes.

8 School of Pharmacy, Queen’s University Belfast, Belfast, UK

Cynthia A Jackevicius

9 Department of Pharmacy Practice and Administration, Western University of Health Sciences, Pomona, CA, and VA Greater Los Angeles Healthcare System, Los Angeles, CA

Denis O’Mahony

10 Department of Medicine (Geriatrics), University College Cork, Cork, Ireland

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• Volume 5, Issue 12
• Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review
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• Janine A Cooper 1 ,
• Cathal A Cadogan 1 ,
• Susan M Patterson 2 ,
• http://orcid.org/0000-0002-5992-3681 Ngaire Kerse 3 ,
• Marie C Bradley 1 ,
• Cristín Ryan 1 ,
• Carmel M Hughes 1
• 1 School of Pharmacy, Queen's University Belfast , Belfast , UK
• 2 Belfast , UK
• 3 Department of General Practice and Primary Health Care , University of Auckland , Auckland , New Zealand
• Correspondence to Professor Carmel M Hughes; c.hughes{at}qub.ac.uk

Objective To summarise the findings of an updated Cochrane review of interventions aimed at improving the appropriate use of polypharmacy in older people.

Design Cochrane systematic review. Multiple electronic databases were searched including MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials (from inception to November 2013). Hand searching of references was also performed. Randomised controlled trials (RCTs), controlled clinical trials, controlled before-and-after studies and interrupted time series analyses reporting on interventions targeting appropriate polypharmacy in older people in any healthcare setting were included if they used a validated measure of prescribing appropriateness. Evidence quality was assessed using the Cochrane risk of bias tool and GRADE (Grades of Recommendation, Assessment, Development and Evaluation).

Setting All healthcare settings.

Participants Older people (≥65 years) with ≥1 long-term condition who were receiving polypharmacy (≥4 regular medicines).

Primary and secondary outcome measures Primary outcomes were the change in prevalence of appropriate polypharmacy and hospital admissions. Medication-related problems (eg, adverse drug reactions), medication adherence and quality of life were included as secondary outcomes.

Results 12 studies were included: 8 RCTs, 2 cluster RCTs and 2 controlled before-and-after studies. 1 study involved computerised decision support and 11 comprised pharmaceutical care approaches across various settings. Appropriateness was measured using validated tools, including the Medication Appropriateness Index, Beers’ criteria and Screening Tool of Older Person's Prescriptions (STOPP)/ Screening Tool to Alert doctors to Right Treatment (START). The interventions demonstrated a reduction in inappropriate prescribing. Evidence of effect on hospital admissions and medication-related problems was conflicting. No differences in health-related quality of life were reported.

Conclusions The included interventions demonstrated improvements in appropriate polypharmacy based on reductions in inappropriate prescribing. However, it remains unclear if interventions resulted in clinically significant improvements (eg, in terms of hospital admissions). Future intervention studies would benefit from available guidance on intervention development, evaluation and reporting to facilitate replication in clinical practice.

• polypharmacy
• systematic review
• interventions
• GERIATRIC MEDICINE

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

http://dx.doi.org/10.1136/bmjopen-2015-009235

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Strengths and limitations of this study

The updated Cochrane review that is summarised in this paper used systematic and rigorous methods to identify, appraise and synthesise available evidence for the effectiveness of interventions aimed at improving appropriate polypharmacy for older patients.

No language restrictions were placed on the search strategy and no apparent publication bias was detected.

The included studies were limited by their small sample sizes and poor quality owing to risks of bias, with little opportunity to pool data.

Despite improvements in appropriate prescribing, it must be noted that assessments were based on surrogate markers of appropriate polypharmacy and the clinical significance of these improvements in terms of other relevant outcomes, for example, hospital admissions, is unclear.

Several studies focused on reducing the number of medications, rather than improving the overall appropriateness of prescribing, including underprescribing.

Introduction

The WHO has predicted that the number of older people (conventionally defined as ≥65 years) worldwide will reach 1.5 billion by 2050. 1 , 2 This population growth poses significant challenges for healthcare systems, as older people use a disproportionate amount of healthcare resources (eg, medications). 3 , 4

Although there is no single agreed definition of the term ‘polypharmacy’, 5 , 6 this has been described as the use of four or more medications. 7 The potential for negative outcomes with the use of multiple medications in older people is well documented (eg, adverse drug events (ADEs), non-adherence, drug interactions). 8 , 9 A critical objective that poses considerable challenges for healthcare professionals (HCPs) is to obtain a balance between aggressively treating diseases and avoiding medication-related harm. 10

Polypharmacy has been identified as the principal determinant of potentially inappropriate prescribing (PIP) in older people. 11 The term PIP encompasses overprescribing, misprescribing and underprescribing. 12 Underprescribing is an important clinical issue because patients with polypharmacy have an increased likelihood of not receiving potentially beneficial, clinically indicated medications compared with patients receiving fewer medications. 13 Accordingly, a range of assessment tools have been developed to identify PIP in older people and to optimise prescribing. 14

Despite the potential for negative consequences in older patients receiving polypharmacy, there is increasing acceptance that the prescribing of multiple medications can be appropriate, and under certain circumstances, should be encouraged. 15 , 16 Thus, polypharmacy can refer to the prescribing of many drugs (appropriately) or too many drugs (inappropriately). 16 Achieving appropriate polypharmacy involves prescribing the correct drugs under the appropriate circumstances to treat the right diseases. Ensuring appropriate polypharmacy is of considerable importance because PIP is highly prevalent in older people and has considerable cost implications for healthcare systems. 11 , 17

The updated Cochrane review that is summarised in this paper 18 sought to determine the effectiveness of interventions aimed at improving appropriate polypharmacy in older people. A recent Cochrane publication, which consisted of an overview of systematic reviews, highlighted that few reviews have considered the implications of polypharmacy on interventions seeking to improve safe and effective medicine use by consumers, including patients and their carers. 19

This systematic review followed the Cochrane Collaboration methodology, and is available from the Cochrane Library. 18

Inclusion criteria

This review looked at interventions in any setting that targeted older people (≥65 years) who had more than one long-term medical condition and were receiving polypharmacy (≥4 regular medications).

Randomised controlled trials (RCTs), including cluster RCTs (cRCTs), non-randomised controlled clinical trials, controlled before-and-after studies (CBAs) and interrupted time series (ITS) studies meeting the Effective Practice and Organisation of Care (EPOC) specification 20 were eligible for inclusion. Any type of intervention that aimed to improve appropriate polypharmacy in any healthcare setting was eligible for inclusion. With the exception of ITS design, studies had to compare the intervention against usual care as defined by the study. Interventions studies that focused on people with single long-term conditions or who were receiving short-term polypharmacy, for example, chemotherapy, were excluded. No language restrictions were applied.

Outcome measures

Primary outcomes were the change in the prevalence of appropriate polypharmacy and the number of hospital admissions. As there is no universally applicable tool to assess polypharmacy appropriateness in older people, validated measures of inappropriate prescribing (eg, Beers’ criteria 21 and the Medication Appropriateness Index (MAI) 22 ) were used as surrogate markers. Studies using expert opinion alone to determine medication appropriateness were excluded.

The following secondary outcomes were included: medication-related problems (eg, adverse drug reactions, medication errors); medication adherence; health-related quality of life (assessed by a validated method).

Search methods for identification of studies

Search strategies (see full review 18 ) comprised keywords and controlled vocabulary such as MeSH (medical subject headings). The following electronic databases were searched for primary studies (all records through to November 2013): Evidence-Based Medicine Reviews, Cochrane Central Register of Controlled Trials, Ovid SP, Health Technology Assessment, National Health Service Economic Evaluation Database, Cochrane Methodology Register, American College of Physicians Journal Club, the Joanna Briggs Institute, MEDLINE, EMBASE, CINAHL, EBSCO Host, PsycINFO.

Related systematic reviews were identified through the Cochrane Database of Systematic Reviews and Database of Abstracts of Reviews of Effects. Authors were contacted for further information where necessary.

Data screening and extraction

The retrieved titles and abstracts were screened independently by two authors against inclusion criteria. Where uncertainty occurred, full-text articles were retrieved and assessed. Any remaining uncertainty or disagreement was resolved by consensus through discussion with another author. Data were extracted independently by two authors.

Assessment of risk of bias

Two authors independently assessed risk of bias using the Cochrane Collaboration's assessment tool 23 and used GRADE (Grades of Recommendation, Assessment, Development and Evaluation) to assess the quality of the evidence for each primary outcome for which data were pooled. 24

Data analysis

Intervention effect was measured using validated assessment tools of prescribing appropriateness (eg, summated MAI, Beers’ criteria). The mean and SD were calculated for summated MAI and number of Beers’ drugs postintervention in each study's intervention and control groups. Where available, the mean change (and SD) from pre to post was determined in the intervention and control group. Based on these numbers, the mean differences were calculated and results presented with 95% CIs. Estimates for dichotomous outcomes from individual studies are presented as risk ratios with 95% CIs.

If at least two studies were homogeneous in terms of participants, interventions and outcomes, the results were pooled in a meta-analysis. In the presence of statistical heterogeneity (I 2 statistic >50%), a random-effects model was applied for meta-analysis. In the absence of statistical heterogeneity, a fixed-effects model was used.

Sensitivity analyses were conducted for studies with a high risk of bias or a unit of analysis error. Where outcome data could not be combined, a narrative summary was reported. Reporting bias was examined using risk of bias tables and funnel plots corresponding to meta-analysis of the primary outcome to assess potential publication bias. Data analysis was conducted using RevMan V.5.2.

Results of the search

Figure 1 provides an overview of the search. In this update, two studies were identified and added, 25 , 26 bringing the total number of included studies to 12. It was not possible to include data from these two studies in any meta-analysis because data were skewed or participants were not considered to be homogeneous with other study populations.

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PRISMA flow chart: risk of bias in included studies (n=12).

The included studies consisted of eight RCTs, 25–32 two cRCTs 33 , 34 and two CBAs. 35 , 36 In total, 22 438 older patients were involved, the majority of whom were female (65.6%). On average, patients were 76 years old (based on 12 studies) and receiving nine medicines at baseline (based on 11 studies).

The studies were conducted in three types of settings ( table 1 ): hospital (outpatient clinics); 27 , 29 , 30 hospital/care home interface; 28 inpatient setting; 25 , 26 , 31 primary care; 32 , 34 nursing homes. 33 , 35 , 36 The studies were carried out in five countries: Australia (two studies), Belgium (two studies), Canada (two studies), Ireland (one study) and the USA (five studies).

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Characteristics of included studies

Description of interventions

All interventions were classified as organisational according to EPOC definitions.

Eleven studies examined complex, multifaceted, pharmaceutical care-based interventions in various settings, using validated assessment criteria to give recommendations on improving the appropriateness of prescribing. In all settings, pharmaceutical care (ie, responsible provision of drug therapy to achieve definitive outcomes that improve patients’ quality of life 37 ) was commonly provided by pharmacists working closely with other HCPs.

The models of pharmaceutical care provided were complex and variable. For example, pharmacists conducted independent medication reviews either using patient notes 28 , 33 or with patients during a face-to-face encounter. 27 , 29–32 , 34 In other cases, recommendations from medication reviews were followed up with prescribers and other HCPs. 27–29 , 31 , 33

Patient education was provided as part of the intervention in four studies involving face-to-face interventions. Patients were given information about their prescribed medications (eg, administration) and specialised medication scheduling tools (eg, monitored dosage systems) to encourage adherence. 27 , 29 , 31 , 32

Education was also provided to prescribers and other HCPs involved in the multidisciplinary team as part of the intervention in five studies. 27–29 , 31 , 33

The only unifaceted study 34 examined computerised decision support (CDS) provided to general practitioners in their own practices.

The timing of intervention provision was variable. A number of interventions were delivered at specific time points, for example, hospital admission, attendance at outpatient clinics, 27 , 29 , 30 , 32 nursing home visits, 33 , 35 , 36 hospital discharge to a nursing home. 28 In other cases, interventions were delivered over a period of time, such as during hospital inpatient stay and at discharge. 30 , 31

Risk of bias in included studies

The included studies showed evidence of potential bias ( figure 2 ). Only three studies showed evidence of allocation concealment 25 , 28 , 33 and only one study demonstrated protection against contamination. 33

Risk of bias in included studies (n=12).

Funnel plots of postintervention estimates of the change in MAI and summated MAI showed little evidence of publication bias. 18

GRADE approach to quality assessment

Based on GRADE, 24 the overall quality of evidence for each primary outcome for which data were included in a meta-analysis was rated as ‘low’ or ‘very low’ ( table 2 ). Although all studies included in the meta-analyses involved randomisation, and, where assessed, no evidence of publication bias was found, 18 the quality of evidence was downgraded for each outcome based on other GRADE considerations (ie, study limitations, consistency of effect, imprecision, indirectness).

Summary of findings table

Prevalence of appropriate use of polypharmacy

The primary outcome of interest was the change in the prevalence of appropriate polypharmacy. Seven validated measures of prescribing appropriateness were used in the included studies, either alone or in combination.

Medication Appropriateness Index

The MAI was used in three ways to assess the appropriateness of polypharmacy. First, data from four studies (210 intervention participants, 214 control participants) were pooled in a meta-analysis using the change in summated MAI score from baseline to follow-up. 27 , 28 , 31 , 33 There was a greater overall reduction in the mean change in summated MAI score in the intervention group compared with the control (mean difference −6.78, 95% CI −12.34 to −1.22; table 2 ). There was marked heterogeneity between the studies (I 2 =96%, p<0.0001). Sensitivity analyses in which one study with a unit of analysis error (nursing homes were the unit of randomisation but the analysis was conducted at patient level) 33 and another study with a large effect size and high risks of bias 31 were removed from analysis showed consistent changes in summated MAI with variable effects on heterogeneity ( table 2 ).

Second, postintervention pooled data from five studies 27–31 (488 intervention participants, 477 control participants) showed a lower summated MAI score (mean difference −3.88, 95% CI −5.40 to −2.35) in the intervention group compared with the control group ( table 2 ). There was little evidence of heterogeneity between these estimates (I 2 =0%). This was consistent with the findings of Gallagher et al , 25 which were not included in the meta-analysis because the data were skewed.

Third, one study 32 expressed the MAI score as the number of inappropriate prescriptions. The percentage of inappropriate prescriptions decreased in all MAI domains (n=10) in the intervention group and increased in five domains in the control group. These data could not be included in a meta-analysis.

Beers’ criteria

Pooled data from two studies 30 , 31 (298 intervention participants, 288 control participants) showed that intervention group participants were prescribed fewer Beers’ drugs than control group participants postintervention (mean difference −0.1, 95% CI −0.28 to 0.09; I 2 =89%; table 2 ).

Spinewine et al 31 also reported the proportion of patients taking one or more Beers’ drugs preintervention and postintervention. Similar improvements were reported in the proportion of intervention and control group patients receiving one or more Beers’ drugs between hospital admission and discharge (OR 0.6, 95% CI 0.3 to 1.1). As this was the only study to report the results in this format, meta-analysis was not possible.

McLeod criteria

One study used the McLeod criteria 38 to identify the initiation and discontinuation rates of 159 prescription-related problems. 34 The reported relative rate of initiation of inappropriate prescriptions for the intervention group was 0.82 (95% CI 0.69 to 0.98). However, the intervention did not appear to have an effect on the relative rate of discontinuation of pre-existing prescription-related problems (1.06, 95% CI 0.89 to 1.26). Meta-analysis was not possible as these criteria were not used in other studies.

STOPP and START criteria

Two studies 25 , 26 used the Screening Tool of Older Person's Prescriptions (STOPP) criteria to screen for PIP in older patients admitted to hospital. Gallagher et al 25 reported lower (p<0.001) proportions of patients in the intervention group compared with the control group with one or more STOPP criteria medications for each of the postintervention assessments (discharge, 2, 4 and 6 months postdischarge). Dalleur et al 26 reported no difference in the proportion of patients with one or more STOPP criteria medications from hospital admission to discharge between the intervention and control groups (OR 1.5, 95% CI 0.49 to 4.89, p=0.454). However, at group level, the discontinuation rate of potentially inappropriate medications as identified using STOPP criteria was higher in the intervention group compared with the control group (OR 2.75, 95% CI 1.22 to 6.24, p=0.013). Data from these studies were not pooled because participants were not homogeneous.

In the Gallagher et al 25 study, the Screening Tool to Alert doctors to Right Treatment (START) criteria were also used. For each of the postintervention assessments (discharge, 2, 4 and 6 months postdischarge), lower proportions of patients with one or more START criteria medications were reported in the intervention group compared with the control group (p<0.001). This was the only study that used these criteria; therefore, meta-analysis was not possible.

Assessment of Underutilisation of Medication

Two studies assessed under-use of medication using the Assessment of Underutilisation of Medication (AUM) index. 25 , 30 Gallagher et al 25 reported a greater reduction in the proportion of intervention group patients with prescribing omissions postintervention (by the AUM index) compared with the control group (absolute risk reduction 21.2%, 95% CI 13.3% to 29.1%). Schmader et al 30 reported a reduction in the number of conditions with omitted drugs postintervention in the intervention group relative to the control group; the difference in change in AUM score was −0.3 (p<0.0001). As each study assessed underprescribing on two different levels (ie, patient, medical condition), meta-analysis was not possible.

Spinewine et al 31 reported that the magnitude of the reduction in Assessing Care of Vulnerable Elderly (ACOVE) scores was greater in the intervention group (baseline score: 50.0, postintervention score: 14.6, p<0.001) compared with the control group (baseline score: 58.9, postintervention score: 44.4, p=0.02). Intervention patients were six times more likely than control patients to have at least one prescribing improvement based on these criteria (OR 6.1, 95% CI 2.2 to 17.0). Meta-analysis was not possible; no other studies used this outcome measure.

Hospital admissions

Five studies measured hospital admissions. 25 , 28 , 31 , 32 , 35 Two studies 25 , 31 reported no difference in hospitalisations between intervention and control groups at follow-up and the remaining studies reported some overall reductions in hospital admissions between the two groups. The statistical significance of these reductions varied based on the methods of assessment employed in the individual studies. Owing to differences in the measurement of hospital admissions and the expression of results, meta-analysis was not possible.

Secondary outcomes

Meta-analysis of secondary outcome assessments was not possible due to differences across studies in design and reporting. Evidence of the effect of the interventions on medication-related problems (six studies) 28–30 , 32 , 35 , 36 was conflicting. One study reported improved adherence scores in intervention patients. 32 No differences in HRQoL were reported between intervention and control groups at baseline or follow-up (two studies). 29 , 32

Given the association between polypharmacy and PIP in older people, 11 , 17 interventions to improve appropriate polypharmacy in this cohort are of considerable importance. Only two studies were added to the original review, bringing the total number of studies included in the updated review to 12. These two additional studies did not change the conclusions of the original review and serve to highlight the lack of intervention studies aimed at improving appropriate polypharmacy in older people that have been conducted to date. Coupled with the findings of Ryan et al , 19 it is evident that interventions targeting polypharmacy are under-researched at both the level of healthcare provider and recipient.

The included studies aimed to ensure the prescribing of appropriate medications to older people that enhanced their quality of life. However, several studies focused on reducing the number of prescribed medications without assessing underprescribing and, therefore, did not consider the overall appropriateness of prescribing. This needs to be addressed as underprescribing is common in older populations with variable prevalence rates depending on medication classes and care settings. 39 Nevertheless, the interventions reduced inappropriate prescribing with resultant improvements in the appropriateness of polypharmacy in older patients. For example, pooled data showed a significant reduction in intervention group patients’ mean MAI score compared with control group patients ( table 2 ). Assessments involving other validated tools also showed improvements in the appropriateness of prescribing. Although these results are promising and indicate that the interventions described in this review were successful in improving appropriate polypharmacy, the clinical impact is not known. For example, it is unclear to what extent a reduction in the magnitude of 3.88 in summated MAI score (a weighted average rating based on 10 assessment criteria) represents a clinically significant reduction in the risk of harm ( table 2 ). This is because the predictive validity of many tools that are currently used to evaluate prescribing appropriateness has not been established. 40 Therefore, the impact of improvements on the overall appropriateness of prescribing on clinical outcomes is unclear.

The findings from our review are consistent with other reviews for a number of outcomes. For example, a related Cochrane review of interventions to optimise prescribing for older people in care homes 41 found no evidence of an intervention effect on ADEs and hospital admissions. Other studies of interventions conducted across various settings have also been unable to detect the effect of pharmaceutical care on these outcomes. 42 , 43

Despite the uncertainty as to the effect of the identified interventions to improve appropriate polypharmacy on a number of outcome measures, this review provides useful guidance for the direction of future research.

Strengths and weakness of this review

The updated Cochrane systematic review that is summarised in this paper represents the most comprehensive overview, using a rigorous methodology, of the existing body of evidence of the effectiveness of interventions aimed at improving appropriate polypharmacy in older patients. Previous reviews have assessed interventions targeting medication use in older people, but have not focused on polypharmacy or exclusively used validated assessment tools. 7 , 44 No language restrictions were placed on the search strategy and all of the studies were published in English, including those studies that were conducted in countries where English is not the first language. Despite the small number of included studies, no apparent publication bias was detected.

Overall, the included studies were limited by their small sample sizes and poor quality, with little opportunity to pool data. There was evidence of potential biases ( figure 2 ) in the studies which may have influenced the reported effect estimates. Although improvements in appropriate polypharmacy were noted, the findings of meta-analyses relating to MAI scores should be treated cautiously, as the intervention did not seem to work consistently across all studies.

It must also be noted that assessments were based on surrogate markers and the clinical significance of these improvements in terms of clinically relevant outcomes, for example, hospital admissions, is unclear as meta-analysis was not possible. Several studies focused on reducing the number of medications, rather than improving the overall appropriateness of prescribing, including underprescribing.

Implications for clinical practice and future research

Inappropriate prescribing is highly prevalent and commonly associated with polypharmacy in older populations. 11 , 17 However, rigorous evaluations of interventions seeking to address this are lacking. The findings of this review indicate that pharmaceutical care-based interventions appear to improve appropriate polypharmacy in older people based on observed reductions in inappropriate prescribing, especially when the provision of care involves a multidisciplinary element. 25 , 27–33 CDS showed potential as an intervention, although this was evaluated in only one study. 34

Surrogate markers of appropriate polypharmacy were used as there is no universally applicable tool to assess the appropriateness of polypharmacy. Despite observed improvements in prescribing appropriateness, it is unclear if the identified interventions resulted in clinically significant improvements, for example, reduction in medication-related problems. In addition to the above noted issues with the predictive validity of existing tools for assessing appropriate prescribing, many studies did not assess outcomes such as adherence, hospitalisations and quality of life, which are arguably the critical outcomes for patients and some studies may have lacked sufficient follow-up periods to detect any significant changes. Future studies should focus on these types of clinical outcomes.

Overall, the quality and reporting of included studies was poor. Future research should pay greater attention to available guidance on intervention development and evaluations 45 to ensure rigour in study design. Methods of specifying and reporting complex interventions, 46 as well as their implementation strategies, are necessary to strengthen the evidence base required for interventions to be more effective, implementable and replicable across different settings. 47 , 48

Future studies should use clearer definitions of appropriate polypharmacy because the term ‘polypharmacy’ can be both negative and positive, and this duality of meaning makes objective research difficult. 49 A recent report by the King's Fund in the UK 6 raised the need to reconsider current definitions of polypharmacy due to the increasing numbers of medications being prescribed to patients. The publication of this report 6 coincided with the abstract screening process in the update of this review. Therefore, for the purpose of this update, the definition of polypharmacy was not changed from the original review. However, future updates may need to reconsider the criteria used to define polypharmacy.

Development of new, universal, easily applied, valid and reliable outcome measures to evaluate effectiveness of interventions should be a priority for future research. Ideally the measure should be globally applicable across various healthcare and cultural settings; for example, STOPP/START are validated instruments that could help to fulfil this need. 50 In contrast to other tools, such as the Beers’ criteria, STOPP/START have been specifically developed for use in European countries. Although STOPP/START-related research is still at a relatively early stage, the criteria are endorsed by the European Union Geriatric Medicine Society and set for wider application in future research. 51 The use of START offers a promising strategy to decrease underprescribing 39 and could serve to improve appropriate polypharmacy when combined with STOPP.

Conclusions

The findings of an updated Cochrane review that are summarised in this paper highlight the lack of existing intervention studies of suitable quality aimed at improving the appropriate use of polypharmacy in older patients. Overall, the interventions included in this review demonstrated benefits in this respect based on observed reductions in inappropriate prescribing. However, it remains unclear if interventions resulted in clinically significant improvements in terms of hospital admissions, medication-related problems and patients’ overall quality of life. Future studies would benefit from guidance relating to intervention development, evaluation and reporting. In addition, more detailed and systematic reporting of interventions in published papers could facilitate replication of effective interventions and uptake into clinical practice.

Acknowledgments

The authors would like to acknowledge the valuable input of Alexandra McIlroy (Queen’s University Belfast) and Michelle Fiander (EPOC Group) in development of the search strategy. They would also like to thank all members of the EPOC Group at Newcastle University, UK, led by Professor Martin Eccles, for their kind assistance with preparation of the protocol. They would also like to thank Julia Worswick (EPOC Group) for her assistance and Mike Steinman for his helpful comments. The authors would like to acknowledge the valuable input of Dr Chris Cardwell (Centre for Public Health, Queen's University Belfast) into data analysis.

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JAC and CAC are joint first authors.

Contributors JAC and CAC drafted the summary review. All authors contributed to, and agreed on, the final submission. SMP prepared the original review protocol under the direction of CMH, NK and CR Cardwell (CRC). CAC and CR were involved in updating the review. SMP undertook the database searches and reviewed the literature identified in the original review. CMH and CAC undertook the second review update including data extraction, risk of bias assessment and writing of the review update. MCB, NK and CR acted as independent co-review authors.

Funding This work was supported by The Dunhill Medical Trust (grant number: R298/0513) and the Research and Development Office, Northern Ireland, UK.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Data sharing statement No additional data are available.

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The Relationship of Continuity of Care, Polypharmacy and Medication Appropriateness: A Systematic Review of Observational Studies

• Systematic Review
• Open access
• Published: 27 March 2023
• volume  40 ,  pages 473–497 ( 2023 )

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• David Lampe   ORCID: orcid.org/0000-0003-3400-0861 1 ,
• John Grosser   ORCID: orcid.org/0000-0003-3890-5596 1 ,
• Daniel Gensorowsky   ORCID: orcid.org/0000-0001-9326-2963 2 ,
• Julian Witte   ORCID: orcid.org/0000-0003-2075-323X 2 ,
• Christiane Muth   ORCID: orcid.org/0000-0001-8987-182X 3 ,
• Marjan van den Akker   ORCID: orcid.org/0000-0002-1022-8637 4 , 5 , 6 ,
• Truc Sophia Dinh   ORCID: orcid.org/0000-0002-9774-6751 4 &
• Wolfgang Greiner   ORCID: orcid.org/0000-0001-9552-6969 1  

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Introduction.

Worldwide, polypharmacy and medication appropriateness-related outcomes (MARO) are growing public health concerns associated with potentially inappropriate prescribing, adverse health effects, and avoidable costs to health systems. Continuity of care (COC) is a cornerstone of high-quality care that has been shown to improve patient-relevant outcomes. However, the relationship between COC and polypharmacy/MARO has not been systematically explored.

The aim of this systematic review was to investigate the operationalization of COC, polypharmacy, and MARO as well as the relationship between COC and polypharmacy/MARO.

We performed a systematic literature search in PubMed, Embase, and CINAHL. Quantitative observational studies investigating the associations between COC and polypharmacy and/or COC and MARO by applying multivariate regression analysis techniques were eligible. Qualitative or experimental studies were not included. Information on the definition and operationalization of COC, polypharmacy, and MARO and reported associations was extracted. COC measures were assigned to the relational, informational, or management dimension of COC and further classified as objective standard, objective non-standard, or subjective. Risk of bias was assessed by using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.

Twenty-seven studies were included. Overall, substantial differences existed in terms of the COC dimensions and related COC measures. Relational COC was investigated in each study, while informational and management COC were only covered among three studies. The most frequent type of COC measure was objective non-standard ( n  = 16), followed by objective standard ( n  = 11) and subjective measures ( n  = 3). The majority of studies indicated that COC is strongly associated with both polypharmacy and MARO, such as potentially inappropriate medication (PIM), potentially inappropriate drug combination (PIDC), drug–drug interaction (DDI), adverse drug events (ADE), unnecessary drug use, duplicated medication, and overdose. More than half of the included studies ( n  = 15) had a low risk of bias, while five studies had an intermediate and seven studies a high risk of bias.

Conclusions

Differences regarding the methodological quality of included studies as well as the heterogeneity in terms of the operationalization and measurement of COC, polypharmacy, and MARO need to be considered when interpreting the results. Yet, our findings suggest that optimizing COC may be helpful in reducing polypharmacy and MARO. Therefore, COC should be acknowledged as an important risk factor for polypharmacy and MARO, and the importance of COC should be considered when designing future interventions targeting these outcomes.

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1 Background

Due to aging populations and multimorbidity, polypharmacy (taking multiple drugs simultaneously) is an increasing public health problem worldwide [ 1 , 2 , 3 , 4 , 5 ]. Across Europe, approximately one-third of people aged > 65 years are affected by polypharmacy [ 6 ]. Because of the heterogeneity of definitions [ 7 ] and due to different settings and populations studied, the worldwide prevalence of polypharmacy varies widely between 10 and 90% [ 8 ]. Studies have shown that polypharmacy is associated with potentially inappropriate prescribing [ 9 ] and several adverse health events [ 10 , 11 , 12 ]. Accordingly, polypharmacy directly and indirectly affects health care spending and causes avoidable costs [ 13 , 14 ]. Several interventions have been developed to tackle the growing problem of polypharmacy and associated adverse events; these interventions appear beneficial in terms of improving medication appropriateness-related outcomes (MARO), such as potentially inappropriate prescribing as measured by the Medication Appropriateness Index, Beers’ criteria, and the STOPP/START criteria. Yet, evidence of improvements in clinical outcomes (e.g., reduction of hospital admissions), including patient-reported outcomes, remains inconclusive [ 15 , 16 , 17 , 18 , 19 ].

Suboptimal care transitions and a lack of collaboration between health care providers (e.g., physicians) have been identified as major problems impeding optimal medication management processes and patient safety [ 20 , 21 , 22 , 23 ]. In this regard, continuity of care (COC), widely acknowledged as a cornerstone of high-quality care, is highly relevant [ 24 ]. According to Haggerty et al. [ 25 ], COC comprises three dimensions: relational continuity, representing an ongoing therapeutic relationship between a patient and one or more providers, informational continuity , representing the use of information on past events and personal circumstances to make current care appropriate for each individual, and management continuity , representing a consistent and coherent approach to the management of a health condition that is responsive to a patient’s changing needs. Furthermore, COC can be assessed using three types of measure: ‘objective standard measures’ (e.g., continuity indices), ‘objective non-standard measures’ (e.g., all other quantitative indices of patient–provider contact), and ‘subjective measures’ (patient-reported assessments of continuity) [ 26 ].

Evidence suggests that improving COC leads to improved patient-reported outcome measures (e.g., patient satisfaction [ 26 ] and quality of life [ 27 ]), reduced mortality [ 28 , 29 ], fewer emergency hospital admissions [ 30 ], fewer hospitalizations [ 31 , 32 ], and decreased healthcare costs [ 33 ]. Furthermore, a recent systematic review investigating relational COC in community pharmacies and its effect on patient outcomes found positive effects of higher COC on medication adherence, inappropriate drug use, and the use of other costly services (e.g., visits to the emergency department) [ 34 ]. However, there is limited evidence regarding the association of COC with polypharmacy and MARO [ 24 , 26 ]. Therefore, this study aims (i) to give an overview of how observational studies examining the relationship between COC and polypharmacy on the one hand and COC and MARO on the other operationalize these concepts and (ii) to perform a narrative synthesis of the results of these studies. The former is necessary since COC [ 25 , 35 , 36 , 37 , 38 , 39 ], polypharmacy [ 7 ], and MARO [ 40 ] are defined and measured in various ways, hampering the comparability of results.

This systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) statement [ 41 ] (Electronic Supplementary Material [ESM] Tables S4 and S5).

2.1 Search Strategy

We performed a systematic literature search from inception to 06 February 2023 using the databases MEDLINE via PubMed, Embase, and CINAHL via EBSCOhost Web. The search strategy included terms related to COC, polypharmacy, MARO, and relevant MeSH terms. For Embase and CINAHL, the same search terms were used (see supplement 1 in the ESM). Additionally, reference lists of relevant studies were searched manually for further relevant publications. Databases were chosen due to their relevance and the search strategy was developed in accordance with published COC- and MARO-related systematic reviews [ 16 , 19 , 27 , 34 ].

2.2 Study Selection

Studies were included if they investigated the relationship between COC and polypharmacy and/or MARO. We included only studies focusing on the continuity of physician care, rather than COC with respect to nurses, pharmacies, or other care providers. Any operationalization of COC, polypharmacy, and MARO was eligible. Only quantitative observational studies (including those using written questionnaires and quantitative interviews) applying multivariate regression analysis techniques were included to ensure that included studies properly controlled for confounding factors. Any experimental and qualitative studies (or reviews of such), editorials, commentaries, conference abstracts, or study protocols were excluded. Experimental studies were excluded as clarifying the operationalization of COC, polypharmacy, and MARO and their relationship in observational studies is a necessary step before interventions targeting COC to improve polypharmacy and MARO can be properly evaluated. The selection was limited to articles published in English and German (see supplement 2 in the ESM). Two investigators (DL and JG) independently screened search results and assessed the eligibility of potentially relevant studies. Discrepancies were resolved by consensus. Another investigator (DG/JW) was involved if consensus could not be reached.

2.3 Data Extraction, Categorization, and Analysis

The following data were extracted from the included studies: information related to study design/analysis, data source (register, claims, administrative and pharmacy data summarized as ‘register/claims data’), country, setting (of exposure), and population. Regarding analyses and outcomes, information on how COC was operationalized was extracted and categorized according to the three dimensions ( relational continuity, informational continuity, and management continuity ) proposed by Haggerty et al. [ 25 ]. Additionally, studies were categorized by their type of COC measure into objective standard measures, objective non-standard measures, and subjective measures according to van Walraven et al. [ 26 ]. Key findings of the studies and reported effect sizes, that is, odds ratios (OR), risk ratios (RR), incidence rate ratios (IRR) resulting from regression models, were also extracted (Table 1 ). Finally, information related to the operationalization of polypharmacy and MARO was extracted (Table 2 ; Tables S1 and S2 in the ESM). One investigator (DL) performed the data extraction, which was verified by a second investigator (JG). Disagreements were resolved by consensus after discussion.

The results of the included studies were synthesized narratively, since the variety of COC, polypharmacy, and MARO measures as well as differences in reported outcomes and study designs did not allow a quantitative synthesis. For those studies reporting OR, RR, and IRR, we visualized point estimates of the effect sizes as well as reported confidence intervals with forest plots. These plots were grouped by type of COC measure and type of outcome.

2.4 Quality Appraisal

Risk of bias was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, which comprises 14 criteria and rating guidance [ 42 ]. This tool classifies the risk of bias of studies as good (low risk of bias), fair (intermediate risk of bias), or poor (high risk of bias). Two reviewers made independent judgments on each of the items (DL, JG). Disagreements between the two reviewers were resolved by consensus after discussion.

3.1 Study Selection

The literature search identified 1984 articles, resulting in 1758 articles after duplicates were removed. After screening titles and abstracts according to the eligibility criteria, we selected 175 articles for full-text review. Full-text articles ( n  = 160) were excluded with the following reasons: (i) no quantitative association of COC and either polypharmacy or MARO investigated ( n  = 117), (ii) experimental design or review of interventional studies ( n  = 39), (iii) conference abstract (no full-text available) ( n  = 3), (iv) language other than English or German ( n  = 1). Finally, 27 studies that met the inclusion criteria were included in the narrative synthesis, including 12 studies that were found by searching the reference lists manually (Fig. 1 ).

PRISMA 2020 flow diagram . Reason 1: No quantitative association of COC and either polypharmacy or MARO investigated, reason 2: experimental design or review of interventional studies, reason 3: conference abstract (no full-text available), reason 4: language other than English or German. COC continuity of care, MARO medication appropriateness-related outcomes

3.2 Study Characteristics and Methodological Findings

Table 1 summarizes the included studies’ main study characteristics and results. The majority of studies ( n  = 16) investigated the relationship between COC and MARO [ 43 , 44 , 45 , 46 , 47 , 51 , 56 , 57 , 58 , 60 , 61 , 63 , 64 , 66 , 68 , 69 ]. Seven studies focused on the relationship between COC and polypharmacy [ 48 , 53 , 54 , 62 , 65 , 67 ], and four studies investigated both the relationship between COC and MARO and between COC and polypharmacy [ 49 , 50 , 52 , 59 ].

The included studies were from North America ( n  = 12), Europe ( n  = 6), and Asia ( n  = 9). Most of the studies ( n  = 9) were from the US [ 46 , 48 , 51 , 57 , 60 , 63 , 66 , 67 , 69 ] and Taiwan ( n  = 6) [ 43 , 44 , 45 , 47 , 50 , 62 ]. The population of interest was mostly at least 60 years old. Only five studies included younger patients [ 45 , 48 , 51 , 57 , 58 ]. Nine studies focused on patients with specific diseases or risks, such as patients with a mental and/or behavioral disorder or dementia [ 47 , 48 , 51 , 52 , 53 , 54 , 62 , 67 , 68 ]. All studies included outpatient data, while only two studies [ 51 , 69 ] included inpatient data. Sample sizes varied substantially between 384 [ 60 ] and 2,318,766 participants [ 50 ]. Cross-sectional analyses were performed in 20 [ 46 , 48 , 49 , 52 , 53 , 54 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 ] and longitudinal analyses in eight studies [ 43 , 44 , 45 , 47 , 50 , 51 , 55 , 69 ]. One study performed both cross-sectional and longitudinal analyses [ 69 ]. Most studies ( n  = 19) performed their analyses based on register/claims data [ 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 59 , 61 , 64 , 68 ]. Five studies used questionnaires/interviews [ 63 , 65 , 66 , 67 , 69 ]. One study based its analyses on medical records [ 60 ]. A combination of multiple data sources was used by two studies [ 58 , 62 ]. The main setting (of exposure) was primary care/outpatient. Only two studies included providers from the primary care/outpatient and secondary care/inpatient setting [ 51 , 69 ]. The following subsections describe methodological characteristics of the included studies, including the measures used to capture COC, polypharmacy, and MARO. Table 2 gives an overview of the frequency of these measures overall and for studies investigating polypharmacy and MARO, respectively.

3.2.1 Operationalization of Continuity of Care (COC)

The most frequent COC dimension investigated was relational continuity , which was considered in every study. Only three studies [ 48 , 57 , 66 ] additionally considered informational continuity and management continuity (Table 1 ). Regarding the operationalization of COC, substantial differences were observed.

Objective standard COC measures were used by 11 studies. Among those, different COC indices were used to measure relational continuity , such as the Continuity of Care Index (COCI), the Usual Provider of Care (UPC) index, and the Sequential Continuity of Care Index (SECON). The COCI was analyzed in six studies [ 43 , 44 , 45 , 47 , 50 , 52 ]. The studies differed in terms of their aggregation level. For example, two studies analyzed COCI at the site level in addition to the physician level [ 43 , 45 ]. Moreover, the variables’ scale of measurement was variously defined as continuous [ 45 , 47 ], ordinal [ 44 , 45 , 50 , 52 ], or binary (e.g., low vs high COCI) [ 43 , 50 ]. The UPC index was also calculated in six studies [ 43 , 44 , 52 , 53 , 54 , 64 ]. Two of these studies used the UPC index to conduct supplementary sensitivity analyses beyond their primary COCI-based analyses [ 43 , 44 ]. Differences in the aggregational level (physician level vs site level) and the variables’ scale of measurement also existed among those studies. Two studies [ 48 , 57 ] operationalized COC via care density, a proxy measure that may reflect how frequently a patient’s doctors collaborate/share patients. Thus, care density corresponds to better communication and information sharing between the patient’s care team, forming a social network of providers [ 70 ]. This was the only COC measure identified that represents informational and management COC. The SECON was only used by one study that also calculated the COCI and the UPC index [ 52 ]. Multiple objective standard measures of COC were used by three studies [ 43 , 44 , 52 ] (Table 2 ; Tables S1 and S2 in the ESM).

Among studies using objective non-standard measures of COC ( n  = 16), the majority ( n  = 11) used the number of prescribers [ 46 , 48 , 51 , 55 , 56 , 59 , 60 , 61 , 63 , 68 , 69 ] to measure COC, with a high number of prescribers indicating low COC. Further measures were the number of treating physicians [ 49 , 61 ], the number of providers [ 57 , 67 ], the number of specialties [ 58 ], the tendency to visit multiple providers [ 62 ], and having a single primary care physician [ 61 ]. Exposure variables were treated as binary, ordinal, or continuous (Table 2 ; Tables S1 and S2 in the ESM).

Subjective measures of COC were used by three studies [ 65 , 66 , 69 ] (Table 2 ). In particular, patients were asked if they have a regular physician [ 65 ], whether they usually see the same physician [ 69 ], or whether they experienced a gap in care coordination [ 66 ]. These COC measures were treated as binary variables (yes vs no) (Tables S1 and S2, see ESM). Overall, a combination of the different types of COC measures was used by three studies [ 48 , 57 , 69 ].

3.2.2 Operationalization of Polypharmacy

Polypharmacy was mostly defined as having five or more medications prescribed (binary variable) [ 49 , 50 , 52 , 55 , 59 , 62 , 65 , 67 ]. Some studies (additionally) included extreme/excessive polypharmacy (≥10 medications prescribed) [ 50 , 52 , 53 , 54 , 55 , 62 ]. One study operationalized multiclass psychotropic polypharmacy as taking two or more psychotropic medications from different drug classes for 60 days or more [ 48 ]. Observational periods varied from 2 weeks to 1 year; two studies also considered persistent (>181 days) polypharmacy [ 50 , 62 ] (Table 2 ; Table S1, see ESM).

3.2.3 Operationalization of Medication Appropriateness-Related Outcomes (MARO)

Overall, seven categories of MARO were investigated: Potentially inappropriate medication (PIM) [ 44 , 46 , 47 , 49 , 52 , 56 , 59 , 64 , 69 ], drug–drug interaction (DDI) [ 45 , 50 , 57 , 64 , 66 , 68 ], adverse drug events (ADE) [ 58 , 63 ], duplicated medication [ 43 , 44 ], unnecessary drug use [ 60 ], overdose [ 51 ], and potential inappropriate drug combination (PIDC) [ 61 ] (Table 2 ).

Regarding the operationalization of PIM, different versions of the Beers criteria [ 71 ] were applied [ 46 , 47 , 64 ]. Other instruments were used, such as the Japanese STOPP-J list [ 59 ], the Norwegian General Practice (NORGEP) criteria, which are based on the Beers criteria [ 56 ], the German PRISCUS list [ 49 ], and the STOPP/START criteria [ 52 ]. PIM was always analyzed by using a binary (yes vs no) variable. Concerning DDI, the outcome variable was dichotomized (yes vs no) in all but one included study, which treated DDI as a continuous variable [ 45 ]. PIDC, as used by Tamblyn et al. [ 61 ], is a combination of PIM and DDI, identified by an expert review. Duplicated medications were used as outcomes by Cheng and Chen [ 43 ] and Chu et al. [ 44 ]. ADE were defined as either the presence of an ADE-specific code [ 58 ] or as a binary (yes vs no) outcome self-reported by the study participants [ 63 ]. One study [ 60 ] measured unnecessary drug use based on the Medication Appropriateness Index [ 72 ]. Finally, overdose as an outcome was defined as the occurrence of one or more medical claims containing a diagnosis code for opioid or benzodiazepine poisoning on a person-day of opioid-benzodiazepine overlap [ 51 ] (Table S2, see ESM).

3.3 Association Between COC and Polypharmacy

Studies using objective standard measures of COC [ 48 , 50 , 52 , 53 , 54 ] found mixed effects concerning the association between COC and polypharmacy (Table 1 ). For example, higher COC (highest quartile, ref.: lowest quartile) was not associated with polypharmacy but with a reduced risk of extreme polypharmacy [ 52 ]. Two studies by Guilcher et al. [ 53 , 54 ] also showed a significant negative association between COC and polypharmacy. Furthermore, COC (care density) was associated with the likelihood of receiving psychotropic polypharmacy. However, this relationship between COC (care density) and psychotropic polypharmacy varied depending on the type of physicians involved in the care team, and a significant negative relationship between COC (care density) and psychotropic polypharmacy was only observed among patients with only PCPs involved in their care teams, while a significant positive relationship was observed among patients who had both PCPs and specialists involved in their care team [ 48 ]. Weng et al. [ 50 ] showed that the proportion of patients with polypharmacy was significantly lower in a high COC group (87.80%) compared with a low COC group (94.29%) and that higher COC was related to fewer DDI events. This latter effect was partially mediated by polypharmacy. Fig. 2 shows the associations between COC and polypharmacy in studies using objective standard COC measures.

Association between COC and polypharmacy for objective standard COC measures. Solid green line indicates significant negative association between COC and polypharmacy; dashed red line indicates non-significant negative association; blue dotted line indicates significant positive association; [ 50 ] was not visualized, as results were not reported as OR, RR, or IRR; [ 54 ] uses low COC as the reference category. Therefore, an RR of 1.07 indicates a negative relationship between high COC and polypharmacy. *OR for care teams of PCPs only; **OR for care teams of specialists only; ***OR for care teams with both PCPs and specialists. COC continuity of care, COCI Continuity of Care Index (physician level), IRR incidence rate ratio, MARO medication appropriateness-related outcomes, OR odds ratio, PCP primary care physician/practitioner, RR risk ratio, SECON sequential continuity of care, UPC usual provider of care

All studies using objective non-standard COC measures (e.g., number of prescribers/providers/treating physicians) [ 48 , 49 , 55 , 59 , 62 , 67 ] demonstrated associations between COC and (different levels of) polypharmacy. Regarding polypharmacy (≥ 5 medications) [ 49 , 55 , 59 , 62 , 67 ], studies consistently showed a significant association with COC. For instance, one study demonstrated that higher COC (lower number of treating physicians) is a predictor of polypharmacy (independent of multimorbidity) in men and women above the age of 60 years [ 49 ]. Regarding subjective COC measures, one study showed that patients reporting low COC (not having a regular physician) are more than twice as likely to be taking five or more prescribed drugs than those patients with high COC (having a regular physician) [ 65 ]. Figure 3 shows the associations between COC and polypharmacy in studies using objective non-standard or subjective COC measures.

Association between COC and polypharmacy for objective non-standard and subjective COC measures. For [ 49 ], only the OR for 2 vs 1 physician among women was visualized. The association between the number of treating physicians and polypharmacy was significantly positive in all other subgroups. Solid green line indicates significant negative association between COC and polypharmacy. COC continuity of care, OR odds ratio

3.4 Association Between COC and MARO

Studies using objective standard measures of COC [ 43 , 44 , 45 , 47 , 50 , 57 , 64 ] to investigate the association of COC with PIM [ 44 , 47 , 52 , 64 ], DDI [ 45 , 50 , 57 , 64 ], and medication duplication [ 43 , 44 ] demonstrated negative relationships (Table 1 ). In terms of PIM, however, one study [ 52 ] showed mixed results (significant or non-significant negative associations) depending on the type of analysis. Figure 4 shows the associations between COC and MARO in studies using objective standard COC measures.

Association between COC and MARO for objective standard COC measures. Solid green line indicates significant negative association between COC and MARO; dashed red line indicates non-significant negative association. [ 43 ] was not visualized, as results were not reported as OR, RR, or IRR. COC continuity of care, COCI Continuity of Care Index (physician level), DDI drug–drug interaction, HF heart failure, IRR incidence rate ratio, MARO medication appropriateness-related outcomes, OR odds ratio, PIM potentially inappropriate medication, RR risk ratio, SECON sequential continuity of care, UPC usual provider of care

Objective non-standard COC measures were used by 12 studies [ 46 , 49 , 51 , 56 , 57 , 58 , 59 , 60 , 61 , 63 , 68 , 69 ]. Regarding PIM, most studies revealed negative associations with COC [ 46 , 49 , 56 , 59 ]. However, one study showed that having low COC (high number of prescribers) was not significantly associated with PIM [ 69 ]. DDI [ 57 , 68 ], ADE [ 58 , 63 ], unnecessary drug use [ 60 ], overdose [ 51 ], and PIDC [ 61 ] were found to be negatively associated with COC. Thus, the more prescribers/providers involved in the care process (representing lower COC), the higher the likelihood of inappropriate prescribing. Subjective COC measures were used by two studies [ 66 , 69 ]. These studies also identified negative associations of COC (gap in care coordination) and DDI [ 66 ] and COC (usually seeing the same physician) and PIM [ 69 ]. Figure 5 shows the associations between COC and MARO in studies using objective non-standard or subjective COC measures.

Association between COC and MARO for objective non-standard and subjective COC measures. Solid green line significant negative association between COC and MARO; red dashed line non-significant negative association. For [ 46 ], the OR for having 2 vs 1 prescriber was visualized (a significant negative association between COC and PIM was also found for 3 and 4+ vs 1 prescriber). For [ 49 ], only the OR for 2 vs 1 physician among women was visualized. The association between the number of treating physicians and polypharmacy was significantly positive in all other subgroups. For [ 56 ], the OR for 3–4 vs 1–2 prescribers was visualized (a significant negative association between COC and PIM was also found for 5 + vs 1–2 prescribers). For [ 69 ], only the longitudinal model was visualized. ADE adverse drug event, COC continuity of care, COCI Continuity of Care Index, DDI drug–drug interaction, MARO medication appropriateness-related outcomes, OR odds ratio, PIDC potential inappropriate drug combination, PIM potentially inappropriate medication

3.5 Risk of Bias Assessment

Overall, 15 studies [ 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ] had a low risk of bias, five studies [ 58 , 59 , 60 , 61 , 62 ] had an intermediate risk of bias, and seven studies [ 63 , 64 , 65 , 66 , 67 , 68 , 69 ] were deemed to have a high risk of bias (Table S3, see ESM). Among studies at high risk of bias, common problems were that the exposure measures (criteria 9) and outcome measures (criteria 11) were not clearly defined, valid, reliable, and implemented consistently across all study participants, that the exposure was not measured before the outcome(s) (criteria 6), or that the exposure was not assessed more than once over time (criteria 10). Loss to follow-up (criteria 13) was deemed not applicable (N/A) to the included studies, as all studies were retrospective.

4 Discussion

This systematic review had two aims. First, we aimed to explore how COC, polypharmacy and MARO are defined, operationalized, and measured in the included studies. Second, we aimed to investigate the relationship between COC and polypharmacy and MARO.

4.1 Methodological Findings: Measuring COC

COC is a multi-faceted concept with various measures available to researchers [ 38 , 73 ]. However, different COC measures reflect the dimensions of relational, informational, and management continuity to various degrees. We found that the majority of included studies used objective non-standard measures, mainly the number of prescribers, while a significant minority used objective standard measures, with only three studies using subjective measures.

Objective non-standard measures are typically simple to compute but are only partially adequate for measuring COC. First, these measures quantify the amount of patient-provider interaction (e.g., the number of particular patient-doctor encounters [ 26 ]) without considering the distribution of these interactions. However, this distribution is important to relational continuity. Second, objective non-standard measures do not adequately capture informational or management continuity. For instance, it is not plausible to consider a patient with a moderate number of prescribers who do not effectively communicate and share information about the patient to have a higher COC than a patient with a somewhat larger but well-connected group of prescribers who adhere to joint treatment plans.

Similarly, objective standard measures were also mainly used to measure relational continuity. However, these measures may be better suited to measuring all COC dimensions than objective non-standard measures. First, they can capture aspects of relational continuity beyond the mere number of providers or prescribers, such as the distribution of visits to different providers. Second, while they were not commonly used, objective standard measures that are capable of measuring informational and management COC do exist (e.g., care density). When measuring relational continuity, included studies used a variety of COC indices and different cut-off values for high and low COC even when the same index was used. In fact, for the COCI, there is no agreed-upon cut-off value for high and low continuity [ 74 ]. This makes it more difficult to compare results between studies.

Few studies used subjective COC measures [ 53 , 55 , 68 ]. While these patient-reported measures are more susceptible to bias than objective COC measures, subjective measures are a valuable supplement to objective measures relying on claims data. Overall, our findings on utilized measures of COC are consistent with other studies showing that objective COC measures referring to relational continuity are most commonly used [ 24 , 26 , 33 ].

The results indicate that there is no agreed-upon approach for measuring COC as a multi-faceted concept in the context of polypharmacy and medication appropriateness. Future research in this area should aim to measure all three dimensions of COC and use multiple COC measures to make comparing measures and their results easier. This means researchers should ensure that the measures used cover all COC dimensions. For example, studies may use a relational COC measure in concert with an informational and management COC measure such as care density or an appropriate subjective measure. However, it remains unclear to what extent these measures appropriately capture informational and management continuity. For instance, care density is only a surrogate measure for care communication and collaboration, based on the premise that certain aspects of coordination may be reflected and/or facilitated by patients seeing physicians whose patient panels significantly overlap [ 75 ]. It should also be taken into account that a high number of patients shared between physicians does not indicate that these physicians necessarily exchange (sufficient) information about their patients [ 75 ]. Therefore, care density is only able to examine conditions that are more or less favorable toward management and informational continuity (care coordination) [ 75 ]. This highlights the need for developing, validating, and using new COC measures referring to the management and information dimension of COC. In addition, researchers should use a combination of different types of COC measures, even within COC dimensions. This means using and comparing multiple COC indices, including those with different methodological approaches (e.g., dispersion, density, or sequence of doctor visits [ 33 , 38 ]) when utilizing objective standard measures. This was only done in three studies [ 43 , 44 , 52 ]. Furthermore, many objective standard measures of relational continuity are calculated from values commonly used as objective non-standard measures. In such cases, researchers should report and compare the values and associations with polypharmacy/MARO for both the objective standard and objective non-standard measures. This was only done in two studies [ 48 , 57 ]. Finally, sensitivity analyses may be appropriate when using COC indices to acknowledge methodological differences in operationalization.

Similar conclusions can be drawn from an analysis of the data types used by the included studies. A large majority of studies used claims data or similar data types to measure continuity, allowing researchers to reach very large sample sizes and compute objective standard and objective non-standard measures. However, COC indices based on claims data cannot fully capture the multiple dimensions of COC [ 33 , 76 ]. A small number of studies used survey data to measure continuity. While survey data alone is also inadequate to capture all three dimensions of continuity [ 77 ], future studies should use appropriate survey-based measures to complement claims-based measures to capture COC in all its facets [ 76 ]. This is particularly important when investigating the association between COC and polypharmacy or MARO, as research has shown discrepancies between COC measured through survey data and claims data [ 78 ].

4.2 Methodological Findings: Measuring Polypharmacy and MARO

Substantial differences existed concerning how polypharmacy and MARO were operationalized and analyzed. While most of the studies defined polypharmacy using a numerical threshold of more than five drugs, which is commonly used in the literature [ 7 ], studies differed concerning the timeframe in which the numerical threshold could be reached. For instance, some studies analyzed the number of drugs within a 1-year period, while others focused on the day of maximum prescriptions. This finding aligns with current research showing that polypharmacy continues to lack a universally accepted definition [ 7 , 79 ]. However, operationalizations based solely on numerical data do not adequately capture the complexity of the problem and make it difficult to assess the safety and appropriateness of drug therapy in clinical practice. For instance, using multiple medications is not necessarily harmful and associated with adverse health effects but may even be entirely reasonable and appropriate for some (multimorbid) patients. Thus, the use of strict numerical cut-offs to measure and operationalize polypharmacy has been criticized. Accordingly, some authors propose distinguishing between appropriate and inappropriate polypharmacy and placing more emphasis on qualifying the term polypharmacy rather than quantifying it [ 80 , 81 ]. However, there is little evidence on how to distinguish between appropriate and inappropriate polypharmacy [ 82 ]. In the absence of a uniform definition, studies should continue to use the five-drug threshold to ensure comparability across studies. However, researchers should perform sensitivity analyses with higher or lower thresholds to test the robustness of their results. Finally, future research should work toward developing a useable definition of ‘inappropriate polypharmacy’, moving away from strictly quantitative definitions. Regarding the operationalization of MARO, future research should aim to use agreed-upon definitions and operationalizations (particularly concerning DDI) to ensure the comparability of results.

4.3 Methodological Findings: Risk of Bias

Most studies had a low risk of bias ( n  = 15/24). These studies examined exposure and outcome based on register/claims data. Studies using questionnaire/interview-based data had a higher risk of bias, indicating that large claims databases can be useful for analyzing COC. However, this is due to the subjective measures used in the included questionnaire/interview-based studies and does not show that subjective measures are generally inappropriate for measuring COC. Instead, these results again highlight the importance of developing suitable and agreed-upon subjective measures for COC, especially the informational and management dimensions.

Additionally, several studies had a higher risk of bias because they failed to address time-dependent bias, a common methodological flaw in COC research [ 26 , 83 ]. Appropriate accounting for the relative timing of COC and outcomes was ensured by only 11 studies [ 43 , 44 , 45 , 47 , 50 , 51 , 52 , 55 , 60 , 65 , 69 ]. In terms of the study design, longitudinal studies had rather good quality compared with cross-sectional studies. However, well conducted, cross-sectional studies did exist [ 46 , 48 , 49 , 52 , 53 , 54 , 56 , 57 ]. Overall, differences regarding the methodological quality of included studies need to be considered when interpreting the results. Future studies should ensure that COC is measured before outcomes, or at least address the issue of relative timing with appropriate methods; aim to have a longitudinal design to investigate the long-term effects of COC on outcomes; and use register/claims data to reduce potential recall bias and to expand the study period at comparatively low cost.

4.4 Empirical Findings

Yet, despite the conceptual variety and differences in quality between studies, our findings suggest a strong association between COC and polypharmacy and between COC and MARO. These results yield that (i) lower COC increases the chance of polypharmacy and (ii) lower COC increases the chance of MARO such as PIM, PIDC, DDI, ADE, unnecessary drug use, medication duplication, and overdose. As shown by Weng et al. [ 50 ], the relationship between COC and inappropriate prescribing (DDI) is mediated by polypharmacy, indicating that polypharmacy itself is an important risk factor for several drug-related adverse events [ 84 ].

Our results contribute to the findings of Choi and Lee [ 34 ], who investigated the relationship of relational COC between patients and community pharmacy (CP) pharmacists. They showed that a high degree of relational COC between patients and CP pharmacists was associated with improved medication adherence. Patients who had visited a single pharmacy were more adherent to their medication regimen compared with those visiting multiple pharmacies. Moreover, a high level of relational continuity could lower inappropriate drug use and emergency department visits caused by adverse drug reactions [ 34 ]. Other studies also showed the importance of doctor–patient COC for safer medication management, demonstrating that higher COC was associated with higher medication adherence and compliance [ 85 , 86 , 87 ].

4.5 Implications for Research and Practice

Our findings have significant implications for health care research and practice. Concerning the operationalization and measurement of COC, our methodological findings highlight that researchers should (i) ensure that all three dimensions of COC (relational, informational, and management continuity) are covered by the COC measures used, (ii) use and compare different COC measures of the same type, (iii) use a combination of subjective and objective COC measures, and (iv) draw from a combination of claims data and patient-reported survey data when doing so. These steps will help researchers better understand and use the various tools available for measuring COC. In particular, future research should aim to identify or develop an appropriate and agreed-upon operationalization of COC, polypharmacy, and MARO to ensure the comparability of results. Researchers investigating the link between COC and outcomes such as polypharmacy or MARO should use longitudinal study designs where possible and give particular regard to the relative timing of exposures and outcomes.

Following these recommendations may also allow future research to improve health care practice regarding COC. Our findings indicate that low COC is a significant risk factor for polypharmacy and MARO, highlighting the need for appropriate interventions to improve COC. However, designing and targeting these interventions will require a more detailed understanding of the underlying causal links between the three dimensions of continuity and outcomes, such as polypharmacy or MARO. Overall, health care providers and researchers involved in intervention planning should acknowledge low COC as an important risk factor for polypharmacy/MARO and consider all three dimensions of COC when designing interventions. This contributes to the findings of Facchinetti et al. on the importance of developing interventions that address all continuity dimensions simultaneously [ 88 ].

4.6 Limitations

While several COC-related systematic reviews have been published, including various health-related outcomes [ 26 , 28 , 29 , 32 , 89 , 90 ], this review is the first to explore doctor–patient COC in polypharmacy and medication management. Nevertheless, some limitations of this review need to be considered. First, there was substantial heterogeneity between studies regarding the measurement and operationalization of exposure and outcomes variables. This allowed us to analyze the methodological approaches to measuring COC, polypharmacy, and MARO used by included studies, but complicated the comparison of empirical findings between different studies. Second, some studies had strong methodological flaws, such as the relative timing of the measurement of exposure and outcomes. Third, in terms of the generalizability of the results, population and health system-related differences need to be considered. However, despite different populations and health care systems studied, the empirical findings of the included studies were quite consistent. Fourth, the literature search was restricted to articles published in English and German. As a significant minority of included studies were from non-English and non-German speaking countries, it is likely that there are further relevant studies that we did not include. Fifth, we included only quantitative studies. Therefore, qualitative approaches to exploring the relationship between COC and polypharmacy/MARO could not be considered. Sixth, due to different operationalizations of MARO, the search strategy may not have been sufficient to identify all relevant studies on this topic. Seventh, another limitation is that this review and its methods were not registered in a review study registry (e.g., PROSPERO) before it was conducted. However, the methodological aspects were pre-specified in the work process and described transparently in this article. Finally, a meta-analysis of effect sizes across studies could not be conducted, given the heterogeneity of study characteristics.

5 Conclusion

This systematic review summarized evidence supporting the negative associations between COC and polypharmacy and between COC and MARO. Despite differences in the operationalization of COC, polypharmacy, and MARO, our findings suggest that improving COC is a promising approach to managing polypharmacy and preventing inappropriate prescribing. However, further research is necessary to develop agreed-upon definitions and operationalizations of the concepts involved, including operationalization of COC that covers all continuity dimensions and an appropriate definition of inappropriate polypharmacy. This will allow researchers and practitioners to design interventions targeting the specific causal links between different continuity dimensions and outcomes, such as inappropriate polypharmacy or MARO.

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Lampe, D., Grosser, J., Gensorowsky, D. et al. The Relationship of Continuity of Care, Polypharmacy and Medication Appropriateness: A Systematic Review of Observational Studies. Drugs Aging 40 , 473–497 (2023). https://doi.org/10.1007/s40266-023-01022-8

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Interventions to reduce the prescription of inappropriate medicines in older patients

Identify and critically evaluate systematic reviews addressing the effectiveness of interventions to reduce the number of prescriptions of potentially inappropriate medication to older patients.

This is an overview of systematic reviews. The studies were searched and selected from Medline, Cochrane Library, Embase, CINAHL, Virtual Health Library, and Web of Science databases, combining the terms aged, prescriptions, inappropriate prescribing and potentially inappropriate medication list with their entry terms and other related descriptors, published by June 2017. This study included systematic reviews with or without meta-analysis that addressed the effectiveness of any intervention or combined interventions to reduce the number of prescriptions of potentially inappropriate medications to older patients, without restriction in terms of design, language or date of publication of primary studies. AMSTAR – A MeaSurement Tool to Assess systematic Reviews – was used to evaluate the methodological quality of selected systematic reviews. Study selection and the methodological quality evaluation were performed by two independent evaluators, who resolved any divergence by consensus. The main findings were grouped into thematic categories, defined after a content analysis and discussed qualitatively as narrative synthesis.

This study analyzed 24 systematic reviews. In terms of study design and methodological quality evaluation, most were systematic reviews of randomized controlled clinical trials and studies of moderate quality, respectively. The interventions were analyzed in five thematic categories: medication review services, pharmaceutical interventions, computerized systems, educational interventions, and others. The interventions analyzed showed good results and most of them helped reduce the number of prescriptions of potentially inappropriate medication to older patients.

CONCLUSIONS:

The systematic reviews included in this overview showed potential benefits of different interventions. However, it was not possible to determine the most effective intervention. Combined interventions are likely to provide better results than isolated interventions.

DESCRIPTORS: Aged. Health of the Elderly; Patient Medication Knowledge; Inappropriate Prescribing; prevention & control; Review

Identificar e avaliar criticamente revisões sistemáticas sobre a efetividade de intervenções para reduzir a prescrição de medicamentos potencialmente inapropriados para pacientes idosos.

Overview de revisões sistemáticas. A busca e a seleção dos estudos foram feitas nas bases de dados Medline , Biblioteca Cochrane, Embase, CINAHL , Biblioteca Virtual em Saúde e Web of Science , combinando os termos aged, prescriptions, inappropriate prescribing e potentially inappropriate medication list com seus sinônimos remissivos e outros descritores associados até junho de 2017. Foram incluídas revisões sistemáticas com ou sem metanálise, que tenham abordado a efetividade de qualquer intervenção ou a combinação de intervenções para reduzir a prescrição de medicamentos potencialmente inapropriados para pacientes idosos, sem restrição quanto ao desenho dos estudos primários, idioma ou data de publicação. Para avaliação da qualidade metodológica das revisões sistemáticas selecionadas, foi utilizado o instrumento A MeaSurement Tool to Assess systematic Reviews . A seleção e a avaliação da qualidade metodológica foram realizadas por dois avaliadores independentes. As divergências foram superadas por consenso. Os principais achados foram agrupados em categorias temáticas, definidas com base em análise de conteúdo e discutidas qualitativamente na forma de síntese narrativa.

RESULTADOS:

Vinte e quatro revisões sistemáticas foram incluídas no estudo. Quanto ao desenho do estudo e à avaliação da qualidade metodológica, prevaleceram revisões sistemáticas de ensaios clínicos controlados randomizados e estudos de qualidade moderada, respectivamente. As intervenções foram analisadas em cinco categorias temáticas: serviços de revisão de medicamentos, intervenções farmacêuticas, sistemas informatizados, intervenções educacionais e outras. As intervenções estudadas apresentaram bons resultados e a maioria contribuiu para reduzir a prescrição de medicamentos inapropriados para pacientes idosos.

CONCLUSÕES:

As revisões sistemáticas incluídas nesse overview apontaram benefícios potenciais de diferentes intervenções. No entanto, não foi possível determinar qual a mais efetiva. É provável que intervenções multifacetadas alcancem resultados melhores do que intervenções isoladas.

DESCRITORES: Idoso; Saúde do Idoso; Conhecimento do Paciente sobre a Medicação; Prescrição Inadequada, prevenção & controle; Revisão

INTRODUCTION

Among current global challenges, one trend is that world population ages rapidly, and this demographic transition will affect almost every aspect of society 1 1. Beard JR, Carvalho IA, Sumi Y, Officer A, Thiyagarajan JA. Healthy ageing: moving forward. Bull World Health Organ. 2017;95(11):730-730a. https://doi.org/10.2471/blt.17.203745 https://doi.org/10.2471/blt.17.203745... . According to estimates, the number of people aged 60 and over will increase from 962 million in 2017 to 2.1 billion in 2050 and 3.1 billion in 2100 a a United Nations Department of Economic and Social Affairs. World population prospects: the 2017 revision. New York; 2017[cited 2017 Dec 21]. Available from: https://www.un.org/development/desa/publications/world-population-prospects-the-2017-revision.htm .

This population growth poses significant challenges for health systems, increasing the demand for health resources, including medication 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... . The greater the number of items used by a patient, the greater the chances of such patient being submitted to therapy with potentially inappropriate medication 3 3. Santos APAL, Silva DT, Alves-Conceição V, Antoniolli AR, Lyra Jr DP. Conceptualizing and measuring potentially inappropriate drug therapy. J Clin Pharm Ther. 2015;40(2):167-76. https://doi.org/10.1111/jcpt.12246 https://doi.org/10.1111/jcpt.12246... .

Prescription of potentially inappropriate medication occurs when the risk of adverse events outweighs the clinical benefit. It also refers to overuse, prescription of multiple drugs with known interactions, incorrect indication or dose, and drug taken longer than necessary 4 4. Fond G, Fajula C, Dassa D, Brunel L, Lancon C, Boyer L. Potentially inappropriate psychotropic prescription at discharge is associated with lower functioning in the elderly psychiatric inpatients: a cross-sectional study. Psychopharmacology (Berl). 2016;233(13):2549-58. https://doi.org/10.1007/s00213-016-4312-z https://doi.org/10.1007/s00213-016-4312-... , 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... .

Adverse events and drug interactions cause significant morbidity and mortality, especially in older patients as they present alterations in body composition and renal and hepatic functions 6 6. Clyne B, Bradley MC, Hughes CM, Clear D, McDonnell R, Williams D, et al. Addressing potentially inappropriate prescribing in older patients: development and pilot study of an intervention in primary care (the OPTI-SCRIPT study). BMC Health Serv Res. 2013;13:307. https://doi.org/10.1186/1472-6963-13-307 https://doi.org/10.1186/1472-6963-13-307... 7. Gutierrez Valencia M, Martinez Velilla N, Lacalle Fabo E, Beobide Telleria I, Larrayoz Sola B, Tosato M. Intervenciones para optimizar el tratamiento farmacológico en ancianos hospitalizados: una revisión sistemática. Rev Clin Esp. 2016;216(4):205-21. https://doi.org/10.1016/j.rce.2016.01.005 https://doi.org/10.1016/j.rce.2016.01.00... - 8 8. Tommelein E, Petrovic M, Somers A, Mehuys E, Cammen T, Boussery K. Older patients’ prescriptions screening in the community pharmacy: development of the Ghent Older People's Prescriptions community Pharmacy Screening (GheOP3S) tool. J Public Health (Oxf). 2016;38(2):e158-70. https://doi.org/10.1093/pubmed/fdv090 https://doi.org/10.1093/pubmed/fdv090... .

Prescription of potentially inappropriate medication to older patients has received special attention from health professionals, care providers, researchers, and health policymakers worldwide 9 9. Soares MA, Fernandez-Llimos F, Cabrita J, Morais J. Critérios de avaliação de prescrição de medicamentos potencialmente inapropriados: uma revisão sistemática. Acta Med Port. 2011 [cited 2018 Feb 26];24(5):775-84. Available from: https://www.actamedicaportuguesa.com/revista/index.php/amp/article/viewFile/509/217 https://www.actamedicaportuguesa.com/rev... . Therefore, this study aimed to identify and critically evaluate systematic reviews addressing the effectiveness of interventions to reduce prescriptions of potentially inappropriate medication to older patients.

Study Design

This is an overview of systematic reviews addressing the effectiveness of interventions to reduce the number of prescriptions of potentially inappropriate medication to older patients.

Eligibility

The inclusion criteria of this overview were:

Participants: older patients (≥65 years) who have received drug prescription.

Interventions: the ones described in the selected studies aiming to reduce the number of prescriptions of potentially inappropriate medication to elderly patients.

Comparators: usual care to elderly patients or comparison to different interventions.

Outcomes: primary and secondary outcomes evaluated in the systematic reviews included in this study.

Study types: systematic reviews with or without meta-analysis that addressed the effectiveness of any intervention or combination of interventions to reduce the number of prescriptions of potentially inappropriate drugs to elderly patients, without restriction in terms of design of primary studies.

Exclusion Criteria

This overview excluded reviews based on the following criteria: a) abstracts for conference papers and protocols of systematic reviews; b) reviews exclusively based on gray literature; c) studies focused on a specific clinical condition or related to a particular medication or therapeutic class; d) systematic reviews addressing exclusively under-use of medications or interventions to improve treatment adherence; e) systematic reviews that have been updated, without loss of relevant information.

Search Method for Study Identification

The studies were searched and selected from Medline, Cochrane Library, Embase, CINAHL, Virtual Health Library, and Web of Science databases, combining the terms aged, prescriptions, inappropriate prescribing and potentially inappropriate medication list with their entry terms and other related descriptors without restriction in terms of study language or date of publication published by June 2017. Box 1 shows the full list of descriptors and Box 2 shows the search strategy in Medline database.

Study Selection

First, the titles and abstracts of searched reviews were evaluated to identify the studies that met the eligibility criteria. Then, full texts were analyzed and the references were reviewed to identify further relevant studies. Both stages were performed by two independent reviewers, and the divergences were resolved by consensus.

Data Extraction

Information was extracted about study population, type of intervention, professionals involved in the intervention, comparative treatment, outcome measures, and design of the studies included in the systematic reviews. Complementary information about diseases, sites where the interventions were implemented, and the tools used to assess the prescription of potentially inappropriate medication was also extracted, when available.

Data extraction was performed by the first reviewer and the information obtained was subsequently checked by a second reviewer. The divergences were resolved by consensus.

Quality Assessment

A MeaSurement Tool to Assess systematic Reviews (AMSTAR) was used for the methodological quality evaluation of the selected systematic reviews 10 10. Shea BJ, Grimshaw JM, Wells GA, Boers M, Andersson N, Hamel C, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10. https://doi.org/10.1186/1471-2288-7-10 https://doi.org/10.1186/1471-2288-7-10... . This instrument was specifically designed to evaluate systematic reviews and includes 11 items with four possible answers each. Every question with affirmative answer receives score 1. The systematic reviews selected were assessed by independent reviewers, and the divergences were resolved by consensus.

Based on the consensus score, the systematic reviews were classified as three levels: low methodological quality (score 0 to 3), moderate methodological quality (score 4 to 7), and high methodological quality (score 8 to 11) 11 11. Biondi-Zoccai G, editor. Umbrella reviews: evidence synthesis with overviews of reviews and meta-epidemiologic studies. Cham (CH): Springer International Publishing; 2016 [cited 2018 Feb 26]. Available from: http://www.springer.com/la/book/9783319256535. DOI: 10.1007/978-3-319-25655-9 http://www.springer.com/la/book/97833192... .

Data Analysis

The main results of the systematic reviews were grouped into thematic categories and discussed qualitatively as narrative synthesis. The method of content analysis was adopted to define the thematic categories 12 12. Bardin L. Content analysis. São Paulo: Edições 70; 2011. , 13 13. Minayo MCS. O desafio do conhecimento: pesquisa qualitativa em saúde. 14.ed. São Paulo: Hucitec; 2014. .

Extracted data were based on the results from each systematic review. Studies of multiple approaches were discussed under more than one thematic category. Discrepancies in the classification of interventions were resolved by consensus. The interventions identified and their results were described in narrative. Detailed information was extracted and systematized to discuss possible discrepant results of the interventions.

No meta-analyses or other quantitative analyses were performed because of the heterogeneity of the studies, considering their different designs, types of intervention, outcomes and measures.

In total, 1,850 studies were identified in the databases, and 302 duplicates were removed, resulting in 1,548 studies submitted to title and abstract screening. This initial screening removed 1,487 studies that did not meet the selection criteria. Later, after fully reading 61 eligible studies, 37 were excluded because they did not meet the inclusion criteria, resulting in 24 studies selected for this review. The flow diagram in Figure shows the study selection process.

Two systematic reviews from Cochrane 14 14. Patterson SM, Hughes C, Kerse N, Cardwell CR, Bradley MC. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2012(5):CD008165. https://doi.org/10.1002/14651858.CD008165.pub2 https://doi.org/10.1002/14651858.CD00816... , 15 15. Alldred DP, Raynor DK, Hughes C, Barber N, Chen TF, Spoor P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2013;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub2 https://doi.org/10.1002/14651858.CD00909... retrieved in the search were subsequently updated. This overview included the two most recent studies 16 16. Alldred DP, Kennedy MC, Hughes C, Chen TF, Miller P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2016;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub3 https://doi.org/10.1002/14651858.CD00909... , 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... only.

Characteristics of Studies

Table 1 shows the main characteristics of the studies. In terms of design of primary studies included in the systematic reviews, most of them were randomized controlled clinical trials. The number of primary studies included in the systematic reviews varied from four to 116. These studies were conducted in different settings, including: primary care, community, hospitals, nursing homes, and long-term care facilities. Fifteen systematic reviews were published in 2014–2017.

Methodological Quality Assessment

The methodological quality assessment according to AMSTAR found most systematic reviews of moderate quality (n = 10). Six studies presented enough score to be considered of high methodological quality and eight were classified as low quality studies. The last column of Table 1 shows the scores attributed to each systematic review.

Synthesis of Interventions Grouped into Thematic Categories

The interventions identified in selected systematic reviews were grouped into five thematic categories: medication review services (n = 16), pharmaceutical interventions (n = 10), computerized systems (n = 10), educational interventions (n = 8), and other interventions (n = 2).

Medication review services were not analyzed in the category of pharmaceutical interventions because, although they may be conducted by pharmacists, they often include other health professionals.

Table 2 shows the thematic categories addressed in each systematic review included in this study.

Medication Review Services

Medication review includes many interventions that can be performed by prescribers (self-review) or other health professionals (usually physicians, pharmacists, and nurses), alone or combined with others, that provide prescribers with recommendations to improve the quality of prescription and increase drug use safety 18 18. Blenkinsopp A, Bond C, Raynor DK. Medication reviews. 2012;74(4):573-80. https://doi.org/http://dx.doi.org/10.1111/j.1365-2125.2012.04331.x https://doi.org/http://dx.doi.org/10.111... .

Although the descriptions of medication reviews varied in the studies analyzed, the process generally involved a systematic assessment of the patient's pharmacotherapeutic needs and prescribed drugs, followed by recommendations to optimize the dosage. Promising results were observed in interventions involving pharmacists, with the authors emphasizing the importance of training these professionals on tools to identify inappropriate medications for older patients 19 19. Castelino RL, Bajorek BV, Chen TF. Targeting suboptimal prescribing in the elderly: a review of the impact of pharmacy services. Ann Pharmacother. 2009;43(6):1096-106. https://doi.org/10.1345/aph.1L700 https://doi.org/10.1345/aph.1L700... .

Medication review with a clinical pharmacist may have a positive influence on the use of medicines. These interventions, either alone or combined with others, can reduce the use of potentially inappropriate medications by older patients in different settings 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... , 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 7 7. Gutierrez Valencia M, Martinez Velilla N, Lacalle Fabo E, Beobide Telleria I, Larrayoz Sola B, Tosato M. Intervenciones para optimizar el tratamiento farmacológico en ancianos hospitalizados: una revisión sistemática. Rev Clin Esp. 2016;216(4):205-21. https://doi.org/10.1016/j.rce.2016.01.005 https://doi.org/10.1016/j.rce.2016.01.00... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... 21. Michelazzo MB, Milovanovic S, Boccia S. A systematic review of case-series studies on the effectiveness of interventions to reduce polypharmacy and its adverse consequences in the elderly. Epidemiol Biostat Public Health. 2017;14(1). https://doi.org/10.2427/12148 https://doi.org/10.2427/12148... 22. Riordan DO, Walsh KA, Galvin R, Sinnott C, Kearney PM, Byrne S. The effect of pharmacist-led interventions in optimising prescribing in older adults in primary care: a systematic review. SAGE Open Med. 2016;4:2050312116652568. https://doi.org/10.1177/2050312116652568 https://doi.org/10.1177/2050312116652568... 23. Thiruchelvam K, Hasan SS, Wong PS, Kairuz T. Residential aged care medication review to improve the quality of medication use: a systematic review. J Am Med Dir Assoc. 2017;18(1):87.e1-87.e14. https://doi.org/10.1016/j.jamda.2016.10.004 https://doi.org/10.1016/j.jamda.2016.10.... 24. Maeda K. Systematic review of the effects of improvement of prescription to reduce the number of medications in the elderly with polypharmacy. Yakugaku Zasshi. 2009;129(5):631-45. https://doi.org/10.1248/yakushi.129.631 https://doi.org/10.1248/yakushi.129.631... - 25 25. Rollason V, Vogt N. Reduction of polypharmacy in the elderly: a systematic review of the role of the pharmacist. Drugs Aging. 2003;20(11):817-32. https://doi.org/10.2165/00002512-200320110-00003 https://doi.org/10.2165/00002512-2003201... .

On the other hand, Holland et al. 26 26. Holland R, Desborough J, Goodyer L, Hall S, Wright D, Loke YK. Does pharmacist-led medication review help to reduce hospital admissions and deaths in older people? A systematic review and meta-analysis. Br J Clin Pharmacol. 2008;65(3):303-16. https://doi.org/10.1111/j.1365-2125.2007.03071.x https://doi.org/10.1111/j.1365-2125.2007... evaluated the impact of medication review on hospital admissions and mortality and found no positive effect.

The studies used different methods for medication review, whose methodology is a key issue in interventions, and it is not clear which would be the most appropriate 27 27. Johansson T, Abuzahra ME, Keller S, Mann E, Faller B, Sommerauer C, et al. Impact of strategies to reduce polypharmacy on clinically relevant endpoints: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(2):532-48. https://doi.org/10.1111/bcp.12959 https://doi.org/10.1111/bcp.12959... . The selection of outcomes to be measured in primary studies has also influenced the results 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... .

Many studies do not mention whether or not the recommended changes in prescription after the medication review were accepted by the prescriber. According to the authors, this is a critical parameter in medication review evaluation, since it describes actual changes in patient treatment as a result of the intervention 29 29. Loh ZW, Cheen MH, Wee HL. Humanistic and economic outcomes of pharmacist-provided medication review in the community-dwelling elderly: a systematic review and meta-analysis. J Clin Pharm Ther. 2016;41(6):621-33. https://doi.org/10.1111/jcpt.12453 https://doi.org/10.1111/jcpt.12453... , 30 30. Verrue CL, Petrovic M, Mehuys E, Remon JP, Vander Stichele R. Pharmacists’ interventions for optimization of medication use in nursing homes: a systematic review. Drugs Aging. 2009;26(1):37-49. https://doi.org/10.2165/0002512-200926010-00003 https://doi.org/10.2165/0002512-20092601... . These rates varied from 39.0% 31 31. Roberts MS, Stokes JA, King MA, Lynne TA, Purdie DM, Glasziou PP, et al. Outcomes of a randomized controlled trial of a clinical pharmacy intervention in 52 nursing homes. Br J Clin Pharmacol. 2001;51(3):257-65. https://doi.org/10.1046/j.1365-2125.2001.00347.x https://doi.org/10.1046/j.1365-2125.2001... to 91.6% 32 32. Furniss L, Burns A, Craig SK, Scobie S, Cooke J, Faragher B. Effects of a pharmacist's medication review in nursing homes: randomised controlled trial. 2000;176:563-7. https://doi.org/10.1192/bjp.176.6.563. https://doi.org/10.1192/bjp.176.6.563... , with possible low acceptance justified by the indirect contact of the pharmacist with the general practitioner, demonstrating the importance of communication in the multidisciplinary health team. The heterogeneity in study design and the quality of studies are obstacles to conclude whether medication reviews by pharmacists are more effective than interdisciplinary interventions 33 33. Tjia J, Velten SJ, Parsons C, Valluri S, Briesacher BA. Studies to reduce unnecessary medication use in frail older adults: a systematic review. Drugs Aging. 2013;30(5):285-307. https://doi.org/10.1007/s40266-013-0064-1 https://doi.org/10.1007/s40266-013-0064-... .

Pharmaceutical Intervention

It refers to the clinical practice of pharmacists, often integrated with physicians, nurses and other members of the health team, to solve or prevent problems that interfere or may interfere in the pharmacotherapy, which is part of the care process. The main objective of this activity is the prevention of errors in drug prescription, dispensing and administration, with a critical role in promoting the rational use of medication by ensuring proper pharmacotherapy with safe therapeutic results and minimizing unfavorable outcomes 34 34. Ribeiro VF, Sapucaia KCG, Aragão LAO, Bispo ICS, Oliveira VF, Lalves BL. Realização de intervenções farmacêuticas por meio de uma experiência em farmácia clínica. Rev Bras Farm Hosp Serv Saude. 2015 [cited 2018 Feb 26];6(4):18-22. Available from: http://www.sbrafh.org.br/rbfhss/public/artigos/2015060403000833BR.pdf http://www.sbrafh.org.br/rbfhss/public/a... .

Pharmaceutical care seems to improve prescriptions to older patients taking different medications at the same time (polypharmacy), especially when a multidisciplinary element is included in care 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... . The practice of pharmacists has been associated with benefits in different contexts, including primary care 22 22. Riordan DO, Walsh KA, Galvin R, Sinnott C, Kearney PM, Byrne S. The effect of pharmacist-led interventions in optimising prescribing in older adults in primary care: a systematic review. SAGE Open Med. 2016;4:2050312116652568. https://doi.org/10.1177/2050312116652568 https://doi.org/10.1177/2050312116652568... , hospitals 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... , 35 35. Walsh K, O’Riordan D, Kearney PM, Timmons S, Byrne S. Improving the appropriateness of prescribing in older patients: a systematic review and meta-analysis of pharmacists’ interventions in secondary care. Age Ageing. 2016;45(2):201-9. https://doi.org/10.1093/ageing/afv190 https://doi.org/10.1093/ageing/afv190... , and nursing homes 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... , 30 30. Verrue CL, Petrovic M, Mehuys E, Remon JP, Vander Stichele R. Pharmacists’ interventions for optimization of medication use in nursing homes: a systematic review. Drugs Aging. 2009;26(1):37-49. https://doi.org/10.2165/0002512-200926010-00003 https://doi.org/10.2165/0002512-20092601... . However, the role of a pharmacist in a multidisciplinary team needs to be more valued to help achieve the expected results 22 22. Riordan DO, Walsh KA, Galvin R, Sinnott C, Kearney PM, Byrne S. The effect of pharmacist-led interventions in optimising prescribing in older adults in primary care: a systematic review. SAGE Open Med. 2016;4:2050312116652568. https://doi.org/10.1177/2050312116652568 https://doi.org/10.1177/2050312116652568... .

Castelino et al. 19 19. Castelino RL, Bajorek BV, Chen TF. Targeting suboptimal prescribing in the elderly: a review of the impact of pharmacy services. Ann Pharmacother. 2009;43(6):1096-106. https://doi.org/10.1345/aph.1L700 https://doi.org/10.1345/aph.1L700... highlighted the importance of training pharmacists on validated tools to identify inappropriate medications. They also argued that the quality of a prescription can improve when these professionals assume a more active role in this process, since intervention studies generally focus on identifying failures after prescription.

On the other hand, Cooper et al. 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... found no evidence of benefit from pharmaceutical interventions on adverse events and admissions. Inadequate selection of outcome measures may have influenced the evaluation of efficacy of such interventions, whose therapeutic adequacy has been analyzed more often than other relevant health outcomes 21 21. Michelazzo MB, Milovanovic S, Boccia S. A systematic review of case-series studies on the effectiveness of interventions to reduce polypharmacy and its adverse consequences in the elderly. Epidemiol Biostat Public Health. 2017;14(1). https://doi.org/10.2427/12148 https://doi.org/10.2427/12148... , 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... .

Computerized Systems

Computerized systems allow electronic prescription and records about the medications taken by every patient; besides, they issue risk alerts and provide information about drug interactions. These systems are often used at two different levels: when making decisions and issuing alerts to pharmacies when dispensing drugs 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 36 36. Tamblyn R, Huang A, Perreault R, Jacques A, Roy D, Hanley J, et al. The medical office of the 21st century (MOXXI): effectiveness of computerized decision-making support in reducing inappropriate prescribing in primary care. CMAJ. 2003;169(6):549-56. 37. Devine EB, Hansen RN, Wilson-Norton JL, Lawless NM, Fisk AW, Blough DK, et al. The impact of computerized provider order entry on medication errors in a multispecialty group practice. J Am Med Inform Assoc. 2010;17(1):78-84. https://doi.org/10.1197/jamia.M3285 https://doi.org/10.1197/jamia.M3285... 38. Nemeth LS, Wessell AM. Improving medication safety in primary care using electronic health records. J Patient Saf. 2010;6(4):238-43. https://doi.org/10.1097/PTS.0b013e3181fe401f https://doi.org/10.1097/PTS.0b013e3181fe... 39. Boockvar KS, Livote EE, Goldstein N, Nebeker JR, Siu A, Fried T. Electronic health records and adverse drug events after patient transfer. Qual Saf Health Care. 2010;19(5):e16. https://doi.org/10.1136/qshc.2009.033050 https://doi.org/10.1136/qshc.2009.033050... 40. Moniz TT, Seger AC, Keohane CA, Seger DL, Bates DW, Rothschild JM. Addition of electronic prescription transmission to computerized prescriber order entry: effect on dispensing errors in community pharmacies. Am J Health Syst Pharm. 2011;68(2):158-63. https://doi.org/10.2146/ajhp080298 https://doi.org/10.2146/ajhp080298... 41. Hazlet TK, Lee TA, Hansten PD, Horn JR. Performance of community pharmacy drug interaction software. J Am Pharm Assoc (Wash). 2001;41(2):200-4. https://doi.org/10.1016/S1086-5802(16)31230-X https://doi.org/10.1016/S1086-5802(16)31... 42. Abramson EL, Bates DW, Jenter C, Volk LA, Barron Y, Quaresimo J, et al. Ambulatory prescribing errors among community-based providers in two states. J Am Med Inform Assoc. 2012;19(4):644-8. https://doi.org/10.1136/amiajnl-2011-000345 https://doi.org/10.1136/amiajnl-2011-000... 43. Raebel MA, Charles J, Dugan J, Carroll NM, Korner EJ, Brand DW, et al. Randomized trial to improve prescribing safety in ambulatory elderly patients. J Am Geriatr Soc. 2007;55(7):977-85. https://doi.org/10.1111/j.1532-5415.2007.01202.x https://doi.org/10.1111/j.1532-5415.2007... - 44 44. Humphries TL, Nikki C, Chester EA, Magid D, Rocho B. Evaluation of an electronic critical drug interaction program coupled with active pharmacist intervention. Ann Pharmacother. 2007;41(12):1979-85. https://doi.org/10.1345/aph.1K349 https://doi.org/10.1345/aph.1K349... .

Information and communications technologies are increasingly used to optimize prescriptions in different settings 16 16. Alldred DP, Kennedy MC, Hughes C, Chen TF, Miller P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2016;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub3 https://doi.org/10.1002/14651858.CD00909... . Most studies have demonstrated the effectiveness of computerized systems 7 7. Gutierrez Valencia M, Martinez Velilla N, Lacalle Fabo E, Beobide Telleria I, Larrayoz Sola B, Tosato M. Intervenciones para optimizar el tratamiento farmacológico en ancianos hospitalizados: una revisión sistemática. Rev Clin Esp. 2016;216(4):205-21. https://doi.org/10.1016/j.rce.2016.01.005 https://doi.org/10.1016/j.rce.2016.01.00... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... , 45 45. Marasinghe KM. Computerised clinical decision support systems to improve medication safety in long-term care homes: a systematic review. BMJ Open. 2015;5(5):e006539. https://doi.org/10.1136/bmjopen-2014-006539 https://doi.org/10.1136/bmjopen-2014-006... , including meta-analysis 46 46. Iankowitz N, Dowden M, Palomino S, Uzokwe H, Worral P. The effectiveness of computer system tools on potentially inappropriate medications ordered at discharge for adults older than 65 years of age: a systematic review. JBI Libr Syst Rev. 2012;10(13):798-831. https://doi.org/10.11124/jbisrir-2012-68 https://doi.org/10.11124/jbisrir-2012-68... .

Collaborative implementation of computerized systems and other interventions can optimize the safety of medication use in primary care and improve health outcomes 47 47. Olaniyan JO, Ghaleb M, Dhillon S, Robinson P. Safety of medication use in primary care. Int J Pharm Pract. 2015;23(1):3-20. https://doi.org/10.1111/ijpp.12120 https://doi.org/10.1111/ijpp.12120... . Patterson et al. 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... also highlighted a study 36 36. Tamblyn R, Huang A, Perreault R, Jacques A, Roy D, Hanley J, et al. The medical office of the 21st century (MOXXI): effectiveness of computerized decision-making support in reducing inappropriate prescribing in primary care. CMAJ. 2003;169(6):549-56. whose results were positive and showed that most pharmaceutical interventions involved a multidisciplinary component and interventions through computerized systems.

Although studies indicate a significant reduction of potentially inappropriate drug prescriptions, computerized systems may not provide a full picture of medication use by older patients, since other drugs may be purchased at pharmacies not participating in the intervention or as over-the-counter medicines 48 48. Shade MY, Berger AM, Chaperon C. Potentially inappropriate medications in community-dwelling older adults. Res Gerontol Nurs. 2014;7(4):178-92. https://doi.org/10.3928/19404921-20140210-01 https://doi.org/10.3928/19404921-2014021... . Gurwitz et al. 49 49. Gurwitz JH, Field TS, Rochon P, Judge J, Harrold LR, Bell CM, et al. Effect of computerized provider order entry with clinical decision support on adverse drug events in the long-term care setting. J Am Geriatr Soc. 2008;56(12):2225-33. https://doi.org/10.1111/j.1532-5415.2008.02004.x https://doi.org/10.1111/j.1532-5415.2008... also pointed out that the high number of alerts in a system can cause prescribers to ignore them, with a negative impact on the prescriptions.

Successful interventions with computerized systems should be tested and improved in different settings to enhance patient safety and minimize adverse effects. Regular medication review and timely interventions in prescriptions are essential in clinical practice to address the increasing challenges involving prescriptions to older patients 50 50. Yourman L, Concato J, Agostini JV. Use of computer decision support interventions to improve medication prescribing in older adults: a systematic review. Am J Geriatr Pharmacother. 2008;6(2):119-29. https://doi.org/10.1016/j.amjopharm.2008.06.001 https://doi.org/10.1016/j.amjopharm.2008... .

Educational Interventions

Educational interventions can be conducted in different ways, including educational sessions for health professionals aiming to reduce drug use; distribution of educational materials; training to expand the knowledge and skills of patients, caregivers, and health professionals; educational programs for prescribers or consumers; and patient education to optimize polypharmacy 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... , 51 51. Fulton MM, Allen ER. Polypharmacy in the elderly: a literature review. J Am Acad Nurse Pract. 2005;17(4):123-32. https://doi.org/10.1111/j.1041-2972.2005.0020.x https://doi.org/10.1111/j.1041-2972.2005... , 52 52. Page AT, Clifford RM, Potter K, Schwartz D, Etherton-Beer CD. The feasibility and effect of deprescribing in older adults on mortality and health: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(3):583-623. https://doi.org/10.1111/bcp.12975 https://doi.org/10.1111/bcp.12975... .

Educational interventions may reduce inappropriate drug prescription 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 48 48. Shade MY, Berger AM, Chaperon C. Potentially inappropriate medications in community-dwelling older adults. Res Gerontol Nurs. 2014;7(4):178-92. https://doi.org/10.3928/19404921-20140210-01 https://doi.org/10.3928/19404921-2014021... and hospitalization period 53 53. Pitkälä KH, Juola AL, Kautiainen H, Soini H, Finne-Soveri UH, Bell JS, et al. Education to reduce potentially harmful medication use among residents of assisted living facilities: a randomized controlled trial. J Am Med Dir Assoc. 2014;15(12):892-8. https://doi.org/10.1016/j.jamda.2014.04.002 https://doi.org/10.1016/j.jamda.2014.04.... , either alone or combined with other interventions 7 7. Gutierrez Valencia M, Martinez Velilla N, Lacalle Fabo E, Beobide Telleria I, Larrayoz Sola B, Tosato M. Intervenciones para optimizar el tratamiento farmacológico en ancianos hospitalizados: una revisión sistemática. Rev Clin Esp. 2016;216(4):205-21. https://doi.org/10.1016/j.rce.2016.01.005 https://doi.org/10.1016/j.rce.2016.01.00... .

Loganathan et al. 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... analyzed six studies 54 54. Fialová D, Topinková E, Gambassi G, Finne-Soveri H, Jónsson PV, Carpenter I, et al. Potentially inappropriate medication use among elderly home care patients in Europe. JAMA. 2005;293(11):1348-58. https://doi.org/10.1001/jama.293.11.1348 https://doi.org/10.1001/jama.293.11.1348... 55. Beers MH, Ouslander JG, Fingold SF, Morgenstern H, Reuben DB, Rogers W, et al. Inappropriate medication prescribing in skilled-nursing facilities. Ann Intern Med. 1992;117(8):684-9. https://doi.org/10.7326/0003-4819-117-8-684 https://doi.org/10.7326/0003-4819-117-8-... 56. Roberts MS, Stokes JA. Prescriptions, practitioners and pharmacists. Med J Aust. 1998;168(7):317-8. 57. Dartnell JG, Anderson RP, Chohan V, Galbraith KJ, Lyon ME, Nestor PJ, et al. Hospitalisation for adverse events related to drug therapy: incidence, avoidability and costs. Med J Aust. 1996;164(11):659-62. 58. Goodman M, Lazzarini R. Examination of the feasibility of an ongoing strategy for disposal of unwanted and outdated medicines [abstract]. In: Pharmaceutical Education Programme Conference; 1995; Sydney, AU. p.24-26. - 59 59. Blackbourn J. Readmission to Fremantle Hospital: part 2. Drug-related readmissions. Fremantle Hosp Drug Bull. 1991;15:13-6. that adopted strategies of educational intervention, resulting in improvements in prescriptions. These interventions included face-to-face academic detailing, interaction between the prescriber and a group of specialists, workshops for nurses, and family education.

However, educational interventions have been studied more in terms of changes in therapy than for other outcomes related to the quality of life of patients, costs and use of health services 21 21. Michelazzo MB, Milovanovic S, Boccia S. A systematic review of case-series studies on the effectiveness of interventions to reduce polypharmacy and its adverse consequences in the elderly. Epidemiol Biostat Public Health. 2017;14(1). https://doi.org/10.2427/12148 https://doi.org/10.2427/12148... .

Other Interventions

Two systematic reviews addressed other interventions to reduce the number of prescriptions of potentially inappropriate medications to older patients, including: geriatric medicine services 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , regulatory interventions 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , and deprescription 52 52. Page AT, Clifford RM, Potter K, Schwartz D, Etherton-Beer CD. The feasibility and effect of deprescribing in older adults on mortality and health: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(3):583-623. https://doi.org/10.1111/bcp.12975 https://doi.org/10.1111/bcp.12975... .

In a study conducted by Kaur et al. 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , all interventions involving geriatric medicine services resulted in improvements for patients. The authors also highlighted two studies on regulatory interventions that reduced the number of potentially inappropriate drug prescription: one in which pharmacy service provision became mandatory in nursing homes in Canada 60 60. Lane CJ, Bronskill SE, Sykora K, Dhalla IA, Anderson GM, Mamdani MM, et al. Potentially inappropriate prescribing in Ontario community-dwelling older adults and nursing home residents. J Am Geriatr Soc. 2004;52(6):861-6. https://doi.org/10.1111/j.1532-5415.2004.52250.x https://doi.org/10.1111/j.1532-5415.2004... , and one that assessed the impact of restrictive measures adopted in the Australian form Pharmaceutical Benefits Scheme (PBS), which lists prescription drugs subsidized by the government 61 61. King MA, Roberts MS. The influence of the Pharmaceutical Benefits Scheme (PBS) on inappropriate prescribing in Australian nursing homes. Pharm World Sci. 2007;29(1):39-42. https://doi.org/10.1007/s11096-005-5618-9 https://doi.org/10.1007/s11096-005-5618-... .

Page et al. 52 52. Page AT, Clifford RM, Potter K, Schwartz D, Etherton-Beer CD. The feasibility and effect of deprescribing in older adults on mortality and health: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(3):583-623. https://doi.org/10.1111/bcp.12975 https://doi.org/10.1111/bcp.12975... presented data about deprescription interventions aiming to reduce polypharmacy and extend longevity. Although the authors state further studies are required, their findings suggest that individualized interventions help reduce inappropriate polypharmacy and seem to be safe and feasible.

Main Findings

This overview of systematic reviews summarizes evidence of interventions to reduce the number of prescriptions of potentially inappropriate medications to older patients, identifying knowledge gaps and providing insight for policy making and future studies.

Medication review prevailed among the types of intervention in this overview. Most studies support the benefits of this intervention, especially when using validated tools. It has produced better results when associated with other interventions 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... , 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 16 16. Alldred DP, Kennedy MC, Hughes C, Chen TF, Miller P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2016;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub3 https://doi.org/10.1002/14651858.CD00909... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 22 22. Riordan DO, Walsh KA, Galvin R, Sinnott C, Kearney PM, Byrne S. The effect of pharmacist-led interventions in optimising prescribing in older adults in primary care: a systematic review. SAGE Open Med. 2016;4:2050312116652568. https://doi.org/10.1177/2050312116652568 https://doi.org/10.1177/2050312116652568... . On the other hand, choice of outcome measures 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... , study design 33 33. Tjia J, Velten SJ, Parsons C, Valluri S, Briesacher BA. Studies to reduce unnecessary medication use in frail older adults: a systematic review. Drugs Aging. 2013;30(5):285-307. https://doi.org/10.1007/s40266-013-0064-1 https://doi.org/10.1007/s40266-013-0064-... , and methodological quality 33 33. Tjia J, Velten SJ, Parsons C, Valluri S, Briesacher BA. Studies to reduce unnecessary medication use in frail older adults: a systematic review. Drugs Aging. 2013;30(5):285-307. https://doi.org/10.1007/s40266-013-0064-1 https://doi.org/10.1007/s40266-013-0064-... have often been obstacles when assessing the efficacy of this intervention.

The practice of pharmacists to reduce the number of prescriptions of potentially inappropriate medications to older patients is also highlighted in the literature. In this type of intervention, pharmacists can act with autonomy to change the prescription, or act passively, identifying problems related to medications and recommending changes to the prescriber, who makes the final decision 62 62. Meid AD, Lampert A, Burnett A, Seidling HM, Haefeli WE. The impact of pharmaceutical care interventions for medication underuse in older people: a systematic review and meta-analysis. Br J Clin Pharmacol. 2015;80(4):768-76. https://doi.org/10.1111/bcp.12657 https://doi.org/10.1111/bcp.12657... . The practice of pharmacists seems to improve prescription in different settings (hospitals, primary care, and nursing homes), particularly when inserted in multidisciplinary teams.

The use of computerized systems presented the best evidence of benefit in selected studies. These resources have been increasingly used in different scenarios, supporting either clinical decision making or the pharmacotherapeutic analysis in drug dispensing 16 16. Alldred DP, Kennedy MC, Hughes C, Chen TF, Miller P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2016;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub3 https://doi.org/10.1002/14651858.CD00909... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 45 45. Marasinghe KM. Computerised clinical decision support systems to improve medication safety in long-term care homes: a systematic review. BMJ Open. 2015;5(5):e006539. https://doi.org/10.1136/bmjopen-2014-006539 https://doi.org/10.1136/bmjopen-2014-006... , 46 46. Iankowitz N, Dowden M, Palomino S, Uzokwe H, Worral P. The effectiveness of computer system tools on potentially inappropriate medications ordered at discharge for adults older than 65 years of age: a systematic review. JBI Libr Syst Rev. 2012;10(13):798-831. https://doi.org/10.11124/jbisrir-2012-68 https://doi.org/10.11124/jbisrir-2012-68... , 50 50. Yourman L, Concato J, Agostini JV. Use of computer decision support interventions to improve medication prescribing in older adults: a systematic review. Am J Geriatr Pharmacother. 2008;6(2):119-29. https://doi.org/10.1016/j.amjopharm.2008.06.001 https://doi.org/10.1016/j.amjopharm.2008... .

Educational interventions can be designed for prescribers, other health professionals, patients or caregivers. Whether alone or combined with other interventions, they have been effective in reducing inappropriate use of medications 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 28 28. Loganathan M, Singh S, Franklin BD, Bottle A, Majeed A. Interventions to optimise prescribing in care homes: systematic review. Age Ageing. 2011;40(2):150-62. https://doi.org/10.1093/ageing/afq161 https://doi.org/10.1093/ageing/afq161... .

Regulatory policies that have produced positive results include the potential benefits of eliminating subsidies from potentially inappropriate medications to influence prescribing 61 61. King MA, Roberts MS. The influence of the Pharmaceutical Benefits Scheme (PBS) on inappropriate prescribing in Australian nursing homes. Pharm World Sci. 2007;29(1):39-42. https://doi.org/10.1007/s11096-005-5618-9 https://doi.org/10.1007/s11096-005-5618-... and making pharmacy services mandatory in nursing homes in Canada 60 60. Lane CJ, Bronskill SE, Sykora K, Dhalla IA, Anderson GM, Mamdani MM, et al. Potentially inappropriate prescribing in Ontario community-dwelling older adults and nursing home residents. J Am Geriatr Soc. 2004;52(6):861-6. https://doi.org/10.1111/j.1532-5415.2004.52250.x https://doi.org/10.1111/j.1532-5415.2004... .

Geriatric medicine services 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... and deprescription 52 52. Page AT, Clifford RM, Potter K, Schwartz D, Etherton-Beer CD. The feasibility and effect of deprescribing in older adults on mortality and health: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(3):583-623. https://doi.org/10.1111/bcp.12975 https://doi.org/10.1111/bcp.12975... have also resulted in improvements for patients.

Strengths and Limitations

One of the reasons for an overview of systematic reviews was to identify different interventions already implemented and evaluated in clinical practice and check which ones present the best evidence of benefit to promote the rational use of medications among older patients.

The strengths of this study include: description of interventions to reduce the number of prescriptions of potentially inappropriate medications to older patients, based on the evidence available; comprehensive search structured according to the PICOS (patient, intervention, comparison, outcomes and study type) method; methodological quality assessment of the studies; and no restrictions regarding language or date of publication.

The quality of systematic reviews, predominantly moderate, must be confirmed by further studies designed with more methodological rigor. It means that although each type of intervention reported relevant results, it was not possible to reach definitive conclusions about the most effective intervention to reduce the number of prescriptions of potentially inappropriate medications to older patients.

In addition, overviews of systematic reviews are subject to important limitations, especially when addressing complex issues and heterogeneous outcomes. When systematizing the results of almost 600 primary studies, particularities of individual studies may have been lost or neglected by the authors of the respective systematic reviews.

Implications for Practice

Evidence supports that the use of computerized systems reduces the prescription and dispensing of inappropriate drugs to older patients. Medication review, either by health professionals alone or in a multidisciplinary team, has presented promising results. However, the acceptance of recommendations by prescribers plays a critical role in the achievement of results, so there is no consensus on which is the best methodology. Interventions conducted by pharmacists may also improve drug prescription to older patients. It stresses the trend of pharmaceutical care implementation and values the clinical role of pharmacists integrated with other health professionals.

A combination of interventions was supported by the evidence of educational interventions 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 7 7. Gutierrez Valencia M, Martinez Velilla N, Lacalle Fabo E, Beobide Telleria I, Larrayoz Sola B, Tosato M. Intervenciones para optimizar el tratamiento farmacológico en ancianos hospitalizados: una revisión sistemática. Rev Clin Esp. 2016;216(4):205-21. https://doi.org/10.1016/j.rce.2016.01.005 https://doi.org/10.1016/j.rce.2016.01.00... and in the evaluation of the effectiveness of computerized systems 47 47. Olaniyan JO, Ghaleb M, Dhillon S, Robinson P. Safety of medication use in primary care. Int J Pharm Pract. 2015;23(1):3-20. https://doi.org/10.1111/ijpp.12120 https://doi.org/10.1111/ijpp.12120... , 50 50. Yourman L, Concato J, Agostini JV. Use of computer decision support interventions to improve medication prescribing in older adults: a systematic review. Am J Geriatr Pharmacother. 2008;6(2):119-29. https://doi.org/10.1016/j.amjopharm.2008.06.001 https://doi.org/10.1016/j.amjopharm.2008... and medication review services 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... , 5 5. Forsetlund L, Eike MC, Gjerberg E, Vist GE. Effect of interventions to reduce potentially inappropriate use of drugs in nursing homes: a systematic review of randomised controlled trials. BMC Geriatr. 2011;11:16. https://doi.org/10.1186/1471-2318-11-16 https://doi.org/10.1186/1471-2318-11-16... , 16 16. Alldred DP, Kennedy MC, Hughes C, Chen TF, Miller P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2016;(2):CD009095. https://doi.org/10.1002/14651858.CD009095.pub3 https://doi.org/10.1002/14651858.CD00909... , 20 20. Kaur S, Mitchell G, Vitetta L, Roberts MS. Interventions that can reduce inappropriate prescribing in the elderly: a systematic review. Drugs Aging. 2009;26(12):1013-28. https://doi.org/10.2165/11318890-000000000-00000 https://doi.org/10.2165/11318890-0000000... , 22 22. Riordan DO, Walsh KA, Galvin R, Sinnott C, Kearney PM, Byrne S. The effect of pharmacist-led interventions in optimising prescribing in older adults in primary care: a systematic review. SAGE Open Med. 2016;4:2050312116652568. https://doi.org/10.1177/2050312116652568 https://doi.org/10.1177/2050312116652568... .

Ideally, interventions should have been evaluated using clinically relevant outcomes, such as mortality, quality of life, or utilization of health services. But these outcomes were not evaluated in most primary studies included in the systematic reviews. Then, the interventions described can improve the prescription and enhance safety in the use of medications, but cannot confirm the clinical benefits achieved.

Implications for Research and Health Policies

A detailed description of the interventions, the settings where they were studied, the implementation strategies, and the results achieved is critical to reinforce the evidence and support the selection and implementation of the best interventions and their reproduction in different contexts 2 2. Cooper JA, Cadogan CA, Patterson SM, Kerse N, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy in older people: a Cochrane systematic review. BMJ Open. 2015;5(12):e009235. https://doi.org/10.1136/bmjopen-2015-009235 https://doi.org/10.1136/bmjopen-2015-009... , 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... . Also important, the cost of interventions should be compared to the economic impact of potentially inappropriate drug prescriptions to sensitize managers and policy makers.

Patient preferences, beliefs and behaviors may also be considered, as well as economic assessments and other aspects of health policies. Qualitative studies involving health professionals and patients can provide important information about obstacles for the implementation or acceptance of an intervention 27 27. Johansson T, Abuzahra ME, Keller S, Mann E, Faller B, Sommerauer C, et al. Impact of strategies to reduce polypharmacy on clinically relevant endpoints: a systematic review and meta-analysis. Br J Clin Pharmacol. 2016;82(2):532-48. https://doi.org/10.1111/bcp.12959 https://doi.org/10.1111/bcp.12959... . Interviews with prescribers can help understand their reasons for not accepting recommendations and alerts from computerized systems that support drug prescription.

Instead of evaluating the reduction in the number of potentially inappropriate drug prescriptions, a trend is observed towards the assessment of whether polypharmacy can be considered appropriate (when drugs were prescribed and used according to the best evidence) or inappropriate (when inappropriately prescribed or the intended benefits have not been achieved) 17 17. Patterson SM, Cadogan CA, Kerse N, Cardwell CR, Bradley MC, Ryan C, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev. 2014(10):CD008165. https://doi.org/10.1002/14651858.CD008165.pub3 https://doi.org/10.1002/14651858.CD00816... .

Future studies should ensure greater methodological rigor in the evaluation of interventions to reduce the number of potentially inappropriate drug prescription to older patients. Further studies are required which should investigate the effectiveness of individual and combined interventions. Studies comparing different interventions can also establish the real value of each intervention.

CONCLUSIONS

The systematic reviews included in this overview showed potential benefits from different interventions in reducing the number of prescriptions of potentially inappropriate medications to older patients. The results expected from each intervention were discussed in this overview, and although it was not possible to determine which one is the most effective, combined interventions are likely to achieve better results than isolated interventions.

Knowledge gaps reveal relevant topics for future studies to be conducted with the higher methodological rigor.

In order to increase the safety of medication use by older patients, organizational and structural measures can be planned and implemented in health services, such as: computerized systems to support drug prescription and dispensing, training on the use of validated tools for the detection of potentially inappropriate drugs, procedures and explicit routines for medication review, continuing education for health professionals, and geriatric medicine services.

It should be noted that the deployment of any intervention can become a reality with the involvement of all stakeholders: policy makers, administrators, health professionals, patients, and caregivers.

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• Funding: Programa de Suporte à Pós-Graduação de Instituições Comunitárias de Educação Superior (PROSUC – master's degree scholarship) of Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).
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Publication Dates

• Publication in this collection 31 Jan 2019
• Date of issue 2019
• Received 28 Feb 2018
• Accepted 06 Apr 2018

• http://orcid.org/0000-0003-1024-2313
• http://orcid.org/0000-0001-5069-6075
• http://orcid.org/0000-0002-1432-196X
• http://orcid.org/0000-0001-5179-3125
• Correspondence: Silvio Barberato-Filho Universidade de Sorocaba Rodovia Raposo Tavares km 92,5 18023-000 Sorocaba, SP, Brasil E-mail: [email protected]
• Authors’ Contribution: Study design and planning: NSS, SB-F. Data collection, analysis, and interpretation: NSS, LLM, FSM, SB-F. Text development and review, and public responsibility for study content: NSS, LLM, FSM, SB-F.
• Conflict of Interest: The authors declare no conflict of interest.

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Figures | tables.

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Figure   Flow diagram showing the selection process of systematic reviews about interventions to reduce the number of prescriptions of potentially inappropriate medications to older patients.

Box 1   Descriptors used in database search.

Box 2   search strategy in medline database (via pubmed)., table 1   characteristics of studies included in this overview..

• AMSTAR: A MeaSurement Tool to Assess systematic Reviews

Table 2   Thematic categories addressed in the systematic reviews about interventions to reduce the number of prescriptions of inappropriate medications to older patients evaluated in this overview.

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A systematic review of randomised-controlled trials on deprescribing outcomes in older adults with polypharmacy

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Helen Omuya, Clara Nickel, Paije Wilson, Betty Chewning, A systematic review of randomised-controlled trials on deprescribing outcomes in older adults with polypharmacy, International Journal of Pharmacy Practice , Volume 31, Issue 4, August 2023, Pages 349–368, https://doi.org/10.1093/ijpp/riad025

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Mixed findings about deprescribing impact have emerged from varied study designs, interventions, outcome measures and targeting sub-categories of medications or morbidities. This systematic review controls for study design by reviewing randomised-controlled trials (RCTs) of deprescribing interventions using comprehensive medication profiles. The goal is to provide a synthesis of interventions and patient outcomes to inform healthcare providers and policy makers about deprescribing effectiveness.

This systematic review aims to (1) review RCT deprescribing studies focusing on complete medication reviews of older adults with polypharmacy across all health settings, (2) map patients’ clinical and economic outcomes against intervention and implementation strategies and (3) inform research agendas based on observed benefits and best practices.

The PRISMA framework for systematic reviews was followed. Databases used were EBSCO Medline, PubMed, Cochrane Library, Scopus and Web of Science. Risk of bias was assessed using the Cochrane Risk of Bias tool for randomised trials.

Fourteen articles were included. Interventions varied in setting, preparation, use of interdisciplinary teams, validated guidelines and tools, patient-centredness and implementation strategy. Thirteen studies (92.9%) found deprescribing interventions reduced the number of drugs and/or doses taken. No studies found threats to patient safety in terms of primary outcomes including morbidity, hospitalisations, emergency room use and falls. Four of five studies identifying health quality of life as a primary outcome found significant effects associated with deprescribing. Both studies with cost as their primary outcome found significant effects as did two with cost as a secondary outcome. Studies did not systematically study how intervention components influenced deprescribing impact. To explore this gap, this review mapped studies’ primary outcomes to deprescribing intervention components using the Consolidated Framework for Implementation Research. Five studies had significant, positive primary outcomes related to health-related quality of life (HRQOL), cost and/or hospitalisation, with four reporting patient-centred elements in their intervention.

RCT primary outcomes found deprescribing is safe and reduces drug number or dose. Five RCTs found a significant deprescribing impact on HRQOL, cost or hospitalisation. Important future research agendas include analysing (1) understudied outcomes like cost, and (2) intervention and implementation components that enhance effectiveness, such as patient-centred elements.

Approximately 85% of older adults have at least one chronic health condition, and 60% have at least two [ 1 ] requiring prescription drugs, hospitalisation, and/or post-acute care. [ 2 ] Studies have shown that 36.7% of adults over the age of 60 use 5 or more drugs; some take 20 or more drugs a day. [ 2 , 3 ] This polypharmacy is common in older populations. [ 4 ] There are multiple definitions of polypharmacy, with the most common being the use of five or more prescription medications. [ 5 ] Polypharmacy in adults with multiple chronic conditions is associated with adverse drug reactions, toxicity, nonadherence, increased risk of falls, health care utilisation, cognitive impairment and could result in death. [ 4 , 6 , 7 ] Polypharmacy is also positively correlated with hospitalisations, morbidity and higher costs of health care. [ 8–10 ] The more medication increases, the higher the likelihood of potentially inappropriate medications (PIM). [ 11 , 12 ] Deprescribing can reduce the negative impacts of polypharmacy and PIM. [ 13 , 14 ] Deprescribing is the supervised withdrawal of PIM, for which the potential harms outweigh the benefits. [ 15 ]

Several publications have addressed deprescribing; however, the majority are prescriptive and conceptual rather than empirical studies. [ 16 , 17 ] Conceptualisation and operationalisation of deprescribing interventions vary across countries, settings and systems. Deprescribing interventions typically involve the withdrawal, reduction or substitution of potentially inappropriate medications. Some interventions have involved the use of computerised decision support tools, guidelines and criteria such as the Beers criteria, a Screening Tool to Alert about the Right Treatment (START) and Screening Tool of Older People’s Prescription (STOPP) tools, and a Systemic Tool to Reduce Inappropriate Prescribing (STRIP).

Systematic reviews on deprescribing have offered an important contribution by focusing attention on the outcomes of deprescribing. [ 18 ] However, reviews and empirical work alike often have mixed findings. [ 19–21 ] In an effort to narrow the lens of the study, systematic reviews have been largely limited to either disease states, physical status, drug class or participant settings. [ 22 ] The systematic reviews by Ibrahim et al. (2021) and Tjia et al. (2013) were limited to older people living with frailty. [ 23 , 24 ] Kua et al. (2019) focused on nursing homes [ 25 ] and Romano et al. (2020) focused on the economic evaluations among community-dwelling older adults. [ 26 ] Thillainadesan et al.(2018) performed a systematic review on deprescribing interventions using randomised-controlled trials (RCTs) with a focus on hospitalised patients. [ 27 ]

Studies have a such wide variation in study designs, operationalisations of deprescribing, and outcome measures that comparing studies is complicated. There is a need for a systematic review that controls study designs and interventions to some degree by limiting the focus to include only RCTs with clearly defined interventions to evaluate the effect of deprescribing interventions on older adults with polypharmacy. Following these parameters would allow us to include studies examining an individual’s full medication profile rather than a subgroup of medications or conditions and to do so across broad health care settings. This review targets interventions that focus on reducing potentially inappropriate medications intended to decrease medication or pill burden that could ultimately lead to improved clinical and economic outcomes.

Systematic reviews on deprescribing interventions have also used different frameworks to assess interventions. These reviews were important because they looked at enablers, barriers, challenges and behaviour change techniques in various clinical settings. [ 28–30 ] This current review adds to the knowledge by mapping intervention design components of randomised-controlled trials using the Consolidated Framework for implementation Research (CFIR) construct. [ 31 ] This assessment allows the reader to explore possible relationships between intervention components and outcomes.

For this review’s analysis, the definition of deprescribing follows the US Deprescribing Network definition as the thoughtful systematic process of identifying problematic medications and either reducing the dose or stopping these drugs in a manner that is safe, effective and helps people maximise their wellness and goals of care. [ 32 ] Characteristics of interventions that had significant beneficial outcomes are explored for factors that contributed to the positive effects. The results of the analysis in this review will also be presented in a way that leverages the intersections of evidence-based deprescribing practice and implementation sciences using three variables: (1) clinical intervention, (2) the implementation strategy and (3) barriers and facilitators. [ 33 ]

This systematic review aims to (1) review RCT deprescribing studies with a focus on complete medication reviews of older adults with polypharmacy, (2) map patients’ clinical and economic outcomes evidence against intervention and implementation strategies, and (3) help inform future research agendas based on the observed benefits and best practices of deprescribing interventions.

To address this agenda, the following questions will be explored:

What were the settings, patient population characteristics and sample size?

What were the intervention tools and strategies used and their duration?

What were the investigators’ comments about implementation barriers and challenges?

What outcomes were measured in addition to reducing drug burden and what findings emerged regarding safety, health-related quality of life, and economic outcomes?

What methodological challenges are common in this line of research?

This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews as shown in Figure 1 . [ 34 ] A protocol for the review was written to guide the review questions, search strategy and the inclusion/exclusion criteria.

PRISMA flow chart.

Eligibility criteria

Using the Population, Intervention, Comparator, Outcome (PICO) Framework , [ 35 ] inclusion and exclusion criteria were established. To be eligible for inclusion, studies had to have an RCT design. The study population had to be 65 years or older and taking five or more prescription or regular medications/drugs. This population was chosen as they are most impacted by multimorbid conditions [ 36 , 37 ] which are highly correlated with polypharmacy and PIM. [ 38–41 ] Deprescribing interventions had to examine the complete medication profile since comprehensive medication reviews in deprescribing interventions have been more effective in resolving drug-related problems and are perceived as more beneficial by patients. [ 42–44 ] The comparison group was ‘usual care’ which could include medication review if this was a usual practice in the study setting. A minimum of two outcomes needed to be reported. First, the study was required to measure whether the intervention attempted to reduce the participant’s number or dose of drugs; this is to ensure that deprescribing was an objective in the intervention. Second, an additional clinical and/or economic outcome had to be collected.

Articles were excluded which were not in English, did not have a clear intervention to reduce drugs or did not meet the inclusion criteria. Authors were contacted for articles that did not report the attempt or number of drugs reduced or when other questions arose. Authors were also contacted when the median rather than the mean number of drugs was reported.

Information sources

A comprehensive literature search was performed in five databases from inception to April 2022. Searched databases were EBSCO Medline, PubMed, Cochrane Library, Scopus and Web of Science (which included grey literature). References cited in reviewed articles and systematic reviews of the similar topic were also screened for eligibility.

Search strategy

A health sciences librarian (PW) in consultation with the clinically oriented reviewer, developed and performed a comprehensive search for this review. The search was translated and executed in Medline (EBSCOhost), PubMed, Scopus, Web of Science Core Collection and Cochrane Library (Wiley). The search contained a combination of controlled vocabulary and keywords relating to deprescribing, elderly and polypharmacy. No publication type, language or date filters were applied to the search. Results were imported into a citation manager (EndNote 20) and deduplicated using Bramer et al. ’s method. [ 45 ] The complete search strategy is included in the Appendix 1 .

Selection process

Articles retrieved from the databases were exported into an Excel sheet and three researchers independently screened the titles and abstracts of the search results against the inclusion and exclusion criteria. All articles were screened by at least two of the researchers. Discrepancies in the inclusion decisions were discussed with a third reviewer to reach a mutual agreement between the reviewers.

Data extraction process

One researcher extracted data from the selected publication and a second researcher reexamined all the articles independently for the same data elements. All uncertainties were resolved by the review team. Inconsistencies in the reports were resolved by looking into supplemental information provided by the authors and efforts were made to contact the authors when necessary. Data collection was done on Microsoft Excel version 16.64 (see Figure 1 ).

Data items (outcomes)

Each study measured whether there was a change in the number or dose of drugs as a result of the deprescribing intervention. In addition, several studies met the inclusion criteria for one or more clinical or economic outcomes. Some outcomes included safety implications such as hospitalisation, emergency room use, morbidity or falls. Other studies measured outcomes such as the cost of medications, subjective health status or health-related quality of life.

Study risk of bias assessment

The Cochrane Risk of Bias 2 (RoB 2) tool was used to assess bias arising from five domains: (1) randomisation process, (2) deviations from the intended interventions, (3) missing outcome data, (4) measurement of the outcome and (5) selection of the reported result. [ 46 ] An overall risk of bias was summarised based on the criteria in the RoB 2 tool judging studies as either ‘low’, ‘some’ or having ‘high’ concern of a risk of bias. One reviewer assessed the RoB of all included articles for the main outcome of interest: number, percentage or the dose of medication. This was assessed by the second reviewer.

Information synthesis

An extraction table providing a record of the key information from each article such as author, setting, providers, participant characteristics, intervention/comparison, outcomes and key findings relevant to clinical and economic outcomes in deprescribing interventions was used to synthesise the information. The tabular structure of individual studies and synthesis of data is shown in Table 1 .

Description Summary.

Sig denotes significant difference at the P < .05 significance level. IG, intervention group; CG, control group; HQOL, health-related quality of life.

1 Author explicitly identified measure was a primary outcome

Total randomised-controlled trials selected

A total of 6587 studies were identified by the literature search. After removing duplicates and exclusions, 105 studies were evaluated for eligibility (see Figure 1 ). Eight more studies were identified from citation sources. Initially, 19 RCT studies were selected for the review. However, five RCT studies had to be excluded after careful review. We were not able to ascertain that three of them met the inclusion criteria of requiring all study participants to have a medication regimen of five or more prescription or regularly used medications. [ 47–49 ] Efforts were made to contact the authors and two of them responded. Two other studies were vague about the deprescribing component and intent; nor did they give the number or mean of drugs discontinued. [ 50 , 51 ]

Descriptive overview of randomised-controlled trials

Fourteen RCTs met all eligibility criteria for this review giving a total of 8813 participants with 4414 in the IG and 4399 in the CG. [ 52–65 ] Given the heterogeneity of their sample characteristics, design, intervention, health care setting, country and outcomes, it is notable that 13 of the fourteen studies found deprescribing succeeded in reducing medication-related burden (e.g. number of drugs or doses). (See Table 1 ).

All the RCTs enrolled participants aged 65 years and older. Frailty, average age, and mean number of drugs varied depending on the health care setting where investigators conducted their research. Eight of the deprescribing trials were in primary care or outpatient sites, [ 52 , 53 , 55 , 60–63 , 65 ] two in community pharmacies, [ 59 , 64 ] one in a hospital, [ 56 ] and three in nursing home/long-term care facilities. [ 54 , 57 , 58 ] In nursing home studies, participants tended to be older (in their eighties) with a higher average number of 13 medications. [ 54 , 57 , 58 ] There was regional variation with 11 studies across Europe, 2 in North America and 1in Asia (see Table 1 ).

Intervention characteristics

Studies differed in staff preparation and implementation of their deprescribing interventions. Similar to Rantsi et al. description of strategies used to manage inappropriate medications, this review found deprescribing interventions used medication reviews, interdisciplinary interventions, staff education and computerised systems to prepare and deliver the intervention. [ 66 ] the most common drugs deprescribed in these studies included anticholinergics, proton pump inhibitors and antiplatelet drugs. These align with the literature as further validation of this research. [ 18 , 23 , 25 ] To help readers see the full variation in this review and the implications, Table 2 provides detailed descriptions of interventions, acceptance of deprescribing recommendations by prescribers, the most common drugs deprescribed, and information about restarting drugs that had been discontinued during the trial. Facilitators, barriers and some limitations that investigators reported are also described. Figure 2 shows the intervention components mapped to the primary outcome(s) for each study drawing on relevant CFIR constructs. [ 31 ]

Abbreviations: ADWE, adverse drug withdrawal event; CMR, comprehensive medication review; DRP, drug-related problems; FP, family physician; GP, general practitioner; HMG CoA, 3-hydroxy-3-methylglutaryl coenzyme A; NSAID, non-steroidal anti-inflammatory drugs; START, Screening Tool to Alert to Right Treatment; STOPP, Screening Tool of Older Persons’ Prescriptions.

Consolidated Framework for Implementation Research Used to Map Intervention Components to Primary Outcomes.

Five studies used established criteria such as STOPP/START or STOPPFrail to assist analysis of patient profiles for PIMs [ 52–54 , 56 , 57 ] and two used the Beers criteria. [ 55 , 57 ] Others used guides, templates and other decision support tools. [ 53 , 55 , 60 , 62 ] As part of interprofessional teams, pharmacists played a key role analysing the presence of PIMs in a variety of hospital, nursing home and clinic-based studies and took the lead in two community pharmacy-based studies. [ 58 , 59 ] The follow-up period for the studies ranged from 1 1/2months to 24 months. The complete deprescribing intervention was performed once in thirteen studies; however, one study had continuous medication review and follow-up throughout the study period. [ 59 ]

Outcomes of deprescribing randomised-controlled trials

The following sections explore deprescribing results related to medication reduction, safety, economic patient Health-Related Quality of Life (HRQOL), and subjective ratings of health status.

Change in number of drugs or dose

Twelve of 14 RCTs in this review documented that the deprescribing intervention reduced the number of drugs. A 13th reduced the dose in the intervention group compared to the control group. A 14th found no significant difference in the number of drugs or doses, citing a difficulty in recruitment to reach the needed sample size and a deprescribing intervention in the prior year. [ 54 ]

Investigators examined the safety of deprescribing using outcomes such as mortality, hospitalisations, emergency room visits and falls (see Table 1 ). Taken together, the findings are consistent across care site and country in terms of safety associated with their deprescribing interventions. Of the five studies with primary outcomes for hospitalisation, falls and emergency department (ED) visits, one found a significant decrease in hospitalisation [ 59 ] ; the other four found no significant difference. [ 53 , 55 , 57 , 62 ] Two studies treated mortality as a composite primary outcome with hospitalisation and found no significant differences between the IG and CG. [ 55 , 62 ] The same was true for falls as a primary outcome. [ 57 ]

Some studies’ secondary outcomes were underpowered or had timeframes too short to identify safety benefits or risks. [ 54 , 58 ] To assist readers, Table 1 marks primary outcomes with two asterisks. When secondary outcomes are included, 10 RCTs measured the impact of deprescribing on intervention-related mortality. All but one found either no differences between the intervention group (IG) and control group (CG) [ 52–56 , 58 , 62 , 63 ] or significantly fewer deaths for the IG than the CG at 6 months [ 57 ] and 4 months. [ 60 ] One study reported deaths unrelated to the intervention to be higher for the IG. [ 52 ]

Similar findings were reported for hospitalisation, emergency department (ED) visits, and falls as for mortality. Seven of the 10 studies evaluating hospitalisation found no significant differences between the IG and CG. [ 53–56 , 61–63 ] However, two studies found significantly fewer hospitalisations associated with the IG than the CG. [ 57 , 59 ] One of the three studies that measured ED visits found significantly less use associated with IG. [ 59 ] The other two did not find significant differences between groups. [ 52 , 53 ] Of the six studies which examined the impact of deprescribing on falls, five found no significant differences in falls [ 54 , 56 , 57 , 60 , 62 ] while one found a decrease in falls for the IG. [ 55 ]

Health-related quality of life outcomes

Four of the five articles that reported HRQOL as a primary outcome found a significant increase in patients’ health-related quality of life associated with deprescribing. [ 59 , 60 , 63 , 64 ]

Again, when studies treating HRQOL as a secondary outcome are included, six reported no difference between groups. [ 52 , 53 , 55 , 56 , 58 , 62 ] One study that used HRQOL as a primary outcome at 4 months reported a significant improvement in the IG compared to the CG. They did not find a significant difference at the secondary outcome timepoint of 13 months. [ 60 ] Two studies measured HRQOL using two instruments. [ 55 , 64 ] The EQ-Visual Analogue Scale (VAS) focused more on health status, had a significant positive difference for the IG and no difference in the EuroQol-5D 5L in one of the studies. [ 64 ] Another study that assessed self-rated health had a significant drop for the CG, but no change in the IG. [ 61 ]

Economic outcomes

Four of RCTs measured economic outcomes of deprescribing, two of them as primary outcomes. [ 59 , 65 ] All four found positive findings. Three studies measured the change in medication cost and found a lower cost of medications in the IG compared to the CG. [ 56 , 57 , 65 ] One study performed a cost-utility analysis estimating the incremental cost-effectiveness ratio and reported a reduction in the mean incremental total cost and an increase in the mean incremental Quality Adjusted Life Years as a result of the deprescribing intervention. [ 59 ]

Recommendation acceptance

When interventions were performed by interprofessional teams, the level of acceptance by either the primary physician or the patient was key and could vary. In one study, only 24.3% of the recommended medications were stopped by the General Physician. [ 55 ] Another study only had a 49% acceptance and implementation and an even lower sustainment at follow-up. [ 54 ] The low level of acceptance was a major factor in determining the true effectiveness of the intervention using an intention-to-treat analysis. Table 2 provides a summary of the recommendation acceptance.

Adverse drug events/adverse drug withdrawal events

Six studies reported a restart of deprescribed medication. [ 52–56 , 58 ] Three of the studies reported that medication was restarted in three participants, each representing 9.6–34.3% of the medications stopped. [ 54 , 56 , 58 ] In one study, the number of drugs restarted was 12.0%, 15.9% and 17.3% at 3, 6 and 12 months follow up, respectively. [ 53 ] Two studies reported adverse drug withdrawal events and adverse drug events. [ 52 , 54 ] One trial had adverse drug withdrawal events in 1.81% of the medications and had to restart those medications. [ 52 ]

Cochrane risk of bias in studies

The Cochrane Risk of Bias 2 tool (RoB 2) for randomized trails [ 46 ] was used to assess the risk of bias for the most frequent main outcome of interest for these studies – the change in the number of drugs or dose. Quality appraisal for the five domains in RoB 2 was developed using a Web App and is presented in Figure 3 . [ 67 ]

Cochrane Risk of Bias 2 Assessment.

The outcome measure was the number of drugs and dose reduction which is objective; hence there was no bias in the measurement of the outcome and the reporting of the result. Seven of the studies had a low risk of bias. One study had a high risk of bias due to possible contamination between IC and CG [ 60 ] ; the trial was conducted in a single centre with the same physician providing care to participants in the intervention and control group. No information was provided on if or how they ensured or monitored if the physicians adhered to the treatment protocol. Despite randomisation, two other studies had imbalances and inhomogeneity of some baseline characteristics across the study groups [ 55 , 65 ] Although one author reported that there was no statistical difference, it would be useful to offer the actual test values. [ 65 ] Five studies had risks of bias due to possible deviations from the intended intervention. Treatment contamination was possible in two studies where the prescribing physicians who received deprescribing recommendations from the pharmacist cared for both intervention group patients and control group patients. [ 42 , 44 ] Further, there was no measure of whether community-dwelling patients adhered to prescription changes in one of these studies. [ 53 ] Another study had concerns due to non-implementation of the intervention in 21.6% of the patients. [ 52 ] An additional study reported physician inconsistency following instructions for treatment of both groups; furthermore, there was a possibility of selection bias when doctors identified participants in their cluster. [ 62 ] Lastly, the overall rate of study discontinuation and loss to follow-up was greater than 20% in one study which included two patients (0.8%) that were not able to comply with the study protocol. [ 49 ]

Barriers and facilitators

Investigators suggested barriers and limitations that could have influenced the implementation of their interventions and the subsequent outcomes. The most common barriers were clinician time constraints, reluctance of patients and providers to adopt recommendations, lack of clinician knowledge and incomplete interprofessional team involvement. [ 58 , 61 , 63 ] They also identified facilitators. When patients were reluctant to stop medications, the assurance from clinicians that the medication would be restarted if there is an adverse event was reassuring. [ 49 ] As well, investigators reported the importance of ensuring patients’ contribution to the medication decisions. [ 63 , 64 ] Interprofessional collaboration to reach consensus on medications to be deprescribed was a major facilitator reported. [ 53 , 57 , 58 , 63 ] It was also a barrier when consensus was not reached. [ 55 ] These reports are valuable clues for future research to explore the process more systematically.

Mapping randomised-controlled trial’s primary outcomes to Consolidated Framework for Implementation Research intervention components

Until now, systematic reviews on RCT deprescribing studies have primarily evaluated the program outcome rather than exploring what are key components of an effective intervention. This review explored this gap by developing Figure 2 and includes findings for primary outcomes. It allows readers to map these outcomes in relation to a study’s intervention characteristics categorised under constructs from the Consolidated Framework for Implementation Research (CFIR). For each study, a shaded cell indicates a component of the intervention is relevant to one of the following CFIR constructs: ‘Outer Setting’ (including patient needs), ‘Inner Setting’ (including professionals’ preparations and resources), ‘Characteristics of Individual’ (physicians) and ‘Process’. Investigators’ perceptions of what facilitated their intervention’s implementation are indicated by a ‘plus sign’ in the cell, just as investigators’ perceptions of ‘barriers’ or ‘limitations’ is denoted by a ‘stop circle’ in a cell. In the primary outcomes columns in Figure 2 , an upward arrow denotes a significant increase between the IG and CG, while a downward arrow denotes a significant decrease between the IG and CG in the primary outcomes. Blank cells indicate no significant difference between IG and CG. As this table demonstrates, all significant findings reported by studies for their primary outcomes favoured the IG.

Five of the 14 studies had significant positive primary outcomes related to HRQOL, cost, and/or hospitalisation. When CFIR characteristics are explored in relation to these five studies, one component is present more than others – an explicitly reported patient-centred component in the CFIR ‘Outer Setting’ category related to attending to patient goals. While this relationship exists across the range of significant primary outcomes, it is clearest for the primary outcome of HRQOL where there are more studies. Out of the five studies where HRQOL was a primary outcome, four of the studies that had positive significant results from deprescribing shared the intervention characteristic of being patient goal focused. This aligns with respected, published recommendations for medication regimen changes to consider the patient’s own goals for care and condition. [ 68 ]

Main findings

This systematic review reports the findings of RCTs across all health settings evaluating the impact of deprescribing for a complete medication profile of older adults aged 65 and older with five or more prescription/regularly used drugs. Using the CFIR to map interventions and primary outcomes, majority of the studies that had significant positive primary outcomes related to HRQoL, cost and/or hospitalisation also reported a focus on patient goals and/or medication review follow-ups.

Inappropriate medication prescribing cuts across every sector of the health care system, including nursing homes, hospitals, primary care and it affects everyone regardless of age. [ 69 ] The studies in this review reflected this full range for older adults and health care settings. The studies offered large and small samples of patient populations ranging from 45 to 3904 participants, with varied degrees of frailty. Countries also ranged from Europe, North America and Asia, with 11 of the 14 studies from countries in Europe. The impact of deprescribing programs was tested on a range of outcomes including reduction in number of drugs and dose, safety (mortality, hospitalisation, emergency department visits, falls), economic outcomes, and health-related quality of life. There were remarkably consistent findings across studies given their differences in design, health care settings and countries (see Table 1 ).

Limitations and strengths

A major strength of this review of RCTs was the diversity of health care settings and countries investigating deprescribing interventions. This line of research is being recognised as important for the general older population regardless of their conditions or set of medications in their profile. To the extent that consistent patterns of findings emerged, we could assess their generalisability in this systematic review. Another strength was the growth in the number of recent studies in this population adopting a randomised-controlled trial study design. While the interventions themselves varied, we could still compare this range of deprescribing interventions against usual care to investigate trends.

As with all research, there are limitations we need to acknowledge. First, we only included publications in English and are very aware that important work is underway and being published in other languages. We look forward to learning from them as they become available in English. Second, the comparison of study findings was complicated with the differences between study populations, and design issues such as the number and length of observations, outcome measures used and power with sample sizes smaller than needed to analyse secondary outcome data. Third, there were times when unclear details were provided for categorisation of different variables for Figure 2 regarding implementation strategies.

Comparison of findings to other reviews

The heterogeneous, 14 RCTs in this review provided promising, consistent evidence by reviewing a complete patient medication profile. Interestingly, all significant findings involving the primary outcomes for all 14 RCTs were in the positive direction. No primary outcome was significant in a negative direction. This was true for the most frequent measures (reduced number of drugs) as well as less frequent primary outcome measures such as safety measures like hospitalisations, HRQOL and cost.

Several reviews on deprescribing had similar results regarding positive outcomes related to reducing medications as well as few significant findings regarding mortality, hospitalisation and falls. This was true even though their lens of investigation focused on particular health care settings and populations. [ 7 , 18 , 19 , 23 , 25 , 27 ] Notably, a review by Kua et al. (2019) found a significant impact on falls and all-cause mortality in a subgroup analysis of nursing home studies. [ 25 ] Thus, viewing these systematic reviews together reinforces that deprescribing can reduce inappropriate drugs in a way that is safe regarding outcomes such as mortality and hospitalisations.

Attention to patient goals offers the possibility of identifying robust factors influencing deprescribing success. Supporting this point, an umbrella review examined nine systematic reviews and proposes that interventions tailored to the patient’s situation offer better results specifically with respect to decreased mortality. [ 18 ] Further, the review argues there is a need to improve communication with patients as well as other colleagues involved in the intervention with patients. [ 18 ] Within our review, investigators commented on facilitators for deprescribing success including increasing the number of times that clinicians spoke with patients. [ 60 ] One study sharing a patient-centred orientation also conducted medication reviews along with follow-up reviews, rather than just a one-time intervention at the beginning. [ 59 ]

Beyond these similar findings across systematic reviews, some additional findings emerged from our review as a result of distinguishing between primary and secondary outcomes. The first of these is HRQOL. Four of the five studies with health-related quality of life as a primary outcome found significant positive differences between the IG and CG in our review. [ 59 , 60 , 63 , 64 ] Studies treating HRQOL as a secondary outcome did not find a significant impact on health-related quality of life and self-ratings of health status. This may be due in part to studies having smaller than needed power for their secondary outcomes as well as challenging response rates for self-report data. [ 54 , 58 ] The nature of the measure used is important to consider. Over half of the studies used the EuroQol-5D-5L instrument needs further validating in the older population. [ 56 ] Verdoorn found a positive significant difference on the Visual Analogue Scale (VAS) for the intervention group, but no significant difference on the EuroQol-5D-5L measure administered at the same time. [ 64 ] The time point of measurement and the presence of continuing reviews may also need to be considered in future work. A study reported that the intervention group increased in the VAS rating of health while the control group decreased during the six months follow up. [ 59 ] Finally, another study reported a significantly higher primary outcome HRQOL measure at 4 months for the IG compared to the CG, noting that the difference disappeared for their secondary outcome measure at 13 months. [ 60 ] This study recommended that continuous alignment of outcomes should be done by follow-up medication reviews. [ 60 ]

The second difference in findings between our review and others relates to cost outcomes. Relatively few randomised trials have explored economic implications although one review mentioned it as a secondary outcome. [ 23 ] Our systematic review of RCTs included four studies addressing economic outcomes, all of which had significant positive outcomes. Two of the studies had cost as a primary outcome. [ 59 , 65 ] This underscores the importance of much more research in this area of cost and utility. From a policy perspective, if upheld, these findings would have major implications for nationalised health systems as well as hybrid and private health care systems internationally.

Methods issues and implications

Using the Cochrane Risk of Bias 2 tool (RoB 2) for randomized trials [ 46 ] to assess the risk of bias helped to identify the limitations noted in Figure 3 . Selection bias needs to be protected against, particularly when clinicians help recruit and allocate study patients. Only two studies in the review experienced these challenges and risks of bias, yet they too offered important findings and information to this systematic review. [ 52 , 62 ] In general, this field is benefitting from high-quality RCTs.

As noted earlier, studies faced multiple design challenges. Sample size limitations existed for different measures within a single study. Frequently, studies included secondary outcomes with insufficient power to detect differences. It is important for studies to select some of their formerly secondary variables and plan for sufficient sample and power to test their intervention impact on these clinical and economic outcomes. There is also a need for longer observation periods with ongoing medication review with as needed deprescribing to capture the trajectory of deprescribing impact. Sufficient multiple observation points are needed, especially given those outcome findings differed by month of study. [ 60 ] Challenges in recruitment need to be acknowledged in order to improve the percent of participation and the external validity of some samples. Similarly, the retention of samples and follow-up to improve return rates if mail is used to gather patient-reported outcomes deserves further incentives and attention. Not infrequently, key aspects of the intervention’s implementation and its fidelity were not provided. This limits inferences about describing intervention effectiveness.

Research agenda

While many studies have documented the success of deprescribing to reduce the number of drugs and doses prescribed for patients, the deprescribing field urgently needs more studies that power their studies to explicitly test the impact of other deprescribing on outcomes such as quality of life and economic effects with adequate ongoing review and follow-up time periods to reinforce and measure these effects. The smaller number of studies that powered these as primary outcomes and short follow-up periods weaken inferences.

There is also a need for more information about the process of implementing interventions. For example, little information was provided on the actual patient–provider communication in inter-professional interventions and how interprofessional communication/collaboration was nurtured and maintained during time pressures. Future research could explore whether systematically studying specific components of interventions such as ongoing patient interaction with medication review at follow-ups could amplify the effect of focusing on patient goals and contributed to positive outcomes. There is a need for RCTs in this population to explicitly study this patient-centred component to test and understand their potential influence on outcomes. The degree of patient-centredness needs to be measured.

This systematic review analysed the outcomes from 14 RCT deprescribing studies reviewing the complete medication profiles of older adults with polypharmacy taking at least 5 prescriptions or regularly used medications. While this review focused broadly across all health care settings, almost all studies found deprescribing succeeded in reducing drugs and/or doses without risking safety as measured by mortality, hospitalisation, emergency room visits or falls as primary outcomes. Similar findings have emerged from systematic reviews of deprescribing within a single type of setting.

Four out of the five studies using HRQOL as a primary outcome found a positive impact from deprescribing. In addition, all four studies which examined the economic outcomes of deprescribing found positive outcomes regarding a lower cost of medications in the intervention group compared to the control group. [ 51 , 56 , 57 , 65 ] One cost-utility analysis estimated the incremental cost-effectiveness ratio and reported a reduction in the mean incremental total cost and an increase in the mean incremental Quality Adjusted Life Years as a result of the deprescribing intervention. [ 59 ] Given the small number of studies in this area, it is important to investigate the economic effects of deprescribing further.

Finally, these studies quite legitimately focused on measuring outcomes. However, it is time also to systematically study the process of deprescribing interventions to understand more about the components of interventions and their implementation which most influence deprescribing outcomes. Adding this research agenda to the RCT outcome studies has the potential to improve deprescribing outcomes, implementation, maintenance and dissemination internationally.

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Polypharmacy in multimorbid older adults: protocol for a systematic review

• Caroline Sirois   ORCID: orcid.org/0000-0003-3294-7883 1 , 2 , 3 , 4 , 8 ,
• Marie-Laure Laroche 5 , 6 ,
• Line Guénette 4 , 7 ,
• Edeltraut Kröger 2 , 4 , 7 ,
• Dan Cooper 1 , 7 &
• Valérie Émond 3  

Systematic Reviews volume  6 , Article number:  104 ( 2017 ) Cite this article

4054 Accesses

8 Citations

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Polypharmacy, the concurrent use of multiple medications, consistently evokes a negative connotation, notably because it is associated with a plethora of adverse events. Nonetheless, the number of individuals exposed to polypharmacy is increasing steeply, especially for older people with multiple diseases. There is a need to carefully study the phenomenon at the population scale to full assess the associated health outcomes. Yet, this reveals a complex task because there exists no consensus indicator of polypharmacy. In fact, the definitions of polypharmacy are heterogeneous and its predisposing factors and associated outcomes are not well defined. The goal of this systematic review is to summarize the literature on polypharmacy in multimorbid individuals aged 65 years and over, targeting three objectives: (1) to identify the definitions of polypharmacy that are used in the context of multimorbidity among older individuals (≥65 years); (2) to ascertain predisposing and concurrent factors associated with polypharmacy; and (3) to describe positive and negative outcomes of polypharmacy among older individuals, including hospitalizations, mortality and costs.

We will include publications from 2004 to 2016 that target four concepts: polypharmacy, older individuals, multimorbidity and positive/negative outcomes. The search will be performed using EBM Reviews, Embase, Global Health, MEDLINE, AgeLine, CINAHL, Health Policy Reference Center, Public Affairs Index, SocINDEX and Google Scholar. Two independent reviewers will screen the articles, extract the information and evaluate the methodological quality of included studies. The results will be presented in tables and narrative summaries will be performed. We will perform meta-analyses (objective 3) if the heterogeneity is not important.

This review will help describe the various ways of conceptualizing polypharmacy and how it is associated with health outcomes. We have selected outcomes most relevant for public surveillance performed with administrative databases. Other positive and negative outcomes have been associated with polypharmacy but may not be included in the review.

Systematic review registration

PROSPERO CRD42014014989

Peer Review reports

The number of older individuals exposed to multiple medications has been increasing tremendously in the recent years. In Canada, two thirds of individuals aged 65 years and over use at least 5 medications per year, and 27% uses at least ten [ 1 ]. In Ireland, the proportion of older individuals exposed to ≥10 medications has risen from 1.5% in 1997 to 21.9% in 2012 [ 2 ]. This increase in medication use is partly explained by the fact that clinical guidelines frequently encourage the use of multiple medications to treat single chronic diseases. However, the impact of using many medications together for different chronic diseases has not been assessed in randomized controlled trials, under controlled environments. The evidence is thus limited to observational data, which nonetheless appear as an optimal design to study complex situations like polypharmacy that are hardly suitable for evaluation in randomized trials. However, observational data are prone to bias and caution must be paid when interpreting results. An increased number of medications has been associated with adverse events in observational studies [ 3 ], such as hospitalization, mortality, falls [ 4 ], inappropriate prescribing [ 5 ], side effects [ 6 ] or drug-drug or drug-disease interactions [ 7 , 8 ]. The benefits of polypharmacy are well less known. Therefore, the decision of adding yet another medication in older patients sometimes becomes a difficult one for clinicians [ 9 , 10 ].

Obtaining a clear and complete portrait of polypharmacy and its impacts reveals a daunting task. Part of the problem emerges from the fact that there is no consensus on the definition of polypharmacy. Indeed, the literature presents an impressive array of heterogeneous definitions. One approach advocates a definition based on the number of medications, but there is no theoretical basis that may confirm the number of medications required for such a definition [ 11 ]. Another approach promotes a definition involving the quality of prescribing, but distinguishing appropriate and inappropriate polypharmacy remains difficult [ 3 ]. In fact, defining polypharmacy is a conceptual challenge. The problematic involves complex situations that impose reflections. For example, the pertinence of polypharmacy may vary according to life expectancy, comorbidities or side effects. This aspect has not been addressed thoroughly in systematic reviews conducted until now [ 12 , 13 , 14 , 15 ].

To fully understand the impacts of polypharmacy, there is a need to identify the predisposing and concurrent factors associated with the use of multiple drugs. Some elements have been associated with polypharmacy, such as older age [ 12 , 16 , 17 , 18 ], lower education levels [ 12 , 16 , 17 , 18 ], being a woman [ 12 , 16 , 17 , 18 ], a recent hospitalization [ 18 ] or multiple prescribers [ 17 ]. Nonetheless, some inconsistencies have been reported around those factors, which are often not evaluated in relation to other contributing factors. Therefore, the features that favour the development of polypharmacy, the groups that are most susceptible to benefit or suffer from polypharmacy, and the characteristics of polypharmacy (specific medications or combinations, interactions) that are most likely to lead to these outcomes are still not well defined for the older population. Such knowledge is essential to ensure rational decisions in treating older individuals.

When medications are used in accordance with clinical practice guidance, the use of multiple drugs should engender positive impacts in multimorbid patients, but polypharmacy has constantly been associated with adverse outcomes. There is a need to thoroughly search how polypharmacy can also be beneficial, notably in terms of hospitalizations and mortality. Finally, evaluating the costs that are driven by polypharmacy is an important task to establish the direct and indirect impacts that polypharmacy engenders on the health system.

There is a need to gather information about polypharmacy to fully judge its consequences and to develop interventions designed to tackle the issues related to this phenomenon, both at the individual and population level. For example, the Institut national de santé publique du Québec (INSPQ) intends to create a population-based surveillance system for polypharmacy, using the Quebec Integrated Chronic Disease Surveillance System (QICDSS) [ 19 ]. In order to be useful, the polypharmacy indicators created for surveillance should respond to the needs of all possible knowledge users, including clinicians, researchers, and decision makers. Yet, there is no data on how well the conceptualizations of polypharmacy align among those fields. Exploring definitions and outcomes of polypharmacy will help design indicators that will be relevant for all purposes.

The goal of this systematic review is to summarize the literature on polypharmacy among multimorbid individuals aged 65 years and over. Specifically, we intend the following:

To identify the definitions of polypharmacy that are used in the context of multimorbidity among older individuals (≥65 years)

To ascertain predisposing (that lead to) and concurrent (that are simultaneously present) factors associated with polypharmacy among older individuals

To describe positive and negative outcomes of polypharmacy among older individuals on hospitalizations, mortality and costs.

Participants/population

The review will consider studies that include people aged 65 years and older with at least two concurrent chronic diseases. We will include studies if at least one of the following applies:

At least 80% of participants are aged 65 years and older.

The data from people aged 65 years and older can be extracted.

We will include all settings (community, hospital, nursing homes) and types of health care (public, private). We will perform subgroup analyses according to those settings.

Exposure and comparators

Older individuals with chronic diseases exposed to polypharmacy will be considered. Older individuals with chronic disease not exposed to polypharmacy will be the comparators when applicable (objectives 2 and 3).

Objective 1: We will include articles presenting a clear operational definition of polypharmacy.

Objective 2: We will include studies that quantify the association of predisposing or concurrent factors (e.g. demographic, treatment-related, morbidity, health system-related) with the presence of polypharmacy.

Objective 3: We will include studies that evaluate the following outcomes of polypharmacy:

Hospitalization or emergency department visits

Costs [e.g. direct (medication, hospitalization, medical visits, diagnostic procedures, laboratory procedures) and indirect (e.g. for relatives: productivity loss, early retirement)]

A systematic search strategy (see Additional file 1 ) has been developed by the authors (CS, VE) in collaboration with an experienced librarian (VT). A second librarian specialized in health sciences has revised the proposed strategy (SV). A first search has been performed in December 2014 and was updated in May 2016 using the ovidSP (Bouquet total access collection, EBM Reviews, Embase, Global Health, MEDLINE) and EbscoHost (AgeLine, CINAHL, Health Policy Reference Center, MEDLINE, Public Affairs Index, SocINDEX) platforms. We will also search Google Scholar and Google to identify grey literature, such as governmental reports, reporting on indicators of polypharmacy that have been used for population-based monitoring.

Four concepts have been defined in our search: polypharmacy, older individuals, multimorbidity and positive/negative outcomes. The search strategy has been adapted to the syntax requirements of each database (use of different thesaurus terms, truncation and wildcard characters). We included studies published since 2004 (corresponding to the last 10 years before our first search) in all languages. We will also hand search the bibliographies of all included papers to retrieve studies that have not been identified through the database searches.

Types of study to be included

There will be no restrictions on the types of study. We will include randomized controlled trials, non-randomized controlled trials, quasi-experimental trials, before and after studies, transversal descriptive studies, surveys, cohort studies, case–control studies, case reports and case series. Reviews, commentaries, editorials and practice guidelines will be used to identify polypharmacy definitions, and they will be searched for the primary references they refer to. Studies evaluating interventions regarding polypharmacy and methodological studies (e.g. those comparing two definitions) will be evaluated. We will also evaluate the grey literature, such as reports, thesis and governmental publications. In case of missing information (both for abstracts and full text), we will contact the authors to complete the required information if the study corresponds to the inclusion criteria. Only those studies published in the last 12 years (2004–2016) will be included to ensure that polypharmacy is representative of today’s pharmacological arsenal and definitions of polypharmacy.

Study selection

We used Endnote to group the results and exclude duplicated articles. Two independent reviewers will examine the titles and screen the abstracts (MD, CS). Full-text articles will be retrieved for the papers not excluded from the previous two steps. Full text will be reviewed by two independent reviewers (CS and NSD/AZ). Additional information from the study authors will be sought if questions about eligibility arise. In case of disagreement, consensus will be obtained through discussion; if consensus cannot be reached, a third reviewer will be consulted (VE). All exclusion criteria will be recorded at each step (title, abstract and full-text review) in order to create flow charts according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) requirements (see Additional file 2 ). The selection process will be repeated independently for the three objectives.

Articles will be excluded on the basis of the following exclusion criteria:

The article does not provide an operational definition of polypharmacy. For example, defining polypharmacy as “large number of medications” would not qualify as an operational definition. To be considered operational, the definition can involve a specific number of medications (e.g. 5 medications and more) or indicate a specific condition (e.g. complex medication regimen with at least one inappropriate medication).

The studied population do not include people 65 years and over. Studies that include individuals younger than 65 years and over can be included if (a) 80% and more of the study population is 65 years old and (b) there are stratified analyses for the age group 65 years and over that allow the extraction of specific data for this age group.

The article refers to polypharmacy used for the treatment of a single medical condition in the absence of multimorbidity. Since the review focuses on individuals with multimorbidity, studies that evaluate a specific disease will be included only if individuals present other concomitant conditions. We will therefore not examine studies that focus on polypharmacy as treatment for a single disease (e.g. polypharmacy for psychiatric conditions can be described as the use of two psychotropic medications).

Missing information. The abstracts will be excluded if required information is not included in the abstract and no further information was available after contacting the corresponding author. The same applies for full-text articles.

Systematic review. The primary references included in the systematic reviews will be included in our review if they respond to our inclusion criteria. Systematic reviews can be included in objective 1 if they provide an operational definition of polypharmacy.

The article does not provide information about predisposing or concurrent factors related to polypharmacy (objective 2 only).

The article does not address outcomes of polypharmacy targeted in our review (objective 3 only).

The paper was published before 2004.

The article is published in a language that our team is not fluent with (English, French, Spanish, German, Portuguese, Arabic) or for which we do not find adequate resources to translate.

Duplicate publications. This exclusion criterion regroups studies that are summary of another published article, duplicate of studies already included or response letter to published articles.

Data extraction

Two independent reviewers (AZ/NSD, CS) will conduct a full-paper evaluation and data extraction. Established data extraction forms adapted for the three objectives of the review have been created using FileMaker MD ( https://www.filemaker.com ). This will allow all researchers to have access to the data in real time.

For each study, we will record bibliographic details, type of study, context, participants and the definition of polypharmacy. Duplicate studies (articles related to the same specific study) will be excluded (criterion 10). We will record specific information according to each objective:

Objective 1: We will extract details about the definition of polypharmacy, the types of medications included in the definition, the way the medications have been counted or what qualitative criteria have been used in order to label a medication regimen as polypharmacy (e.g. inappropriate medication). The methods used to define the quality of polypharmacy will be recorded when present. We will compare the definitions used in the publications according to whether the article relates to areas of clinical practice, research or public health. This will allow us to evaluate whether the concept of polypharmacy is consistent between the three areas, and whether to develop a single indicator of polypharmacy that is pertinent for the three areas is realistic. We will also evaluate whether the definition used in the articles relies on a theoretical framework is the result of a methodological assessment, refers to other published material or seems arbitrary. We will regroup definitions according to their nature (numerical definitions only, quality of prescribing only, mixed definitions).

Objective 2: We will extract factors that are associated with polypharmacy (prevalence) and those associated with its development (incidence), taking into account the definition of polypharmacy. We will group factors in three categories: patient-related (e.g. sex, age); disease-related (e.g. comorbidity, inappropriate medications); and health system-related (e.g., multiple prescribers, insurance type).

Objective 3: We will extract information on three outcomes: (1) hospitalization/emergency department visits (all-caused, specific causes and hospitalization length); (2) all-cause and specific mortality; (3) direct costs (related to medications, medical visits, emergency unit visits, hospitalization, diagnostic procedures) and indirect costs.

Risk of bias (quality) assessment

For objectives 2 and 3, two independent reviewers (AZ and (LG, MLL, EK, DC, ND)) will assess the quality of the studies according to the Scottish Intercollegiate Guidelines Network methodology checklists for controlled trials, cohort studies and case–control studies [ 20 – 22 ]. In case of disagreement between two reviewers that cannot be resolved through discussion, a third reviewer will be consulted to reach consensus (CS).

The studies will be rated according to a nominal scale of risk based on the gathered information (critical, serious, moderate or low risk). The quality assessment data will be presented in the table of the results. All data will be interpreted in light of the risk of bias. Subgroup analysis based on quality will be performed if required.

Strategy for data synthesis

We will conduct a narrative synthesis of individual studies for the three objectives. We will summarize information on study types, population characteristics, settings and outcomes. We expect that the heterogeneity of the definitions of polypharmacy will preclude the possibility of a meta-analysis of the outcomes stated in objective 3. We will use GRADE criteria to appraise the quality of the evidence.

Analysis of subgroups or subsets

We will analyze the results according to different subgroups if possible: age groups (e.g. 65–74/75–84/85+; or 75 and above, etc.), sex, comorbidities (patients with diabetes/cardiovascular disorders/pulmonary conditions/chemotherapy…), settings (community, hospital, nursing homes) and type of drug plan (public, private).

This review will summarize the data around polypharmacy in older individuals following the criteria of the PRISMA-P checklist (see Additional file 3 ). The first objective will help us gather the different definitions of polypharmacy used in the context of multimorbidity among older individuals. This collation will notably help evaluate if conceptualization of polypharmacy diverges between different settings and populations, and whether visions of polypharmacy in clinical practice, research and population surveillance are aligned. Considering the heterogeneity of the definitions and the amount of potential data we will likely gather, we do not intend to evaluate the quality of each definition retrieved. As such, this first stage of the review corresponds to the methodology of a scoping review. We acknowledge that a quality assessment of definitions would provide more insight to the work, but at this stage, we do not intend to clarify what should be the best definition of polypharmacy. The review will also help identify in a systematic way the factors that are associated with polypharmacy, and the characteristics of polypharmacy that are linked with increased or decreased risks of hospitalization, mortality costs outcomes. We are under no illusions with regard to the possibility of performing meta-analysis for the third objective of the review. We expect that the heterogeneous definitions will preclude such analysis. There is also a definite possibility that a significant number of studies that report factors associated with polypharmacy be of low quality (e.g. presenting univariate evaluation of factors only), which will limit the conclusions that we can generate from the review.

There are other known limitations to our protocol regarding the information retrieved from the literature. First, since our overarching goal is to determine how polypharmacy is defined and tied to health outcomes, studies focusing on a number of medications without considering a specific definition of polypharmacy will not be included. However, we believe our search strategy will identify most of these papers, which should not be excluded before the full-text stage. We will therefore be able to evaluate how our exclusion criteria could impact the results, and we will discuss this point in our review. Second, considering that research on polypharmacy has been increasing in recent years, we expect that a large number of abstracts will be retrieved from our search and that the full-length papers related to them will not yet be available. We will strive for ensuring that complete information be available for all eligible studies, notably by contacting authors for all abstracts and full text that do not provide required data. Nonetheless, we anticipate that some authors will not answer our queries, which will limit the inclusion of recent evidence into our review. Finally, we have selected a limited number of outcomes for the third objective. Those outcomes should be the most relevant for population surveillance as they can be tracked in administrative databases. However, other important outcomes for clinical practice, such as adverse events and adherence, will not be addressed.

Our review will include a great number of observational studies. This poses challenges because it entails ensuring the associations observed are not biased (e.g. confounding by multimorbidity). Considerable effort must be deployed to ensure quality of such studies is adequately evaluated [ 23 , 24 ]; our team of experienced pharmacoepidemiologists should be capable of addressing this challenge.

We believe the results of this review will help optimize polypharmacy. The increased knowledge about polypharmacy will benefit students and clinicians because there is an obvious need to improve education about polypharmacy [ 25 , 26 ]. By looking at definitions that are tied to outcomes, we will help establish what should a polypharmacy indicator comprise. Validated polypharmacy indicators will be useful for public health, researchers and clinicians. They will allow for surveillance but also to identify individuals at risk of suffering from negative impacts of polypharmacy and to target individuals who are most likely to benefit from polypharmacy under certain circumstances.

Abbreviations

Cumulative Index to Nursing and Allied Health Literature

Excerpta Medica dataBASE

Grading of Recommendations Assessment, Development and Evaluation

Medical Literature Analysis and Retrieval System Online

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

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Acknowledgements

The authors want to thank Vicky Tessier, librarian at the INSPQ for her help in elaborating the search strategy and management of files. The authors also thank Sandrine Vachon from UQAR for double checking the search strategy.

This project is funded by the Canadian Institute of Health Research (Knowledge Synthesis Grant). The funder had no role in the development of this protocol.

Availability of data and materials

The datasets that will be analysed during the current study will be available from the corresponding author on reasonable request.

Authors’ contributions

CS and VE planned the study and CS wrote the manuscript. VE, MLL, LG, EG and DC provided important intellectual content and commented on the drafts of the protocol and the present manuscript. All authors read and approved the final manuscript.

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The authors declare that they have no competing interests.

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Additional files

Additional file 1:.

Search strategies. Search strategies performed in MEDLINE and Embase. (DOCX 157 kb)

Additional file 2:

PRISMA chart. (DOCX 283 kb)

Additional file 3:

PRISMA checklist. (DOCX 31 kb)

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Sirois, C., Laroche, ML., Guénette, L. et al. Polypharmacy in multimorbid older adults: protocol for a systematic review. Syst Rev 6 , 104 (2017). https://doi.org/10.1186/s13643-017-0492-9

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Received : 12 October 2016

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Published : 19 May 2017

DOI : https://doi.org/10.1186/s13643-017-0492-9

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