Prevalence And Definitions of Polypharmacy: A Systematic Review And Meta-Analysis

doi:10.21203/rs.3.rs-1096695/v1

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Prevalence And Definitions of Polypharmacy: A Systematic Review And Meta-Analysis

https://doi.org/10.21203/rs.3.rs-1096695/v1

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INTRODUCTION: Polypharmacy is common associated with several adverse health outcomes. There are currently no systematic reviews or meta-analyses on the prevalence of polypharmacy and associated factors. We aimed to identify population-based observational studies reporting on the prevalence of polypharmacy and factors associated with polypharmacy.

METHODS: MEDLINE, EMBASE, and Cochrane databases with no restriction on date. Population-based observational studies with cross-sectional, case-control, or cohort designs using administrative databases or registries to define or measure polypharmacy among individuals over 19. Using a standardized form, two reviewers independently extracted study characteristics, a crude prevalence rate of polypharmacy and its standard error with 95% confidence intervals (CIs). The risk of bias and quality of studies was assessed using the Newcastle-Ottawa Scale. The main outcome was the prevalence of polypharmacy and factors associated with polypharmacy. Using a random-effects model, pooled prevalence estimates with 95% CI was reported. Subgroup analysis was performed if significant heterogeneity was explored. Meta-regression analysis was conducted to predict polypharmacy prevalence.

RESULTS: 106 full-text articles were identifies using 21 unique terms with 138 descriptive definitions of polypharmacy. The pooled estimated prevalence polypharmacy in studies reporting all medication classes was 37% (95% CI: 31%-43%). Differences in polypharmacy prevalence were reported for studies using different numerical threshold and polypharmacy was also associated with study year in meta-regression. Sex, study geography, study design and study setting were not associated with differences in polypharmacy prevalence.

DISCUSSION: Our review highlights that polypharmacy is common particularly among older adults and those in inpatient settings. A variety of definitions are used to define polypharmacy and differences in polypharmacy definitions may have implications for understanding the burden or polypharmacy and outcomes associated with polypharmacy.

CONCLUSIONS AND IMPLICATIONS: Clinicians should be aware of the common occurrence of polypharmacy in all populations and undertake efforts to minimize inappropriate polypharmacy whenever possible.

Geriatrics & Gerontology

polypharmacy

multiple medication prescribing

population-based study

administrative database.

While medications are often necessary to manage acute and chronic health conditions, polypharmacy is a significant problem related to prescribing medications. Polypharmacy refers to a situation where an individual uses multiple medications simultaneously. The World Health Organization (WHO) defines polypharmacy as “the administration of many drugs at the same time or the administration of an excessive number of drugs “.[1] While there is no consensus on the medication threshold and means of measurement, polypharmacy is often commonly defined as concomitant use of 5 or more medications.[1, 2]

Prescribing multiple medications is often clinically required (appropriate polypharmacy). However, exposure to multiple medicines may lead to harm or the ongoing use of medications no longer indicated (inappropriate polypharmacy).[2, 3] Polypharmacy can be associated with numerous poor health outcomes, especially among older adults with multimorbidity, including an increased risk of death, falls, drug interactions, non-adherence, and hospitalization.[2, 3] Polypharmacy has become a substantial health care burden. It is associated with an annual estimated US $50 billion costs, which is increasing over time.[4] To avoid such cost and prevent adverse events, identification of individuals receiving inappropriate polypharmacy is essential.[3]

Some research indicates that inappropriate polypharmacy can affect up to one-third of the population under study.[4] However, there is no comprehensive and global definition of polypharmacy and factors associated with polypharmacy have not been well-described. We conducted this systematic review and meta-analysis of population-based observational studies to estimate polypharmacy prevalence and identify factors associated with polypharmacy. We also described the terminology and definitions used to define polypharmacy in the research literature.

We registered our review protocol on PROSPERO (CRD42019130998). This systematic review is written following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.[5]

Eligibility Criteria

We included population-based observational studies with cross-sectional, case-control, or cohort designs using administrative databases or registries to define or measure polypharmacy among individuals over 19. We excluded studies that focused on children and adolescents (aged 0-19) and duplicate articles and non-original studies (e.g. editorials). We included all publication dates and limited articles to the English language only. The primary study objective outcome was to estimate polypharmacy prevalence and identify factors associated with polypharmacy. Our secondary objectives were to identify definitions and measurements of polypharmacy using administrative databases or registries.

Search Strategy and Study Selection

We developed a search strategy in consultation with a librarian specializing in health databases. We searched EMBASE, MEDLINE, and Cochrane Library from inception to March 30, 2019, using individualized search strategies prepared for each database. We limited results to studies conducted in humans and available in the English language. We used exploded MeSH terms (e.g. polypharmacy, polytherapy, poly medication, poly prescription, multi medication, multi prescription, multidrug therapy, multiple drug treatment, multiple pharmacotherapies, administrative data, databases, registries) and combinations of relevant keywords and their variants by grouping polypharmacy and administrative database associated terms. The MEDLINE search strategy is presented in online supplementary materials (Appendix 1). We also hand-searched for additional publications using a reference list of relevant papers. Reference management and citation screening were performed using EndNote ^TM (V.X7).[6] Using a two-step process for study selection, two of three reviewers (MD, LM) independently screened each citation's title and abstract to determine whether a study met the broad inclusion criteria. The full texts of all relevant citations were retrieved for formal review. Two reviewers (MD, LM) independently assessed the full-text reports. Conflicts were resolved by discussion between reviewers.

Data Extraction and Management

We used a standardized and piloted data extraction form. Reviewers (MD, LM) extracted data independently, using a standardized form, with conflicts resolved through consensus. The extracted study characteristics were bibliographic references, country, year of publication, sample size, setting, study design, age and sex. Appendix 2 illustrates the baseline data extracted from each study. Other data items extracted from the retrieved articles included a crude prevalence rate of polypharmacy and its standard error, 95% confidence intervals (CIs), and polypharmacy definitions. Definitions were broken down based on medication threshold, duration of therapy, overlapping days, measurement indicators, and type of drug assessment. Additional related to studies are provided in Appendix 3.

Quality Assessment

We assessed the risk of bias and quality of the included studies using the Newcastle-Ottawa Scale.[7] This tool consists of 7 to 8 domains depending on the type of study design; each domain is rated ’low risk,’ ‘unclear risk,’ or ‘high risk.’ Studies were categorized based on total scores as either high quality (total scores ≥ 7) or low quality (total score <7).

Data Analysis

The included studies' data were summarized in frequency tables and analyzed using RStudio (version 3.6.1). Meta-analyses were performed using random effects. Using inverse variance, we expressed pooled continuous data as prevalence estimates and reported 95% CI. Heterogeneity was determined using the I-squared (I²) statistic (low <25%, moderate 25–50%, high > 50%).[8] If significant heterogeneity was suspected, further analysis, including subgroup analysis, was conducted. Publication bias was assessed for the prevalence of polypharmacy using funnel plot techniques as appropriate, given the known limitations of these methods.[9] We also used meta-regression analysis to predict polypharmacy prevalence using the identified factors in a linear regression model.

Subgroup Analyses

We restricted subgroup analyses to situations where a minimum of 4 studies were available for each categorical study-level variable.[10] A total of nine subgroup analyses were planned based on: mean age (< 65 vs ≥ 65); sex of participants (male vs female), location of study (North America vs elsewhere), health care setting (inpatient vs outpatient vs community), study design (cross-sectional vs case-control vs cohort), methodological quality (low vs high); medication threshold (2 vs 5), measurement indicator (simultaneous vs cumulative).

Of 525 unique citations with available abstracts, we retrieved and reviewed 179 full texts. Of these, 106 studies met inclusion criteria (Appendix 4). The studies were published from 1989 to 2019. Figure 1 depicts a PRISMA flowchart of citations reviewed. While two studies were multicentre, most studies were conducted in Europe (n=59), followed by Asia (n=21), North America (n=20), Australia (n=2), and South America (n=2). The healthcare setting was specified in 50 studies (49.1%) including community (n=15), inpatient (n=15), outpatient (n=13) or a combination of these settings (n=7). Nearly 75% percent of the studies were cross-sectional (n=80). The studies included a different number of participants varying from 248 to 12,301,537 individuals. The mean age of participants ranged from 26 to 87 years old. Studies were overall adjudicated to be at low risk of bias or high quality (101 studies, 95.3%), and five studies were judged to be at high risk of bias or low quality. The details of the study characteristics varied across studies (Appendix 2).

Definitions of Polypharmacy

Fifty-seven studies used the term polypharmacy (54%) followed by polytherapy (n=18 studies, 17%), co-prescribing (2 studies,1.9%), multiple medication use (1 study, 0.9%), concurrent medication (1 study, 0.9%), poly medication (1 study, 0.9%), concomitant use (1 study, 0.9%) and comedication (1 study, 0.9%) (Appendix 3). Out of the 106 identified articles, 96 (90.6%) included descriptive definitions of polypharmacy resulting in 124 different definitions. All definitions had a numerical component ranging from 2 to 21 medications. A common descriptive definition was identified for polypharmacy with five or more medications (33 studies, 31.1%) followed by polypharmacy with two or more medications (16 studies, 15.1%). The descriptive definition with a medication threshold of 2 (52 studies, 49%) was most frequently used after combining these terms, followed by 5 (39 studies, 37%). All descriptive definitions had a time component, including the duration of therapy, minimum days of overlap, time interval, or assessment frequency. Three studies expressly incorporated an allowable gap of 12, 14, and 15 days in their definitions, and one study reported a grace period of 28 days.

Measuring Polypharmacy

As illustrated in Appendix 3, techniques for operationalizing polypharmacy varied across studies as follows: 59 studies used simultaneous approach (55.7%), 45 used cumulative method (42.5%), and two studies examined a combination of simultaneous, cumulative and continuous approaches (1.9%). In the simultaneous process, the most common sub-indicator was described as the concurrent use of medications with at least one day overlap (47 studies, 44%). Among studies using a cumulative approach, the summing up of different medications taken over 90 days was identified as the most frequent sub-indicator (9 studies, 9%). The timing of polypharmacy assessment also differed across studies. The minimum overlap days required for the simultaneous evaluation ranged from 1 day to 1 year. Studies using the cumulative approach specified a period between 14 to 730 days. The time frame ranged from 180 to 360 days in the continuous approach.

Prevalence of Polypharmacy

Overall Prevalence

Nighty-four studies (100 single reports) contributed raw data for the prevalence of polypharmacy terms. Of the 94 studies, 54 reported on polypharmacy incorporating all medications while the remaining studies only reported polypharmacy related to specific medication classes (e.g. psychotropic polypharmacy, polypharmacy with antiepileptic medications). The pooled estimated prevalence of polypharmacy among the 54 studies reporting on polypharmacy including all medications was 37% (95% CI: 31% - 43%). There was a high degree of heterogeneity observed in this estimate (Tau²=0.0424, Chi²=22194826, df=53, I²=100%) (Figure 2).

Factors Associated with Polypharmacy

Subgroup analyses were undertaken using the 54 studies reporting polypharmacy including all medication classes (Table 1). These subgroup analyses includes sex, numerical threshold (≥2 medications vs ≥5 medications), study geography (North America vs other), study design (cross-sectional, case-control, or cohort) and study setting (community, outpatient and inpatient) or study location (North America vs outside North America). Meta-regression was used to assess the associations between mean age of participants and study year. A summary of the subgroup analyses are provided in Table 1.

Table 1

Summary of Subgroup Analyses of Polypharmacy Prevalence
Variable	Pooled Prevalence (95% CI)	Chi²	df	p-value
Mean age of participants	36 (29,43)	10.88	1	<0.01
Non-elderly (< 65)	25(16,35)	238592.68	20	<0.0001
Elderly (≥ 65)	45 (37,54)	4378199.84	25	<0.0001
Sex	32 (26,39)	0.04	1	0. 85
Male	32 (22,41)	1484546.49,	21	0
Female	33 (23,43)	1754816.42	21	0
Health care setting	40 (32,49)	13.55	2	<0.01
Inpatient	52 (38,66)	36809.71	10	0
Outpatient	47 (33,62)	910219.51	12	0
Community	20 (6,35)	12462667.1	10	0
Numerical cut off for medications	32 (26,38)	2.60	1	0.11
2 medications	29 (27,37)	1615476.66	40	<0.0001
5 medications	37 (30,43)	12019635.95	31	<0.0001
Measurement indicator	33 (28,38)	0.01	2	P = 0.91
Simultaneous	33 (27,40)	9353584.02	50	<0.0001
Cumulative	33 (25,41)	12926693.67	37	<0.0001
Methodological quality	33(28,38)	0.37	1	0.54
High quality	34(29.39)	21220449.4	83	<0.0001
low quality	27 (0,57)	5005.5	4	<0.0001
Country of publication	33 (28.38)	0.15	1	0.70
North America	35 (21,49)	463188.05	17	<0.0001
Non-North America	32 (27,38)	22176139.61	70	<0.0001
Study design	33 (28,38)	9.93	2	<0.01
Cross-sectional	37(31,43)	20427507.22	63	<0.0001
Cohort	23 (9,38)	326083.41	11	<0.0001
Case-control	24 (17,31)	365802.26	12	<0.0001
Chi² = Chi-squared; df = degrees of freedom; Number of reports exceeding the total number of included studies indicates that some studies contributed more raw data at different study periods, age groups or etc.

There was a significant difference in the prevalence of polypharmacy in subgroup analyses for studies using a threshold of ≥ 2 medications (40%, 95% CI: 0% – 47%) when compared to studies using a threshold of ≥ 5 medications (22%, 95% CI: 10% - 35%; P<0.01, Appendix 4). There were no differences in polypharmacy prevalence in subgroup analyses based on sex (Appendix 5), study design (Appendix 6), healthcare setting (Appendix 7) or study location (Appendix 8) (. Meta-regression demonstrated that more recent studies were associated with a higher prevalence of polypharmacy (estimate = 0.0175, p=0.003). Age was not associated with the prevalence of polypharmacy in meta-regression (estimate = -0.0204, p=0.4).

Assessment of Study Quality

The assessment of study quality according to the Newcastle-Ottawa Scale risk of bias assessments for cohort, case-control and cross-sectional studies are provided in Appendix 8. Overall, 10/13 cohort (77%), 11/13 of case-control (85%) and 80/80 cross-sectional studies (100%) were reported to be of high quality.

Publication Bias Assessment

A funnel plot analysis was used to investigate publication bias which did not demonstrate any evidence of publication bias.

Overall, our review indicates that polypharmacy is common (33%) regardless of the definitions used to define it. Older age, inpatient clinical settings and cross-sectional study design were associated with an increased prevalence of polypharmacy. Our review also identified several definitions used to define polypharmacy in the literature. However, the term polypharmacy and a threshold of ≥ 2 medications were the most common definitions found in the literature. However, we did not find that these differing definitions significantly impacted the overall prevalence of polypharmacy in our meta-analysis.

To date, only one systematic review has addressed the multiple definitions of polypharmacy. In their review, Masnoon et al.[3] identified 110 articles that assessed polypharmacy. However, in contrast to our study, Manson et al. did not incorporate a meta-analysis reporting the overall prevalence of polypharmacy or factors associated with polypharmacy. However, these authors highlighted the diverse range of terms used to define polypharmacy, such as minor, major, severe, excessive, hyper, appropriate, persistent, chronic, long term, and pseudo-polypharmacy.[3] Both our review and this previous review highlight the variety of terms used to define polypharmacy and emphasize the need for researchers to create standardized definitions of polypharmacy in the future.

Awareness of polypharmacy is important as it is associated with several adverse outcomes such as the increased risk of drug-drug interactions, hospitalizations, functional decline and mortality.[11–14] When the number of prescribed medicines increases, the number of drug combinations increases exponentially, increasing the risk of adverse drug reactions and drug- drug interactions.[15] Whether polypharmacy is directly causing these outcomes or if it is a marker for frailty or general vulnerability to poor outcomes is not always clear. However, the presence of polypharmacy may be an indicator for clinicians to identify individuals at risk for adverse outcomes who may benefit from preventative health measures and medication review. It has been suggested that different methods of measuring polypharmacy may have different clinical implications in this respect.[1] To reduce adverse events or assess prescription appropriateness, cumulative indicators of polypharmacy may be more useful, whereas simultaneous assessments of polypharmacy may be more helpful for exploring drug-drug interactions. Continuous indicators may be more appropriate for assessing economic costs associated with polypharmacy or chronic disease burden measures. While our review could not incorporate contextual information related to comorbid medical conditions into our assessment of polypharmacy, this information is also critical to understanding if polypharmacy is appropriate or not at an individual level.

Several strategies can be employed to reduce inappropriate prescribing and/or polypharmacy. Medication review (by pharmacists, physicians, or multidisciplinary teams), education and training, and the use of screening tools to identify potentially inappropriate prescribing (e.g. Screening Tool of Older Persons’ Potentially Inappropriate Prescription (STOPP)) have all been found to be effective for reducing polypharmacy in various populations.[16–20] Digital technologies (for example, automatically generated alerts in electronic prescribing programs) have shown promising results in lowering polypharmacy in various settings but have not been widely adopted or investigated.[21] Most of these studies focus on interventions to reduce polypharmacy in settings of greatest concern, such as among older adults or those in residential care settings. However, interventions to reduce polypharmacy vary widely, and the most effective aspects of interventions are still unclear.[20] Deprescribing does not appear to increase adverse outcomes,[22] but whether reducing polypharmacy results in better outcomes is questionable. Studies incorporating clinical outcomes have had mixed findings on the impact on the quality of life, falls, disease-specific outcomes, and hospitalizations.[17–20] Several reviews of interventions to reduce polypharmacy found no effect on all-cause mortality.[16, 18, 22]

Polypharmacy is a complex issue and may differ in appropriateness and implications for medically compromised individuals compared to those who are healthier. In general, polypharmacy needs to be justified and limited as much as possible, especially in older or frail adults. Several strategies have been proposed to reduce polypharmacy, such as deprescribing, reducing the use of unnecessary and inappropriate drugs, and underuse of medications. Still, their clinical significance is not well known.[15] One of the main challenges is to disentangle the effects of removed drugs from reducing the overall burden of medicines that cause no harm.[15] As well, the use of polypharmacy definitions in clinical practice and informatics systems depends on their operationalization and utility.[1] Therefore, the evidence base of the suggested approaches merits more exploration.

This study is a novel and comprehensive review summarising the range of definitions and measurements of polypharmacy and alternative terms available in the literature. This is the first meta-analysis of polypharmacy prevalence. Our study included multiple electronic database searches and hand searching of bibliographies of included studies. This review also provided a high quality of evidence, as 95% of the included studies were at low risk of bias.

Despite these strengths, we acknowledge that this work has some limitations. Most studies operationalized polypharmacy as multiple medication use, so we could not distinguish between appropriate and inappropriate prescriptions. The prevalence estimates in this review were based mainly on raw and dispensing data available in some studies. The included studies did not use a homogenous, evidence-based approach to reporting the proportional rates of polypharmacy. This is likely one reason for the considerable heterogeneity observed across studies. While the observed difference among some subgroups was not significant, the high heterogeneity within those subgroups may reflect the presence of unmeasured factors influencing heterogeneity such as comorbidities, prescription patterns, medication dosage, or genetic factors. We could not obtain enough data from studies to examine these factors' effect on pooled estimates' variations.

The current study reviewed 106 studies[1, 23–127] (See Appendix 3) published from 1989 to 2019 which met inclusion criteria. Regardless of the employed definitions and measure indicators, polypharmacy is a common phenomenon. Given the adverse outcomes associated with polypharmacy, it is essential to understand which definitions of polypharmacy are strongly related to adverse effects and which populations are most susceptible to polypharmacy-related adverse events. Clinicians should routinely assess patients for the presence of polypharmacy and institute measures to reduce inappropriate polypharmacy when it is possible to do so. There were also numerous approaches to define polypharmacy. Still, due to considerable heterogeneity among studies, we failed to identify a comprehensive, clear, and universal definition of polypharmacy and its measurement to address safety and efficacy concerns in the clinical setting. While a numerical cut-off to define polypharmacy may be somewhat arbitrary, it can be a starting point to identify patients at potential risk of developing adverse events due to inappropriate therapy. Depending on the purpose, different measurement indicators of polypharmacy may be required. To make definitions more clinically relevant, adding new components to present comorbidities and treatment appropriateness are recommended.

CI: Confidence Interval; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analysis; STOPP: Screening Tool of Older Persons’ Potentially Inappropriate Prescription

Ethics approval and consent to participate: Not applicable.

Consent for Publication: Not applicable

Availability of data and material: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing Interests: The authors declare they have no competing interests.

Funding: The authors have no sources of funding to declare.

Author Contributions: M.D. and D.P.S contributed to the conception of the study. MD., B.J., A.B and D.P.S contributed to the design of the work. M.D., L.M., B.J, A.B, Z.G, J.K, and D.P.S. contributed to the acquisition, analysis and interpretation of data. M.D. drafted the work and L.M., B.J., A.B, Z.G., J.K. and D.P.S substantively revised it.

Acknowledgements: Not applicable

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AppendicesBMCGeriatricsUpdated.docx
Appendix 1. Search Strategy using Medline Database Appendix 2. Baseline Characteristics of Included Studies Appendix 3. References to Studies Included in Review Appendix 4. Descriptive Definitions and Measurement Indicators of Polypharmacy and Alternative Terms across Studies Appendix 5. Prevalence of Polypharmacy Associated with Different Mean Age of Individuals Appendix 6. Prevalence of Polypharmacy Associated with Different Study Designs Appendix 7. Prevalence of Polypharmacy Associated with Different Health Care Settings Appendix 8. Risk of Bias Summary in Included Studies (n=106)

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Prevalence And Definitions of Polypharmacy: A Systematic Review And Meta-Analysis

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Abstract

Figures

Introduction

Methods

Eligibility Criteria

Search Strategy and Study Selection

Data Extraction and Management

Quality Assessment

Data Analysis

Subgroup Analyses

Results

Definitions of Polypharmacy

Measuring Polypharmacy

Prevalence of Polypharmacy

Overall Prevalence

Factors Associated with Polypharmacy

Assessment of Study Quality

Publication Bias Assessment

Discussion

Conclusion And Implications

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1