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Tools to measure barriers to medication management capacity in older adults: a scoping review

BMC Geriatrics volume 24, Article number: 285 (2024) Cite this article

Abstract

Background

Medication management capacity is a crucial component of medication adherence, particularly among older adults. Various factors, including physical abilities, cognitive functions, sensory capabilities, motivational, and environmental factors, influence older adults' ability to manage medications. It is, therefore, crucial to identify appropriate tools that allow clinicians to determine which factors may impact medication management capacity and, consequently, nonadherence to medications.

Purpose

1)To identify tools that measure physical, cognitive, sensory (vision, hearing, touch), motivational, and environmental barriers to medication self-management in older adults, and 2) to understand the extent to which these tools assess various barriers.

Methods

The scoping review was conducted using Arksey and O'Malley's scoping review framework and the PRISMA Extension for Scoping Reviews checklist. In June 2022, the relevant literature was identified by searching PubMed (MEDLINE), Ovid Embase, Ovid IPA, EBSCOhost CINAHL, APA PsycINFO, and Scopus.

Results and discussion

In total, 7235 studies were identified. Following the removal of duplicates, 4607 articles were screened by title and abstract, of which 4253 did not meet the inclusion criteria. Three reviewers reviewed the full texts of the remaining 354 articles; among them, 41 articles, 4 theses and 1 conference abstract met the inclusion criteria. From the included studies, 44 tools were identified that measured a combination of physical, cognitive, sensory, motivational, and environmental barriers (n=19) or only cognition (n=13), vision (n=5), environmental factors (n=3), auditory (n=1), and motivational factors (n=1). The review also examined the psychometric properties of the identified tools and found that most of them had reported validity and reliability data. Several tools have demonstrated promise in assessing a combination of barriers with validity and reliability. These tools include the Self-Medication Assessment Tool (SMAT), ManageMed Screening (MMS), Self-Medication Risk Assessment Tool (RAT), HOME-Rx revised, and Medication Management Ability Assessment (MMAA).

Conclusion

This scoping review identified 44 validated tools to measure various challenges that older adults encounter with medication management. However, no tool measures all five barriers (physical, cognitive, sensory, motivational, and environmental) to medication-taking at home. Therefore, utilizing a combination of tools would be most appropriate to measure these different aspects comprehensively. Further research is needed to develop a new comprehensive tool that simultaneously measures various barriers to medication self-management.

Peer Review reports

Introduction

In individuals aged 60 years and above, there is a higher prevalence of multiple chronic conditions, including diabetes, hypertension, heart disease, stroke, and cancer, compared to younger age groups [1]. According to a report by the National Council on Aging, “approximately 92% of older adults have at least one chronic disease, and 77% have at least two chronic diseases” [2]. These chronic diseases, along with associated disabilities, can result in complex medication regimens and an increased risk of functional impairment, presenting significant challenges in medication management capacity [3]. Additionally, the burden of handling medications, especially within the context of multi-morbidity and complex medications regimens, introduces an added layer of complexity to the day-to-day lives of older people, and these burdens can also influence their capacity to manage medications [4, 5].

Medication management capacity (MMC) refers to the “cognitive and functional ability to comply with a medication regimen, when it is the individual’s wish or desire to follow a medication regimen as prescribed” [6]. MMC encompasses factors such as understanding the purpose and importance of medications, being able to remember and follow prescribed dosages and administration instructions and having the necessary skills to handle medication containers and administer medications correctly [6]. Medication management capacity is closely linked to adherence [7]. Medication adherence refers to “the extent to which a person’s medication‐taking behavior corresponds with agreed-upon treatment recommendations from a healthcare provider” [8, 9]. If an individual lacks the necessary cognitive or functional abilities to manage their medications effectively, it can result in unintentional nonadherence [6, 7, 9]. Compared to younger patient groups, concerns regarding medication management capacity are particularly significant among older adults [10]. According to the World Health Organization (WHO), approximately 46% of people over the age of 60 suffer from some form of disability, with visual impairment, hearing impairment, cognitive limitations, and osteoarthritis being the most common causes [11]. These limitations can impair the ability of older individuals to manage complex medications and, as a consequence, restrict their independence [11].

The MOLD-US framework, with its focus on physical, cognitive, sensory, and motivational barriers affecting the usability of mobile health applications in older adults, serves as a valuable guide for understanding and categorizing challenges in medication self-management [12]. By considering impairments associated with aging and their consequences, this framework addresses the challenges involved in medication management in older adults [12]. Physical impairments associated with aging include a decline in grip strength, dexterity, coordination, and mobility of the hands and arms [12]. Research on rheumatoid arthritis patients revealed that hand function deterioration associated with arthritis hindered their ability to open tablet containers and unit dose packs [13]. Aging also leads to a loss of certain cognitive abilities, including processing speed as well as certain memory, language, visuospatial, and executive functions [14, 15]. In addition, certain conditions, such as dementia, can worsen cognitive decline, which ultimately reduces medication management ability [14, 15]. Visual functions that decline with age include the ability to resolve detail, focus on close objects, discriminate between colors, detect contrast, adapt to darker conditions, and increase susceptibility to glare [16, 17]. A study involving 156 patients above the age of 65 compared issues related to self-management of medications among older individuals with and without visual impairment [16]. Despite using visual aids, approximately 29% of individuals with visual impairment required assistance managing their medications [16]. Moreover, age-related eye diseases such as cataracts, age-related macular degeneration, glaucoma and diabetic retinopathy can also deteriorate the vision functions of older individuals [17]. Motivational challenges that older adults encounter with medication self-management at home include inadequate knowledge about medications and the use of adherence technologies (health literacy and technology literacy), low self-efficacy, lack of confidence in taking medications properly, and integration of medication management during daily activities [12]. Additionally, research suggests that feedback from care partners and the environment in the home can impact the ability of older adults to self-administer medication [18, 19]. Therefore, when assessing various barriers to medication-taking, it is important to take into account a variety of environmental factors, including social factors such as support from family and caregivers and home environment [19, 20].

Several studies have emphasized the importance of assessing the functional ability of older adults to medication management in clinical practice as it serves as a guiding factor for planning, applying, and monitoring interventions aimed at optimizing medication management, allowing healthcare professionals to tailor strategies to individual needs and challenges [21,22,23,24]. However, despite the significance of this assessment, standardized evaluations of functional ability in medication management or medication self-management are not routinely performed in clinical settings [24]. Often, judgments regarding medication management ability rely on the clinician's intuition or reports provided by the patient or caregiver, which have limitations in terms of knowledge, insight, and objectivity [21]. Instruments that measure instrumental activities of daily living and medication adherence are sometimes used to assess medication management capacity, but they are insufficient for evaluating the specific skills required for independent medication management [21].

A number of instruments have been developed to assess an individual's functional and cognitive capacity to manage medications [22,23,24,25]. Drug Regimen Unassisted Grading Scale (DRUGS), Medication Management Instrument for Deficiencies in the Elderly (MedMaIDE), the Hopkins Medication Schedule (HMS), and the Medication Management Ability Assessment (MMAA) are the tools most recommended by various reviewers based on the medication management skills measured, administration time, scoring scale, type of medication regimen used, and psychometric properties [21,22,23,24]. It is important to note that while various tools exist, most are designed to identify cognitive and physical barriers to successful medication administration, and none are known to address all barriers to medication management. [21,22,23]. Furthermore, considering that motivational and environmental factors significantly influence an individual's medication-taking behavior, it is crucial to incorporate these factors when assessing medication management capacity [19, 26]. The integration of these diverse elements into a single tool enables healthcare professionals to acquire a comprehensive overview of an individual's medication management capacity. This comprehensive assessment facilitates targeted interventions that consider the interplay of physical, cognitive, sensory, motivational and environmental factors, potentially result in more effective support and strategies to enhance medication management.

This review aims 1) to identify tools that measure physical, cognitive, sensory, environmental, and motivational barriers to medication self-management in older adults, and 2) to understand the extent to which these tools assess various barriers Although previous reviews have been conducted, this review aims to include any new tools that have emerged since then and to consider a broader range of barriers, including physical, cognitive, sensory, motivational, and environmental factors. By synthesizing the existing evidence and offering a consolidated resource, we aim to assist healthcare professionals in selecting appropriate tools for assessing medication management capacity in older adults and contribute to the advancement of knowledge in this field.

Methodology

This scoping review was informed by the guidance provided by the Arksey and O’Malley scoping study framework and the PRISMA Extension for Scoping Reviews checklist [27, 28]. Based on the direction from these two sources, the scoping review included the following stages: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, and (5) summarizing and reporting the results.

Stage 1. Identifying the research question

The research question was as follows: Which tools exist to measure physical, cognitive, sensory, environmental, and motivational barriers to medication taking in older adults?

For this study, we define "tools" as instruments, scales, or assessment methods specifically designed to measure, evaluate, or assess various factors, including physical abilities, cognitive functions, sensory capabilities, motivational factors, and environmental factors that can influence an older adult's capacity to manage medications.

The MOLD-US framework developed to evaluate barriers of older adults influencing usability of mobile health applications was used in this scoping review to guide the identification and categorization of barriers to medication taking in older adults [12]. Even though its primary purpose may differ, the framework allowed us to categorize the diverse barriers impacting older adults' medication self-management in a comprehensive manner as physical, cognitive, sensory, and motivational barriers. In addition to these barriers, we aimed to capture the broader contextual factors, including environmental factors such as social support and home environment (e.g., counter space, adequate lighting), that may influence medication-taking among older adults [18,19,20].

Stage 2. Identifying relevant studies

Relevant articles were found by using a thorough search strategy consisting of both medical subject headings and keywords in 6 databases: PubMed (MEDLINE), Ovid Embase, Ovid International Pharmaceutical Abstracts, EBSCOhost CINAHL, APA PsycINFO, and Scopus. An experienced medical librarian (CC) constructed the database search strategies and conducted the search with input from the team. The search strategies contained synonyms for the following search concepts: medication, self-management, tools, functional impairment (e.g., impaired hearing, vision) and older adults. In each database, all keywords were limited to the title and abstract fields. All search strategy results were limited to the English language and the date range of 2002-2022. The final search strategies were run in each database on June 20th, 2022, and all results were exported to EndNote 20 (Clarivate Analytics, 20.2.1) for duplicate removal. Supplemental file 1 contains the full search strategy utilized in each database. After duplicate removal, the remaining results were exported into Covidence (Veritas Health Innovation, 2022) for screening.

Stage 3. Study selection

Two team members (BB and HP) initially independently screened the titles and abstracts of 460 articles (10% of citations retrieved) based on the predetermined inclusion and exclusion criteria. The inter-rater reliability between the two researchers was determined (the Kappa coefficient was found to be 0.88). The remaining publications were screened by a single reviewer (BB) in view of this strong inter-rater reliability. Full-text screening of eligible studies was conducted by three team members (BB, AM, KP). One reviewer (BB) screened all the eligible studies, and the other two reviewers (AM, KP) screened 50% of the studies each. The bibliographies of the pertinent studies were also screened for additional relevant studies. Studies were included if they were (1) conducted in participants with a mean age of ≥60 years, (2) introduced or proposed tools designed to examine any of the physical, cognitive, motivational, and environmental barriers related to medication taking, or tools to assess functional decline/capacity/limitation/independence/disability related to medication-taking, (3) tools for which psychometric evaluation (at least one of reliability, content validity or construct validity) is available, (4) published between 2002 and 2022, (5) published in the English language, and (6) performed in the outpatient setting or after hospital discharge. The exclusion criteria were as follows: (1) studies performed in inpatients or assisted living residents, (2) editorials, comments, letters to the editor, guidelines, case series and case reports, (3) studies that reported on condition-specific tools (designed to be used in specific diseases only), (4) tools introduced to measure domains other than barriers to medication management, such as self-care or medication adherence, and (5) studies measuring physical, cognitive, sensory, motivational, and environmental barriers, but not related to medication-taking. Disagreements among the three reviewers were resolved through discussion and consensus. Where consensus was not achieved, a fourth team member (SA) was invited to assist with resolving the disagreement.

Stage 4. Charting the data

Data abstraction from the included studies was completed using a Microsoft® Excel® (Office 365 Version 1906) spreadsheet. The following data were abstracted for each included study: title, author, year of publication, journal, country, age and gender of participants, sample size, study objective, study design, study duration, study setting, inclusion criteria, exclusion criteria, assessment tools mentioned, and main outcomes. For the identified tools, the following data were abstracted: purpose, administration time, type of instrument (performance-based/self-reported), type of medication regimen used, barriers assessed, and psychometric properties (validity & reliability). Two reviewers (BB, RS) abstracted data from eligible studies, and the accuracy of the abstracted data was verified by two additional reviewers (AM, KP).

STAGE 5: Summarizing and reporting the results

The general characteristics of the studies and properties of the tools were collected and summarized. The results were then categorized and summarized based on the type of tool, barriers assessed, medication management skills assessed, and psychometric properties.

Results

A total of 7235 studies were identified. After removing duplicates, two reviewers screened 4607 articles by title and abstract, of which 4253 did not meet the inclusion criteria. Therefore, 354 articles were included for full-text review. Of these, 39 articles, four theses, one conference abstract, and two articles identified from the manual search of bibliographies met the inclusion criteria. In the 46 papers included, 44 tools measuring various barriers to medication management capacity were identified. The flow chart in Figure 1 illustrates the screening process.

Fig 1
figure 1

PRISMA flow diagram

Full size image

Study Characteristics

Publication rates varied across decades, with sixteen articles published from 2002 to 2012 and thirty from 2013 to 2022. More than half of the studies (n=25) were conducted in the United States, 13 in Europe, 4 in Asia, 2 in Australia, and 2 in Canada. A variety of study designs were used: cross-sectional (n=30), pilot study (n=5), cohort study (n=2), scoping review (n=2), validity study (n=3), case‒control study (n=1), mixed method study (n=1), systematic review (n=1), and randomized controlled trial (n=1). Most of the studies included both males and females, except for one study conducted on community-dwelling women aged 70 to 80 years. Twelve studies targeted older adults with specific conditions (coronary heart disease, Parkinson’s disease, chronic obstructive pulmonary disease, hypertension, age-related macular degeneration), one study recruited pharmacists and pharmacy students to evaluate the validity of a medication assessment tool for older adults, and the remaining studies targeted community-dwelling older adults. A detailed description of the studies included is summarized in Table 1.

Table 1 Study characteristics
Full size table

Tool properties

Among the 44 tools, two broad categories were identified: performance-based (n=30) and self-report measures (n=14). Performance-based measures involved asking older adults to complete different tasks related to medication management or different instrumental activity tasks, while self-reported measures are based on subjective information provided by individuals as part of surveys and offer insights into aspects of their own lives that are not directly observable. Of the included tools, 19 measured a combination of various barriers, while others assessed only cognition (n=12), vision (n=5), motivational (n=4), environmental (social support) (n=3), or auditory (n=1) factors.

A detailed description of the tools identified is summarized in Tables 2 and Table 3 illustrates the type and extent of barriers assessed by these tools.

Table 2 Tool properties
Full size table

Psychometric properties

There was at least one validity (content and construct) and one reliability (inter-rater, test-retest, internal consistency) data reported for most of the tools we reviewed. For MedTake, Medi-cog, and MTS, only validity data (both content and construct) were reported. Construct validity was shown through association with cognitive function and correctly filled pills for MTS and Medi-cog. The MedTake test was validated for construct validity using cognitive function (MMSE) and educational level. For the ETDRS eye chart, the psychometric properties were measured in terms of accuracy (-0.12*0.14) and test-retest variability (-0.23*0.17). Sensitivity - 100% (95% CI: 96-100) and specificity - 87% (95% CI: 80-92) were reported for the whisper test as psychometric measures. Table 2 contains a detailed description of the psychometric properties of each tool identified.

Discussion

For older adults, managing multiple health conditions with complex medication regimens can be quite challenging, potentially affecting their quality of life [4]. Assessment and identification of specific limitations in medication management capacity can promote a deeper understanding amongst healthcare providers of how these challenges influence adherence to treatment as well as implementation of appropriate strategies to mitigate the impact on adherence [22,23,24,25, 29, 49, 56, 99]. We aimed to identify a tool that comprehensively evaluates various barriers to medication self-management, including physical, cognitive, sensory, motivational, and environmental domains. Although we found 44 tools that assess these barriers either separately or together, no single tool collectively addressed all five barriers.

Assessment domains and promising tools

There are significant differences in the type and extent to which physical, cognitive, sensory, motivational, and environmental barriers are assessed in the tools we identified. While there are several instruments that exist to measure various aspects of physical and cognitive barriers, sensory components such as color vision, dark adaptation, and auditory factors, along with socio-economic factors including cost considerations and the home environment, are less frequently or thoroughly addressed. Instruments such as the Self-medication Assessment Tool (SMAT), ManageMed Screening (MMS), Self-medication Risk Assessment Tool (RAT), HOME-Rx revised, Medication Management Ability Assessment (MMAA), Medication Management Instrument for Deficiencies in the Elderly (MedMaIDE), and MedTake test stand out for their degree of assessment, each assessing between 11 to 16 of the 29 components [20, 29, 34, 35, 49, 56, 59, 61, 99]. However, it is important to highlight that the tools predominantly assess physical and cognitive domains. Previous studies by Farris and Phillips, Elliot and Marriott, and Badawoud et al. have also confirmed the effectiveness of tools like DRUGS, MedMaIDE, MedTake test, MMAA, and HMS in determining physical and cognitive abilities for independent medication management [21, 23, 24].

This focus on physical and cognitive barriers underscores a significant gap in the assessment of other critical domains, especially sensory and socio-economic factors. Sensory components, such as visual and auditory factors, are essential for accurately identifying and managing medications, yet they are often not considered in current assessment tools. Socio-economic factors, including affordability and the suitability of the home environment for medication management, also play a significant role in an individual's ability to adhere to medication regimens but are similarly under addressed. The limited emphasis given to sensory, motivational and environmental barriers highlights the necessity for further research.

Table 3 Tools and type of barriers assessed
Full size table

Psychometric properties of assessment tools

It is important to establish psychometric properties of tools as they highlight each tool’s validity and reliability in clinical and research settings. If a tool lacks sufficient validity , the outcomes derived from the use of the tool cannot be confidently relied upon. Our review highlights a mixed picture regarding the psychometric properties of these tools. Instruments, such as the Self-medication Assessment Tool (SMAT) and Medication Management Ability Assessment (MMAA), demonstrate good psychometric properties through the assessment of their content and construct validity and with high scores in various reliability measures such as inter-rater reliability, test-retest reliability, and internal consistency [34, 49, 56]. However, other tools like the Cognitive Screen for Medication Self-Management (CSMS) showed potential issues with reliability, indicated by its low internal consistency scores [30]. Similarly, MedTake test only has only validity measures with a lack of various reliability measurements [53]. This variability indicates that while many tools have undergone some level of psychometric evaluation, there remains a gap in the comprehensive validation of these instruments. Future research should focus on addressing these gaps, particularly by expanding validation studies to include larger and more diverse populations, examining test-retest reliability, inter-rater reliability, and internal consistency more consistently, and exploring the practical implications of these tools in everyday clinical use.

Clinical utility and implementation challenges

While identifying tools that are comprehensive is important, implementing such tools in clinical settings presents its own set of challenges. Most of the promising tools we identified are performance-based assessments, which healthcare professionals are responsible for administering. However, implementing these assessments in busy clinical environments can be challenging. Given that the administration times for these tools vary widely, from 5 minutes to 60 minutes, integrating them effectively into busy clinical workflows can be a hindrance to implementation. This is especially true when considering the average physician visit lasts approximately 15.7 minutes [100]. Consequently, use of comprehensive tools may be impractical within a clinical setting. However, clinicians can make use of these findings to selectively determine which tools are most suitable for the specific needs of the patients under their care.

Limitations and real-world applicability of assessments

While the measurement of MMC provides valuable insights into an individual's ability to handle medications effectively, it's essential to recognize its limitations [20,21,22,23, 30, 34, 49, 56]. This assessment doesn't offer a comprehensive prediction of real-world medication-taking behavior [101, 102]. Medication non-adherence can be intentional or unintentional [6,7,8,9]. Intentional medication non-adherence, where individuals may consciously choose to deviate from prescribed regimens due to personal beliefs, concerns, or experiences with side effects, is not examined by these measurements [103]. However, incorporating MMC assessments into routine clinical practice allows clinicians to identify those who are unintentionally non-adherent and may benefit from person-specific assistance in managing their medications [21,22,23,24]. Such tailored interventions include patient education, simplified medication regimens, cognitive-behavioural therapy, and technology-based solutions to help manage medications [7]. Addressing barriers to MMC in older adults has the potential for long-term health benefits by improving overall well-being, reducing hospitalizations and complications associated with chronic conditions, while concurrently addressing the burden associated with managing medications [1, 3,4,5, 11, 21, 24].

Strengths and limitations

Strengths

One of the main strengths of this scoping review is the involvement of patient partners in the full text review and data extraction stages. Their valuable input not only provided insights into the needs and concerns of older adults regarding medication self-management, but also contributed to the identification of tools that were considered crucial for measuring diverse medication management components, drawing upon their personal lived experience with managing medications. Furthermore, by comprehensively identifying and comparing various tools that measure barriers to MMC, this scoping review contributes to the advancement of knowledge in the field of medication management in older adults. It serves as a reference point healthcare professionals can use for selecting tools to assess their patient's MMC. Researchers can use this information to select appropriate tools for their studies and to develop new tools that address specific barriers to MMC.

Limitations

A limitation of this study is that it was limited to English language studies published between 2002 and 2022. There may be important studies that were excluded from this study due to language and time restrictions. Future research should consider including studies published in other languages to increase the comprehensiveness of the review. Additionally, although we searched six different databases using well-constructed search strategies, it is still possible that relevant studies were missed.

Conclusion

This scoping review identified several validated tools to measure various challenges that older adults encounter with medication management. However, no one tool measures all five barriers (physical, cognitive, sensory, motivational, and environmental) to medication-taking at home. Therefore, a combination of tools is recommended to comprehensively measure these different aspects. The study's findings can aid healthcare professionals and researchers in selecting appropriate tools for assessing medication management capacity in older adults and enhancing the quality of care for this population. Nonetheless, despite the valuable insights from this review, the development of a comprehensive tool that addresses all these barriers is still necessary. Further research and development in this area is needed to provide healthcare professionals with a more efficient and holistic approach to assess medication management capacity.

Availability of data and materials

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

Abbreviations

CSMS:

Cognitive Screen for Medication Self-Management

CVLT:

California Verbal Learning Test

CHAS:

Comprehensive Health Activities Scale

DRUGS:

Drug Regimen Unassisted Grading Scale

DLTV:

Daily Living Tasks associated with Vision

DSB:

Digit Span Backward

ETDRS:

Early Treatment Diabetic Retinopathy Study eye chart

FCCHL:

Functional, Communicative and Critical Health Literacy scale

FOME:

Fuld Object-Memory Evaluation

HMS:

Hopkins Medication Schedule

LTMBSES:

Long-Term Medication Behavior Self-Efficacy Scale

MMAA:

Medication Management Ability Assessment

MMC:

Medication Management Capacity

MCI:

Mild Cognitive Impairment

MMSE:

Mini-Mental State Examination

MTS:

Medication-Transfer screen

MedMaIDE:

Medication Management Instrument for Deficiencies in the Elderly

MoCA:

Montreal Cognitive Assessment

MSSS:

Medication-Specific Social Support Questionnaire

MeDS:

Measure of Drug Self-Management

MSPSS:

Multidimensional Scale of Perceived Social Support

MPED:

Martin and Park Environmental Demands Questionnaire

MMS:

ManageMed Screening

MASES:

Medication Administration Self-Efficacy Scale

NVS:

The Newest Vital Sign

NEI VFQ-25:

National Eye Institute Visual Function Questionnaire-25

PASS:

Performance Assessment of Self-care Skills

PSS-Fr & PSS-Fa:

Perceived Social Support from Friends and the Perceived Social Support from Family

PR test:

Pelli–Robson test

REALM:

Rapid Estimate of Adult Literacy in Medicine

RAT:

Self-medication Risk Assessment Tool

S-TOFHLA:

Short Test of Functional Health Literacy in Adults

SEAMS:

Self-Efficacy for Appropriate Medication Use Scale

SMAT:

Self-Medication Assessment Tool

SBT:

Short Blessed Test

TMT:

Trail-Making Test

TOFHLA-R:

Test of Functional Health Literacy in Adults

WCST:

Wisconsin Card Sorting Test

WHO:

World Health Organization

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Funding

The project is funded by National Research Council of Canada (NRC) and Canadian Institutes of Health Research (CIHR - Funding Reference Number (FRN)-184372) by the Government of Canada.

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Authors and Affiliations

  1. School of Pharmacy, University of Waterloo, Waterloo, ON, Canada

    Bincy Baby, Hawa Patel, Rishabh Sharma, Caitlin Carter, Feng Chang, Sara Abu Fadaleh & Tejal Patel

  2. Patient Advisor’s Network, Toronto, ON, Canada

    Annette McKinnon & Kirk Patterson

  3. National Research Council Canada, Ottawa, ON, Canada

    Ryan Griffin

  4. Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada

    Catherine Burns

  5. Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada

    Sara JT Guilcher

  6. Department of Family Medicine, McMaster University, Hamilton, Canada

    Linda Lee

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BB and TP directed and contributed to all aspects of this research. CC developed the search strategy and conducted search in various databases. HP and SF contributed to title and abstract screening. AM, KP and RS contributed to full text screening and data extraction. All authors read and approved the final manuscript.

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Correspondence to Tejal Patel.

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Baby, B., McKinnon, A., Patterson, K. et al. Tools to measure barriers to medication management capacity in older adults: a scoping review. BMC Geriatr 24, 285 (2024). https://doi.org/10.1186/s12877-024-04893-7

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