Keywords
multimorbidity, medication adherence, study protocol, systematic review
This article is included in the HRB Primary Care CTNI gateway.
multimorbidity, medication adherence, study protocol, systematic review
Multimorbidity has been defined as the presence of two or more chronic conditions in one individual (Fortin et al., 2012). The rising prevalence of multimorbidity can be attributed to improvements in healthcare and the ageing population associated with the epidemiologic transition (Omran, 2005). A 2012 UK study involving over 1 million patients reported that 23.2% had two or more chronic conditions, while this rate increased to 65% when the population considered was restricted to those aged 65–84 years (Barnett et al., 2012). Patients with multimorbidity are placed at increased risk of experiencing fragmented care due to the disease-centric care model currently dominating medical research, education, and practice (Tinetti et al., 2012). Accordingly, synthesising the relevant evidence existing to date is required to guide future research and practice in the context of multimorbidity.
Adherence refers to the extent to which a person’s behaviours correspond with agreed recommendations from their healthcare provider (Haynes et al., 2005). As well as changes to lifestyle behaviours, patients with chronic diseases are often expected to adhere to complex drug regimens (Noël et al., 2007). In the context of multiple conditions, the likelihood of medication non-adherence increases as patients are prescribed more medications (Benner et al., 2009), with associated risks to health outcomes (DiMatteo et al., 2002). Such non-adherence poses potential problems for both patients and health systems, highlighting a need to further investigate the occurrence of medication non-adherence and associated factors in multimorbidity according to existing evidence.
Despite knowledge of the rising prevalence of multimorbidity, much intervention development to enhance medication adherence and reviews of the adherence literature are centred on single-disease populations (Williams et al., 2008). Such a focus is at odds with the rising prevalence of multimorbidity and may lead to an artificial underestimation of the complexity of self-management in chronic disease. One existing systematic review has evaluated medication adherence in older adults with polypharmacy, a phenomenon closely associated with multimorbidity (Zelko et al., 2016). They cite caregiver burden, impaired hearing, poor cognition and greater number of drugs as predictors of non-adherence in that population (Zelko et al., 2016). Nevertheless, it has been noted that while relative risk of multimorbidity increases with age, the absolute prevalence of multimorbidity is higher among adults aged under 65 years (Barnett et al., 2012). Additionally, while multimorbidity and polypharmacy have been branded as “two sides of the same coin” (Sinnott & Bradley, 2015), it has also been noted that the phenomena may be independent of one another depending on the definition and measurement used in individual studies (Nicholson et al., 2019). Therefore, a review of the literature inclusive of all adults with multimorbidity is considered necessary to provide the breadth of understanding required to inform intervention development relevant to the whole population of patients with multimorbidity.
Quantitative studies have reported prevalence rates and predictors of medication non-adherence in adult patients with two or more chronic conditions, however to our knowledge no synthesis of this evidence exists to date. Understanding non-adherence to prescribed medications among patients with multiple chronic conditions will provide insight which goes beyond the single-disease focus currently dominating adherence research. The proposed systematic review aims to identify an evidence base to inform research and practice involving patients with multimorbidity, who comprise a large proportion of the population living with chronic disease.
The primary objective of the review is to systematically examine existing evidence relating to prevalence of medication non-adherence and predictors of medication non-adherence among patients with multimorbidity.
The review will specifically address three research questions:
1. What is the prevalence of medication non-adherence among patients with multimorbidity?
2. What are the clinical and psychosocial predictors of medication non-adherence among patients with multimorbidity?
3. Is the method of medication adherence measurement a moderator of non-adherence estimates in multimorbidity?
The study is prospectively registered in PROSPERO, the International Prospective Register of Systematic Reviews (CRD42019133849).
The study will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) (Moher et al., 2009). Each stage of the study selection process will be reported, from title and abstract screening through to selection of full-text articles for inclusion in the review. Reasons for exclusion during full-text review will be reported. A PRISMA flow diagram will be generated to outline each stage of this process. The present systematic review protocol is reported according to PRISMA-P guidelines (Moher et al., 2015) (see Reporting guidelines; Foley, 2019). Any amendments to the study protocol will be documented here and in the associated PROSPERO document.
Experimental and non-experimental quantitative studies reporting prevalence of medication non-adherence in people with two or more chronic conditions will be included in the review. Observational studies – including longitudinal and cross-sectional studies – are anticipated to be the most pertinent study type reviewed. Where intervention studies (randomised and non-randomised controlled trials) report prevalence and/or determinants of medication non-adherence, only baseline data will be extracted and used in the review. The presence of multimorbidity (two or more chronic conditions) must be explicit (i.e. part of study aims and/or inclusion criteria) for studies to be included in the review.
Prevalence of medication non-adherence measured using any relevant method, e.g. self-report, pharmacy data, physical tests, etc.
The review will employ the following electronic databases: PsycINFO, PubMed, EMBASE, and CINAHL. Articles considered eligible for inclusion will be available in English and in full-text from January 2009 to April 2019. The search strategy will combine terms relating to adherence and multimorbidity (see Extended data; Foley, 2019). The date range is deemed appropriate considering the scope of adherence prevalence studies conducted in people with two or more chronic conditions since Fortin & colleagues (2012) called for “a more uniform methodology” in multimorbidity research, promoting consistency in how multimorbidity is defined within the literature.
Studies identified from database searching will be exported to Endnote X8® where duplicated references will be identified and excluded using the ‘find duplicates’ function, and then screened manually for outstanding duplicates by listing studies in order of title. Remaining studies will be exported to Covidence review management software for screening. Titles and abstracts will be screened by a single reviewer (LF will screen 50% and RLV will screen 50%). To assess agreement between reviewers, 20% of these records will be cross-checked by the other reviewer (LF, RLV). Full-text articles will be independently screened by two members of the review panel (LF, JL). Reference lists of all included studies will be independently searched by two reviewers for additional relevant articles. Where disagreement arises between reviewers at any stage, a third reviewer (GJM and/or AWM depending on subject expertise required) will be consulted.
Data extraction will be performed by two independent reviewers (LF, JL). A pre-defined data-extraction form will be used (see Extended data; Foley, 2019) to extract the following: country of publication, citation, study aims, study design, study setting, chronic conditions studied, sample size, participant age, participant gender, definition of multimorbidity used (if applicable), definition of medication adherence, measure of medication adherence, prevalence of medication non-adherence (or non-adherence score), predictors of medication non-adherence (if reported), authors’ conclusions. Where disagreement occurs, a third reviewer (GJM) will be consulted. Where reported data are deemed unclear or insufficient, corresponding authors will be contacted by LF for clarification.
Study-level quality appraisal will be conducted for all included studies by two reviewers (LF, JL) using criteria for assessing quality and risk of bias in observational studies (Sanderson et al., 2007). Specifically, criteria relate to appropriateness of source population, inclusion/exclusion criteria, measurement methods, methods to deal with design-specific sources of bias, design and/or analytical methods, use of statistics, and declarations of conflict of interest and/or funding sources. While RCT designs may be included in the proposed systematic review, the observational nature of the aforementioned tool is considered appropriate as only baseline observations will be extracted from RCT studies for review. No studies will be excluded on the basis of quality appraisal.
The I2 statistic will assess heterogeneity, using an alpha level of 0.05 for statistical significance. An I2 value between 50% and 75% indicates high heterogeneity between studies (Higgins & Thompson, 2002).
Where data support quantitative synthesis, a meta-analysis will be conducted using the metaprop function in R (R Core Team, 2019). Study-specific estimates will be pooled to estimate the prevalence of medication non-adherence. A random effects model will be employed to account for between-study heterogeneity (Higgins & Thompson, 2002). To account for asymmetry, the Clopper Pearson method will be used to calculate binomial proportion confidence intervals (Clopper & Pearson, 1934). The effect of each individual study on the overall estimates of non-adherence prevalence will be assessed using sensitivity analyses by serial exclusion.
Where data are sufficient, the following a priori moderator analyses will be performed:
Publication bias will be assessed by producing and inspecting a funnel plot (Egger et al., 1997) and by conducting an Egger test for statistical significance (Sterne et al., 2005).
The systematic review protocol was finalised in March 2019 and the database search was conducted in April 2019. Full-text screening was completed in October 2019. It is anticipated the review will be completed in January 2020.
The review will describe the cumulative evidence relating to medication non-adherence prevalence and relevant predictors among patients with multimorbidity. Understanding non-adherence prevalence and associated factors in this population will reflect the current reality of a rising incidence of complex patients. It is expected the prevalence of medication non-adherence will increase in accordance with the complexity of multimorbidity. A potential limitation relates to the restricted date range for database searching and the use of single-review to screen titles and abstracts. Another potential limitation relates to the heterogeneity associated with the experience of multimorbidity. Accordingly, between-study heterogeneity may not support the conduct of quantitative meta-analysis.
Results of the systematic review will be published in a peer-reviewed journal and disseminated at a range of health research conferences. The systematic review is part of a larger PhD project which aims to identify and understand predictors of non-adherence in multimorbidity in order to guide intervention development to support medication adherence for patients with multimorbidity.
Open Science Framework: Prevalence and predictors of medication non-adherence among patients with multimorbidity: A systematic review and meta-analysis. https://doi.org/10.17605/OSF.IO/9Y3RH (Foley, 2019).
The following files are available as extended data on Open Science Framework (OSF):
Open Science Framework: PRISMA-P checklist for ‘Prevalence and predictors of medication non-adherence among patients with multimorbidity: A systematic review and meta-analysis’. https://doi.org/10.17605/OSF.IO/9Y3RH (Foley, 2019).
Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Not applicable
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Multimorbidity, diabetes epidemiology, health services research.
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Not applicable
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Medication adherence; polypharmacy; multi-morbidity; community pharmacy; systematic reviews; intervention development; feasibility and pilot studies; pharmacists.
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
---|---|---|
1 | 2 | |
Version 2 (revision) 17 Mar 21 |
||
Version 1 11 Nov 19 |
read | read |
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Register with HRB Open Research
Already registered? Sign in
Submission to HRB Open Research is open to all HRB grantholders or people working on a HRB-funded/co-funded grant on or since 1 January 2017. Sign up for information about developments, publishing and publications from HRB Open Research.
We'll keep you updated on any major new updates to HRB Open Research
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)