Accuracy of measures of medication adherence in a cholesterol-lowering regimen

General medication adherence scale in patients with chronic illnesses: Persian translation and psychometric evaluation

OBJECTIVES

This study was conducted with the aim of determining the validity and reliability of the Persian version of "General Medication Adherence Scale (GMAS)" in chronic patients in Iran.

METHODOLOGY

The study was conducted among patients with chronic diseases in five hospitals of Iran. In this study, after cultural validation, using the steps of Content, Response Reaction, and Internal structure evaluations, the research sample was increased to 150 individuals for exploratory factor analysis (EFA) and 313 chronic patients for confirmatory factor analysis (CFA) to confirm the construct validity. Cronbach's alpha coefficient was used to assess internal consistency, and test-retest method was used to evaluate the reliability of the tool.

FINDINGS

The results of EFA and CFA confirmed the tool with three factors and 11 items. The R2 index in the above model was estimated at 0.99, indicating that 99% of the variation in medication adherence scores in research units was explained by GMAS with 11 items. The main indices of the model in factor analysis were all above 0.9, indicating a good fit for the model.

DISCUSSION

Overall, the study results showed that the Persian version of GMAS has acceptable and practical characteristics for evaluating medication adherence, and it can be used as a valid tool in various related fields.

Translation, cultural adaptation and validation of the General Medication Adherence Scale (GMAS) in moroccan patients with type-2 diabetes

BACKGROUND

The objective of the study was to cross-culturally adapt and validate the General Medication Adherence Scale (GMAS) in patients with type-2 diabetes in Morocco.

METHODS

The study was a cross-sectional study conducted between September 12 and October 12, 2022, and included patients with type-2 diabetes from a primary health care network. To measure the different psychometric parameters of the construct, data analysis was performed using SPSS v20. The study was approved by the Moroccan Association for Research and Ethics.

RESULTS

A total of 284 patients were included in the study; the results of the different psychometric parameters were largely acceptable. Indeed, the improvement of the goodness-of-fit of the model in relation to the independence model was evaluated by the comparative fit index (CFI), which was higher than 0.95, as well as the normalized fit index (NFI), which expresses the percentage of the general covariance between the variable demonstrated via the tested model when the null model is taken as reference and was also higher than 0.95 in this study. Additionally, the Tucker Louis Index (TLI) or Unstandardized Fit Index, which measures the increase in goodness of fit when moving from the reference model to the model under study, had a value of > 0.95. The correlations between the items were good; indeed, the Kaiser-Meyer-Olkin (KMO) index was > 0.7. The translated tool presents good internal consistency; thus, Cronbach's α had a value of approximately 0.804 (> 0.7).

CONCLUSIONS

The version of the GMAS tool adapted to the Moroccan context has very acceptable psychometric values. This means that Moroccan researchers and health professionals can use it as an instrument to measure adherence among individuals with type-2 diabetes.

The Role of Depression on Treatment Adherence in Patients with Heart Failure-a Systematic Review of the Literature

INTRODUCTION

Although poor medication adherence is considered an impacting risk factor for worsening heart failure (HF) outcomes, adherence rates in HF patients continue to be considerably low. To improve this condition, several studies investigated the impact of many determinants on medication adherence; however, few authors explored the role of depression on it.

PURPOSE OF REVIEW

The purpose of this systematic review was to explore the association between depressive symptoms and medication adherence in HF patients. In particular, the research question was is depression a barrier to medication adherence in HF patients?

METHODS

A systematic review of quantitative analysis studies was undertaken. Six electronic databases were searched between the end of October and March 2022. Thirty-one trials were included, all of them assessed depression, adherence to medication, and their possible relationship.

RESULTS

As was intended, findings showed that the impact of a mild to moderate level of depression was significant on adherence to treatment in HF patients. However, many other risk factors emerged, like family support and health practices (es. low sodium diet).

CONCLUSION

The detection of depression in the setting of HF should be crucial to HF patients' physical health and quality of life. Future research should take depression into account, exploring this area through self-report and qualitative interview as well.

Exploring Stem Cell Transplanted Patients' Perspectives on Medication Self-Management and Electronic Monitoring Devices Measuring Medication Adherence: A Qualitative Sub-Study of the Swiss SMILe Implementation Science Project

PURPOSE

Little is known about allogeneic stem cell transplant (alloSCT) patients' medication adherence strategies. Acceptability and preferences regarding electronic monitoring (EM) systems to assess all three phases of medication adherence (ie, initiation, implementation, persistence) are crucial to allow their successful implementation in clinical or research settings but have not yet been evaluated. We therefore aimed to explore: 1) alloSCT patients' medication adherence and self-management strategies; and 2) their acceptability and preferences of three different EM systems (MEMS Cap, Helping Hand, Button) as part of the Swiss SMILe study.

PATIENTS AND METHODS

Respecting anti-pandemic measures, we used a purposive sample of six adult alloSCT patients from the University Hospital Basel, Switzerland (USB)-6 weeks to 2 years post-alloSCT-to conduct three focus group sessions with two patients each. Using a semi-structured outline, we explored 1) patients' medication adherence strategies and medication self-management; and 2) their acceptance and preferences regarding EM use. The three tested EM systems were available for testing during each session. Discussions were audio-recorded, visualized using mind-mapping and analyzed using Mayring's qualitative content analysis.

RESULTS

Patients (33% females; mean age 54.6±16.3 years; 10.4±8.4 months post-alloSCT) used medication adherence enhancing strategies (eg, preparing pillbox, linking intake to a habit). Still, they indicated that post-alloSCT medication management was challenging (eg, frequent schedule changes). All participants preferred the MEMS Button. Participants said its small size and the possibility to combine it with existing pillboxes (eg, putting it into/next to them) made them more confident about implementing it in their daily lives.

CONCLUSION

Regarding EM systems for medication adherence, end-user preferences and acceptability influence adoption and fidelity. Of the three systems tested, our sample found the MEMS Button most acceptable and most preferable. Therefore, we will use it for our USB SMILe study.

Self-reported medication adherence measurement tools: Some options to avoid a legal minefield

WHAT IS KNOWN AND OBJECTIVE

Self-report questionnaires are used to measure medication adherence, often times both clinically and for research purposes. Despite the presence of several published tools, some may have prohibitive licensure and fee requirements, which researchers should be aware of prior to using them. This paper presents a summary of selected self-report measures, which have been developed and validated in various health conditions and can be used free of cost.

COMMENT

Our review identified self-report tools that are valid to measure medication adherence in different chronic health conditions. Most of these tools measure both intentional and unintentional non-adherence and have shown good correlation with relevant clinical outcomes.

WHAT IS NEW AND CONCLUSION

Given the potential copyright risks associated with using some of the self-report measures of adherence, an improved awareness and understanding of the available self-report questionnaires will better facilitate the decision by researchers to select appropriate tools relevant to their studies.

Long-term metformin adherence in the Diabetes Prevention Program Outcomes Study

INTRODUCTION

To investigate long-term metformin adherence in the Diabetes Prevention Program Outcomes Study (DPPOS) by examining: (1) predictors of long-term adherence to study metformin and (2) whether metformin adherence was associated with incident type 2 diabetes.

RESEARCH DESIGN AND METHODS

DPPOS was an open-label continuation of the randomized clinical trial (Diabetes Prevention Program (DPP)) in which eligible participants randomized to the metformin group were offered study metformin and followed over 11 years. A brief structured adherence interview was administered semiannually. Metformin adherence was assessed by pill counts. Predictors of metformin adherence were examined in multivariate regression models. Incident diabetes associated with metformin adherence and other variables was assessed in Cox proportional hazards models.

RESULTS

Of 868 participants eligible to continue taking study metformin, 664 (76%) took at least some metformin over 11 years, with 478 of them reporting problems with adherence. DPPOS cumulative adherence showed significant associations of higher adherence (≥80%) with early adherence at 3 months in DPP (p<0.001) and lower depression scores during DPPOS (p<0.001); significant differences were also seen by race/ethnicity (p<0.004). Predicting adherence by multivariate modeling showed odds of adherence significantly lower for Black participants and for participants reporting more than one barrier. Odds for adherence were significantly higher for those adherent early in DPP and those reporting at least one planned strategy to improve adherence. Higher metformin adherence was significantly associated with a lower diabetes risk (p=0.04), even after adjustment for demographic variables, depression, and anxiety scores.

CONCLUSIONS

In this long-term diabetes prevention study, early metformin adherence and planned strategies to promote adherence improved long-term adherence over 11 years; higher adherence to metformin was related to lower diabetes incidence. Incorporating strategies to promote adherence when initially prescribing metformin and counseling to support adherence over time are warranted.

User Acceptability and Technical Robustness Evaluation of a Novel Smart Pill Bottle Prototype Designed to Support Medication Adherence

PURPOSE

Smart medication adherence monitoring devices can provide objective and granular drug utilization data and help patients engaging with their treatment. In this proof-of-concept study, the acceptability and technical robustness of a novel smart pill bottle prototype (SPBP) were assessed in order to allow further optimization.

METHODS

The SPBP is an app-controlled automatic dispense system, capturing real-time data on a web-based platform, which sends text reminders and measures storage conditions. A heterogeneous group of ten volunteers was asked to dispense placebo capsules with the SPBP and to follow a predefined dosing schedule for a trial period of 2 weeks. Afterwards, a questionnaire was filled out during a short interview. Primary outcome was dispense adherence as measured by the bottle. Other study outcomes included system acceptability (System Usability Scale [SUS]), self-reported adherence (MARS) and technical robustness of the bottle's mechanics (electronic pill dispenser) and sensors (bottle temperature).

RESULTS

The overall dispense adherence rate as measured by the SPBP was 88%. All participants completed the study and four participants had an adherence rate of 100% during the study. The dispense adherence rates corresponded well with participants' self-reported adherence with an average MARS total score of 23.6 (out of 25). Participants judged the system easy to use, with a mean SUS score of 79.3 (range: 57.5-97.5). The overall mean temperature difference between the bottle sensor and calibrated external sensor was -0.82°C (range: -1.37°C to -0.21°C).

CONCLUSION

The SPBP was well accepted and this study provides data for further optimization and follow-up studies. Smart adherence technologies such as these may change the way healthcare professionals, trialists and patients manage medication adherence.

Developing implementation strategies to improve uptake of guideline-recommended treatments for individuals with familial hypercholesterolemia: A protocol

BACKGROUND

Familial hypercholesterolemia (FH) affects more than one million Americans, and most individuals have not been formally diagnosed with the condition. Individuals with FH have markedly elevated serum low-density lipoprotein cholesterol (LDL-C) levels from birth that substantially increase their risk for early-onset cardiovascular (CV) events. Guideline-recommended treatments exist to lower LDL-C and reduce the risk of CV events in individuals with FH and hypercholesterolemia. This study seeks to address a significant gap in the care of individuals with FH by systematically developing an effective approach to increase the adoption of guideline-recommended treatments for FH.

METHODS

This developmental study will consist of three aims: 1) determine the barriers to and facilitators of treatment of FH; 2) develop a list of potential implementation strategies to promote the adoption of guideline-recommended treatment of individuals with FH, and 3) pilot one implementation strategy from Aim 2 in one health care system to evaluate implementation outcomes of the strategy. The Practical, Robust Implementation and Sustainability Model will guide this project, including the development of interview questions, implementation strategies, and evaluation of the implementation strategy. The implementation outcomes include: of individuals targeted by the implementation strategy, how many are impacted by it (reach), measure the change in knowledge, attitude, and behavior that is impacted by the implementation strategy (effectiveness), in settings targeted by the implementation strategy, how many adopt it (adoption), and fidelity and cost of the implementation strategy (implementation). Data sources will include electronic health records, administrative databases, surveys, and semi-structured interviews.

DISCUSSION

The inclusion of patient and organizational stakeholder experiences is a critically important step in developing efficient and effective implementation strategies. Additionally, perspectives from a variety of geographic areas and cultural perspectives should increase feasibility and fidelity of the interventional approach to improve adoption of guideline-recommended practices for FH care.

Translation and validation of the English version of the general medication adherence scale (GMAS) in patients with chronic illnesses

Objective: This study aimed to translate the General Medication Adherence Scale (GMAS) into English language and validate it in patients suffering from chronic illnesses. Methods: A 1-month study (January 2018) was conducted in a random sample of patients suffering from chronic illnesses who visited the outpatient departments of four tertiary healthcare facilities in Karachi, Pakistan. Translation of the tool and its content, as well as face validity, was carried out. Factor structure was explored (i.e. exploratory and partial confirmatory factor analyses were carried out) and fit indices were calculated for model fitting. Test-re-test reliability and internal consistency were analyzed. Validity of GMAS-English was established by convergent, discriminant, and concurrent validity analysis. Sensitivity analysis was conducted. Data was analyzed through SPSS version 23. The study was ethically approved by concerned authorities (Letter# NOV:15). Results: The GMAS was translated into English language by standard procedure. Factor analysis indicated a 3-factor model. Fit indices, namely normed fit index, Tucker Lewis index, comparative fit index, and root mean square of error approximation, were calculated with satisfactory results (i.e. NFI, TLI, and CFI > 0.9 and RMSEA < 0.08). Internal consistency (α) was 0.82. A high response rate of 91.6% was reported. GMAS-English established convergent, discriminant, and concurrent validities. The tool was sensitive (>75%) in screening patients with partial-to-low adherence based on their education level. Conclusion: The tool was translated in English language and demonstrated adequate internal consistency. The results indicate that GMAS-English is a valid and reliable tool to measure medication adherence in patients with chronic illness.

Development and Validation of a Novel General Medication Adherence Scale (GMAS) for Chronic Illness Patients in Pakistan

Objective: This study aimed to develop and validate a self-reporting adherence tool termed as General Medication Adherence Scale (GMAS) in Urdu language for measuring adherence toward medication use among Pakistani patients with a chronic disease. Methods: A month-long study (December 2017) was conducted in three tertiary health care settings of Karachi, Pakistan. The tool underwent content and face validity as well as factor analyses, i.e., exploratory, partial confirmatory and confirmatory factor analyses. Random sampling was conducted, and sample size was calculated using item response theory. The item-to-respondent ratio was 1:15. Fit indices namely normed fit index (NFI), Tucker Lewis index (TLI), comparative fit index (CFI), goodness of fit index (GFI), absolute goodness of fit (AGFI), parsimony goodness of fit index (PGFI), root mean square error of approximation (RMSEA), and standard root mean square residual (SRMR) were calculated. Additionally, estimation of the convergent, discriminant and known group validities, was conducted. Internal consistency was analyzed by test-retest reliability, McDonald's and Pearson correlation coefficient. The factor analyses were conducted using IBM SPSS version 22 and IBM SPSS AMOS version 25. Results: Content validity index (CVI) was reported at 0.8 (SD 0.147) and the tool was content validated with three hypothetical constructs. Factor analyses highlighted a 3-factor structure. The fit indices were calculated with satisfactory results, i.e., PGFI, GFI, AGFI, NFI, TLI, and CFI were greater than 0.9 and PGFI > 0.5. The values of RMSEA and SRMR were less than 0.07. A Cronbach's alpha value of 0.84 was obtained in reliability analysis. The test-retest Pearson's correlation coefficient value was reported at 0.996 (p-value < 0.01). Convergent and discriminant validities for all constructs and, known group validity for two constructs, were established. A high response rate of 91% was achieved in respondents. Patients without insurance coverage appeared to be low adherent compared to those with insurance coverage (p-value < 0.05). Non-comorbid patients were more likely to be highly adherent as compared to comorbid patients (p-value < 0.01). Conclusion: A novel tool GMAS was developed in Urdu language and was subsequently validated in patients with chronic diseases.

A systematic literature review comparing methods for the measurement of patient persistence and adherence

OBJECTIVES

A systematic literature review was conducted comparing different approaches estimating persistence and adherence in chronic diseases with polypharmacy of oral and subcutaneous treatments.

METHODS

This work followed published guidance on performing systematic reviews. Twelve electronic databases and grey literature sources were used to identify studies and guidelines for persistence and adherence of oral and subcutaneous therapies in hypercholesterolemia, type 2 diabetes, hypertension, osteoporosis and rheumatoid arthritis. Outcomes of interest of each persistence and adherence data collection and calculation method included pros: accurate, easy to use, inexpensive; and cons: inaccurate, difficult to use, expensive.

RESULTS

A total of 4158 records were retrieved up to March 2017. We included 16 observational studies, 5 systematic reviews and 7 guidelines, in patients with hypercholesterolemia (n = 8), type 2 diabetes (n = 4), hypertension (n = 2), rheumatoid arthritis (n = 1) and mixed patient populations (n = 13). Pharmacy and medical records offer an accurate, easy and inexpensive data collection method. Pill count, medication event monitoring systems (MEMs), self-report questionnaires and observer report are easy to use. MEMS and biochemical monitoring tests can be expensive. Proportion of days covered (PDC) was recommended as a gold standard calculation method for long-term treatments. PDC avoids use of days' supply in calculation, hence is more accurate compared to medication possession ratio (MPR) to assess adherence to treatments in chronic diseases.

CONCLUSIONS

Decisions on what method to use should be based on considerations of the route of medication administration, the resources available, setting and aim of the assessment. Combining different methods may provide wider insights into adherence and persistence, including patient behavior.

Concordance of Adherence Measurement Using Self-Reported Adherence Questionnaires and Medication Monitoring Devices: An Updated Review

INTRODUCTION

As medication adherence continues to be a prevalent issue in today's society, the methods used to monitor medication-taking behaviors are constantly being re-evaluated and compared in search of the 'gold standard' measure. Our review aimed to assess the current literature surrounding the correlation between self-reported questionnaires (SRQs) and electronic monitoring devices to determine if these measures produce similar results.

METHODS

We performed a literature search from 2009 to 2017 using PubMed, PubMed In-Process and Non-Indexed, EMBASE, Ovid MEDLINE, and Ovid MEDLINE In-Process. A keyword search using the terms 'patient compliance', 'treatment compliance', 'medication adherence', 'drug monitoring', 'drug therapy', 'electronic', 'digital', 'computer', 'monitor', 'monitoring', 'drug', 'pharmaceutical preparations', 'compliance', and 'medications' was done to capture all articles. We included articles measuring adherence using both monitoring devices and SRQs.

RESULTS

Thirty-five articles were included in this review. The average difference in measured adherence rates between the two measures was 9.2% (range -66.3 to 61.5). A majority (62.7%) of articles reported moderate (n = 12; 27.9%), high (n = 5, 11.6%), or significant (n = 10, 23.3%) correlations between SRQs and monitoring devices.

CONCLUSION

Results from our review are consistent with previous studies, as we found that many of our studies produced moderate to high correlation between both SRQs and monitoring devices [Farmer, Clin Ther 21(6):1074-90 (1999), IMS Institute for Healthcare Informatics. Avoidable costs in US health care (2012), Patel et al., Respirology 18(3):546-52 (2013), Siracusa et al., J Cyst Fibros 14(5):621-6 (2015), Smith et al., Int J Cardiol 145(1):122-3 (2010)]. Our findings demonstrate that self-reported adherence produces comparable results to electronic monitoring devices. As there is not yet a 'gold standard' measure for monitoring patient adherence, SRQs and Medication Event Monitoring Systems (MEMS) operating together continue to emerge as the preferred effective method for measuring medication adherence.

Medication Adherence in Hematopoietic Stem Cell Transplantation: A Review of the Literature

Adherence to oral medications has been repeatedly shown to fall below the recommended 80% to 95% in pediatric and adult cancer populations. The purpose of this review is to report the state of the science about oral medication adherence during the acute phase of hematopoietic stem cell transplantation across the lifespan. An exhaustive search of the literature yielded 5 records for inclusion in the review. Two studies examined adherence in pediatrics, 2 in adults, and 1 included both pediatric and adult patients. Three studies were descriptive and 2 were interventional in design. The rate of adherence to oral medications ranged from 33% to 94.7%. Adherence decreased over time in all studies except in 1 pharmacist-led intervention study. Different methods were used to measure adherence, but most relied on self-report. Further research is needed in medication adherence in hematopoietic stem cell transplantation to better understand facilitators, barriers, and relationships to health outcomes.

A Randomized Controlled Trial of a Mobile Health Intervention to Promote Self-Management After Lung Transplantation

Lung transplant recipients are encouraged to perform self-management behaviors, including (i) monitoring health indicators, (ii) adhering to their regimen, and (iii) reporting abnormal health indicators to the transplant coordinator, yet performance is suboptimal. When hospital discharge was imminent, this two-group trial randomized 201 recipients to use either the mobile health (mHealth) intervention (n = 99) or usual care (n = 102), to compare efficacy for promoting self-management behaviors (primary outcomes) and self-care agency, rehospitalization, and mortality (secondary outcomes) at home during the first year after transplantation. The mHealth intervention group performed self-monitoring (odds ratio [OR] 5.11, 95% confidence interval [CI] 2.95-8.87, p < 0.001), adhered to medical regimen (OR 1.64, 95% CI 1.01-2.66, p = 0.046), and reported abnormal health indicators (OR 8.9, 95% CI 3.60-21.99, p < 0.001) more frequently than the usual care group. However, the two groups did not differ in rehospitalization (OR 0.78, 95% CI 0.36-1.66, p = 0.51) or mortality (hazard ratio 1.71, 0.68-4.28, p = 0.25). The positive impact of the mHealth intervention on self-management behaviors suggests that the intervention holds promise and warrants further testing.

The Effectiveness of Medication Adherence Interventions Among Patients With Coronary Artery Disease: A Meta-analysis

BACKGROUND

Despite the known benefits of medication therapy for secondary prevention of coronary artery disease (CAD), many patients do not adhere to prescribed medication regimens. Medication nonadherence is associated with poor health outcomes and higher healthcare cost.

OBJECTIVE

The purpose of this meta-analysis was to determine the overall effectiveness of interventions designed to improve medication adherence (MA) among adults with CAD. In addition, sample, study design, and intervention characteristics were explored as potential moderators to intervention effectiveness.

METHODS

Comprehensive search strategies helped in facilitating the identification of 2-group, treatment-versus-control-design studies testing MA interventions among patients with CAD. Data were independently extracted by 2 trained research specialists. Standardized mean difference effect sizes were calculated for eligible primary studies, adjusted for bias, and then synthesized under a random-effects model. Homogeneity of variance was explored using a conventional heterogeneity statistic. Exploratory moderator analyses were conducted using meta-analytic analogs for analysis of variance and regression for dichotomous and continuous moderators, respectively.

RESULTS

Twenty-four primary studies were included in this meta-analysis. The overall effect size of MA interventions, calculated from 18,839 participants, was 0.229 (P < .001). The most effective interventions used nurses as interventionists, initiated interventions in the inpatient setting, and informed providers of patients' MA behaviors. Medication adherence interventions tested among older patients were more effective than those among younger patients. The interventions were equally effective regardless of number of intervention sessions, targeting MA behavior alone or with other behaviors, and the use of written instructions only.

CONCLUSIONS

Interventions to increase MA among patients with CAD were modestly effective. Nurses can be instrumental in improving MA among these patients. Future research is needed to investigate nurse-delivered MA interventions across varied clinical settings. In addition, more research testing MA interventions among younger populations and more racially diverse groups is needed.

Predictors of medication adherence: fact or artifact

Numerous studies have examined socio-demographic, psychosocial, and other factors as potential contributors to poor adherence. Variability exists in the strength and consistency of findings. We speculated that the method of measuring adherence might be a factor in the variability in identification of predictor variables. We examined the identification of predictors of adherence by method of measurement in two randomized, controlled trials of adherence interventions. Both studies used the Aardex Medication Event Monitor and the Morisky Self-Report Scale. Twenty-one days of baseline data from 698 subjects were examined in relation to measures of depression, functional status, perceived therapeutic efficacy, number of co-morbidities, and socio-demographic indices. Analysis included Spearman rho, Pearson r, and multiple logistic regression. Differences in the identification of predictors between adherence measurement methods were identified. These data support the hypothesis that different measurement methods yield different predictors of adherence.

Toward appropriate criteria in medication adherence assessment in older persons: Position Paper

Nonadherence to medication regimens is a worldwide challenge; adherence rates range from 38 to 57 % in older populations with an average rate of less than 45 % and nonadherence contributes to adverse drug events, increased emergency visits and hospitalisations. Accurate measurement of medication adherence is important in terms of both research and clinical practice. However, the identification of an objective approach to measure nonadherence is still an ongoing challenge. The aim of this Position Paper is to describe the advantages and disadvantages of the known medication adherence tools (self-report, pill count, medication event monitoring system (MEMS) and electronic monitoring devices, therapeutic drug monitoring, pharmacy records based on pharmacy refill and pharmacy claims databases) to provide the appropriate criteria to assess medication adherence in older persons. To the best of our knowledge, no gold standard has been identified in adherence measurement and no single method is sufficiently reliable and accurate. A combination of methods appears to be the most suitable. Secondly, adherence assessment should always consider tools enabling polypharmacy adherence assessment. Moreover, it is increasingly evident that adherence, as a process, has to be assessed over time and not just at one evaluation time point (drug discontinuation). When cognitive deficits or functional impairments may impair reliability of adherence assessment, a comprehensive geriatric assessment should be performed and the caregiver involved. Finally, studies considering the possible implementation in clinical practice of adherence assessment tools validated in research are needed.

Medication adherence interventions that target subjects with adherence problems: Systematic review and meta-analysis

BACKGROUND

Inadequate medication adherence is a pervasive, under-recognized cause of poor health outcomes. Many intervention trials designed to improve medication adherence have targeted adults with adherence problems. No previous reviews have synthesized the effectiveness of medication adherence interventions focused on subjects with medication adherence difficulties.

OBJECTIVE

This systematic review and meta-analysis synthesized findings from medication adherence intervention studies conducted among adults with medication adherence difficulties.

METHODS

Primary research studies were eligible for inclusion if they tested an intervention designed to increase medication adherence among adults with documented adherence difficulties and reported medication adherence behavior outcomes. Comprehensive search strategies of 13 computerized databases, author and ancestry searches, and hand searches of 57 journals were used to locate eligible primary research. Participant demographics, intervention characteristics, and methodological features were reliably coded from reports along with medication adherence outcomes. Effect sizes for outcomes were calculated as standardized mean differences, and random effects models were used to estimate overall mean effects. Exploratory dichotomous and continuous variable moderator analyses were employed to examine potential associations between medication adherence effect size and sample, intervention, and methodological characteristics.

RESULTS

Data were extracted from 53 reports of studies involving 8243 individual primary study participants. The overall standardized mean difference effect size for treatment vs. control subjects was 0.301. For treatment pre- vs. post-intervention comparisons, the overall effect size was 0.533. Significantly larger effect sizes were associated with interventions incorporating prompts to take medications than interventions lacking medication prompts (0.497 vs. 0.234). Larger effect sizes were also found for interventions that linked medication taking with existing habits compared to interventions that did not (0.574 vs. 0.222). Effect sizes were largest among studies that measured adherence by pill counts or electronic event monitoring systems. Analysis of study design features identified several potential risks of bias. Statistically significant publication bias was detected, but adherence effect sizes were not significantly associated with other risks of bias.

CONCLUSIONS

These findings document that interventions targeting individuals with medication adherence problems can have modest but significant effects on medication-taking behavior. The findings support the use of behavioral strategies such as prompts and linking medications to habits to increase medication adherence in adults with adherence challenges. Face-to-face interventions appear to be critical for patients who have experienced past problems with medication adherence.

Self-report measures of medication adherence behavior: recommendations on optimal use

Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review self-report medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care.

Medication adherence in a nurse practitioner managed clinic for indigent patients

PURPOSE

Little is published in the literature about medication adherence rates among patients who are medically indigent and patients receiving primary care from nurse practitioners (NPs). This project examined adherence rates and barriers to adherence among patients at an NP-managed health clinic (NPMC).

DATA SOURCES

The setting for this research was an NPMC for uninsured and low-income patients. A cross-sectional convenience sample of patients (n = 119) completed surveys eliciting demographic information, self-report of medication adherence, health literacy, and barriers to adherence.

CONCLUSIONS

Analysis of subjects demonstrated a vulnerable population, yet the mean adherence rate was surprisingly high (77%), compared to the rate usually cited in published literature. The best predictive model differentiating patients with high adherence from those with low adherence combined the total number of reported barriers, health literacy, and employment status. The barriers most frequently cited by subjects were difficulty paying for medications, and difficulty reading and understanding written prescription labels, which was particularly prevalent among Spanish-speaking patients.

IMPLICATIONS FOR PRACTICE

Clinic efforts to improve patient access to affordable medications may have contributed to subjects' high rates of adherence. These efforts included helping patients with filling out prescription assistance program paperwork, prescribing generic medications, providing samples, and providing effective patient education.

KDOQI US commentary on the 2013 KDIGO Clinical Practice Guideline for Lipid Management in CKD

The National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (NKF-KDOQI) guideline for management of dyslipidemia in chronic kidney disease (CKD) was published in 2003. Since then, considerable evidence, including randomized controlled trials of statin therapy in adults with CKD, has helped better define medical treatments for dyslipidemia. In light of the new evidence, KDIGO (Kidney Disease: Improving Global Outcomes) formed a work group for the management of dyslipidemia in patients with CKD. This work group developed a new guideline that contains substantial changes from the prior KDOQI guideline. KDIGO recommends treatment of dyslipidemia in patients with CKD primarily based on risk for coronary heart disease, which is driven in large part by age. The KDIGO guideline does not recommend using low-density lipoprotein cholesterol level as a guide for identifying individuals with CKD to be treated or as treatment targets. Initiation of statin treatment is no longer recommended in dialysis patients. To assist US practitioners in interpreting and applying the KDIGO guideline, NKF-KDOQI convened a work group to write a commentary on this guideline. For the most part, our work group agreed with the recommendations of the KDIGO guideline, although we describe several areas in which we believe the guideline statements are either too strong or need to be more nuanced, areas of uncertainty and inconsistency, as well as additional research recommendations. The target audience for the KDIGO guideline includes nephrologists, primary care practitioners, and non-nephrology specialists such as cardiologists and endocrinologists. As such, we also put the current recommendations into the context of other clinical practice recommendations for cholesterol treatment.

Validity of medication adherence self-reports in adults with type 2 diabetes

OBJECTIVE

To assess the validity of self-report measures of diabetes medication adherence and evaluate the effect of depression on the validity of these reports.

RESEARCH DESIGN AND METHODS

Adults with type 2 diabetes, treated with oral medications, completed a set of medication adherence self-reports that varied response scales and time frames, were administered structured clinical interviews for depression, and provided blood samples for HbA(1c) as part of a screening for an intervention study. A subsample of participants with HbA(1c) ≥7.0% and clinically significant depression received Medication Event Monitoring System (MEMS) bottle caps to record adherence. Analyses examined relationships between adherence measures and HbA(1c) and, in the subsample, MEMS. Moderated linear regression evaluated whether depression severity modified relationships with HbA(1c).

RESULTS

Participant (n = 170, 57% men, 81% white, mean HbA(1c) 8.3% [SD, 1.7]) adherence self-reports were significantly (r = -0.18 to -0.28; P < 0.03) associated with lower HbA(1c). In the subsample (n = 88), all self-reports were significantly (r = 0.35 to 0.55; P ≤ 0.001) associated with MEMS-measured adherence. Depression significantly moderated the relationship between three of six self-reports and HbA(1c); at high levels of depression, associations with HbA(1c) became nonsignificant.

CONCLUSIONS

Results support the validity of easily administered self-reports for diabetes medication adherence. One-month, percentage-based ratings of adherence had the strongest associations with MEMS and HbA(1c); those requiring the report of missed doses had weaker associations. One-week self-ratings and measures that require respondents to record the number of missed doses appear to be vulnerable to bias from depression severity.

A multifaceted prospective memory intervention to improve medication adherence: design of a randomized control trial

Adherence to prescribed antihypertensive agents is critical because control of elevated blood pressure is the single most important way to prevent stroke and other end organ damage. Unfortunately, nonadherence remains a significant problem. Previous interventions designed to improve adherence have demonstrated only small benefits of strategies that target single facets such as understanding medication directions. The intervention described here is informed by prospective memory theory and performance of older adults in laboratory-based paradigms and uses a comprehensive, multifaceted approach to improve adherence. It incorporates multiple strategies designed to support key components of prospective remembering involved in taking medication. The intervention is delivered by nurses in the home with an education control group for comparison. Differences between groups in overall adherence following the intervention and 6 months later will be tested. Systolic and diastolic blood pressure levels also will be examined between groups and as they relate to adherence. Intra-individual regression is planned to examine change in adherence over time and its predictors. Finally, we will examine the association between executive function/working memory and adherence, predicting that adherence will be related to executive/working memory in the control group but not in the intervention group.