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Background: Quality improvement efforts are frequently tied to patients achieving ≥80% medication adherence. However, there is little empirical evidence that this threshold optimally predicts important health outcomes., Objective: To apply machine learning to examine how adherence to oral hypoglycemic medications is associated with avoidance of hospitalizations, and to identify adherence thresholds for optimal discrimination of hospitalization risk., Methods: A retrospective cohort study of 33,130 non-dual-eligible Medicaid enrollees with type 2 diabetes. We randomly selected 90% of the cohort (training sample) to develop the prediction algorithm and used the remaining (testing sample) for validation. We applied random survival forests to identify predictors for hospitalization and fit survival trees to empirically derive adherence thresholds that best discriminate hospitalization risk, using the proportion of days covered (PDC)., Outcomes: Time to first all-cause and diabetes-related hospitalization., Results: The training and testing samples had similar characteristics (mean age, 48 y; 67% female; mean PDC=0.65). We identified 8 important predictors of all-cause hospitalizations (rank in order): prior hospitalizations/emergency department visit, number of prescriptions, diabetes complications, insulin use, PDC, number of prescribers, Elixhauser index, and eligibility category. The adherence thresholds most discriminating for risk of all-cause hospitalization varied from 46% to 94% according to patient health and medication complexity. PDC was not predictive of hospitalizations in the healthiest or most complex patient subgroups., Conclusions: Adherence thresholds most discriminating of hospitalization risk were not uniformly 80%. Machine-learning approaches may be valuable to identify appropriate patient-specific adherence thresholds for measuring quality of care and targeting nonadherent patients for intervention.

Introduction: Although consistent use of tyrosine kinase inhibitors (TKIs) confers significant improvements in long-term survival for individuals with chronic myeloid leukemia (CML), only 70% of CML patients are adherent to TKIs. Understanding the factors that contribute to non-adherence and establishing dynamic adherence patterns in this population are essential aspects of targeted drug monitoring and intervention strategies. Methods: Newly diagnosed CML patients were identified in the MarketScan database and relevant covariate values extracted. Proportion of days covered (PDC) per 30-day interval was used to calculate adherence over a 12-month follow-up period. We conducted a latent profile analysis (LPA) on these PDC estimates to identify distinct, dynamic patterns of TKI adherence. Identified trajectories were grouped into four clinically relevant categories and predictors of membership in these categories were determined via multinomial logistic regression. Results: Four broad adherence categories were identified from the LPA: never adherent, initially non-adherent becoming adherent, initially adherent becoming non-adherent, and stable adherent. Results from the subsequent multinomial logistic regression indicated that younger age, female sex, greater monthly financial burden, fewer comorbidities, fewer concomitant medications, year of diagnosis, higher starting dose, TKI type, and a longer duration from diagnosis to treatment were significantly associated with membership in at least one of the three non-stable adherent groups. Conclusion: Select sociodemographic and clinical characteristics were found to predict membership in clinically meaningful groups of longitudinal TKI adherence. These findings could have major implications for informing personalized monitoring and intervention strategies for individuals who are likely to be non-adherent. [ABSTRACT FROM AUTHOR]

Background/objective: As pharmacists work to ensure reimbursement for chronic disease management services on the national level, evidence of their impact on important health metrics, such as medication adherence, is needed. However, summative evidence is lacking on the effectiveness of pharmacists to improve medication adherence in older adults. The objective was to assess the effectiveness of pharmacist‐led interventions on medication adherence in older adults (65+ years). Design/setting/participants: Using a systematic review and meta‐analytic approach, a comprehensive search of publications in PubMed, Scopus, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Google Scholar was conducted through April 2, 2020 for randomized clinical trials of pharmacist‐led interventions to improve medication adherence in older adults. A standardized mean difference effect size (Cohen's d) was calculated for medication adherence in each study. Study effect sizes were pooled using a random‐effects model, with effect sizes weighted by inverse of its total variance. Measurements Medication adherence using any method of measurement. Results: Among 40 unique randomized trials of pharmacist‐led interventions with data from 8822 unique patients (mean age, range: 65–85 years), the mean effect size was 0.57 (k = 40; 95% Confidence Interval [CI]: 0.38–0.76). When two outlier studies were excluded from the analysis, the mean effect size reduced to 0.41 (k = 38; 95% CI: 0.27–0.54). A sensitivity analysis of medication adherence outcome by time point resulted in a mean effect size of 0.64 at 3 months (k = 12; 95% CI: 0.32–0.97), 0.30 at 6 months (k = 13; 95% CI: 0.11–0.48), 0.22 at 12 months (k = 12; 95% CI: 0.08–0.37), and 0.36 for outcome time points beyond 12 months (k = 5; 95% CI: 0.02–0.70). Conclusion: This meta‐analysis found a significant improvement in medication adherence among older adults receiving pharmacist‐led interventions. Implementation of pharmacist‐led interventions supported by Medicare reimbursement could ensure older adults' access to effective medication adherence support. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to characterize trajectories of antiseizure medication (ASM) adherence in adults with newly treated epilepsy and to determine predictors of trajectories. Methods: This was a retrospective cohort study using Medicare. We included beneficiaries with newly treated epilepsy (one or more ASM and none in the preceding 2 years, plus International Classification of Diseases codes) in 2010–2013. We calculated the proportion of days covered (proportion of total days with any ASM pill supply) for 8 quarters or until death. Group‐based trajectory models characterized and determined predictors of trajectories. Results: We included 24 923 beneficiaries. Models identified four groups: early adherent (60%), early nonadherent (18%), late adherent (11%), and late nonadherent (11%). Numerous predictors were associated with being in the early nonadherent versus early adherent group: non‐White race (e.g., Black, odds ratio [OR] = 1.7, 95% confidence interval [CI] = 1.5–1.8), region (e.g., South vs. Northeast: OR = 1.2, 95% CI = 1.1–1.4), and once daily initial medication (OR = 1.1, 95% CI = 1.0–1.3). Predictors associated with decreased odds of being in the early nonadherent group included older age (OR =.9 per decade, 95% CI =.9–.9), female sex (OR =.9, 95% CI =.8–1.0), full Medicaid eligibility (OR =.6, 95% CI =.4–.8), neurologist visit (OR =.6, 95% CI =.6–.7), and initial older generation ASM (OR =.6, 95% CI =.6–.7). Significance: We identified four ASM adherence trajectories in individuals with newly treated epilepsy. Whereas risk factors for early nonadherence such as race or geographic region are nonmodifiable, our work highlighted a modifiable risk factor for early nonadherence: lacking a neurologist. These data may guide future interventions aimed at improving ASM adherence, in terms of both timing and target populations. [ABSTRACT FROM AUTHOR]

Improving the quality of medication use and medication safety is an important priority for prescribers who care for older adults. The objective of this article was to identify key articles from 2018 that address these issues. In addition, we selected four of these articles to annotate, critique, and discuss their broader implications for clinical practice. The first study highlights a cluster‐randomized trial that utilized a pharmacist‐led education‐based intervention delivered to both patients and physicians to deprescribe four types of inappropriate medications (sedative‐hypnotics, first‐generation antihistamines, selective nonsteroidal anti‐inflammatory drugs, and glyburide). The second study, a nested case‐control study using data from within the UK Clinical Practice Research Datalink, examined the association between anticholinergic exposure, overall and by anticholinergic medication class, and dementia risk in 40 770 older adults. The third study, a longitudinal cohort study of 1028 Swedish older adults, examined the association between antihypertensive medications and incident dementia. The last study was a randomized, double‐blind, placebo‐controlled trial that investigated the effect of daily low‐dose aspirin (100 mg) for primary prevention on cardiovascular events and major hemorrhage in 19 144 community‐dwelling older adults. Collectively, this current article provides insight into the pertinent topics of medication use quality and safety in older adults and helps raise awareness about optimal prescribing in older adults. J Am Geriatr Soc 67:2458–2462, 2019 [ABSTRACT FROM AUTHOR]

Background: Robust evidence is lacking on optimal timing of statin administration and its impact on patient outcomes.Objective: This study aims to evaluate among incident statin users the relationship between those prescribed evening vs. daily dosing instructions, medication adherence, and changes in low-density lipoprotein cholesterol (LDL-c).Design: This is an observational cohort study at Sutter Health, a community-based healthcare system, 2010-2016.Participants: Patients were ≥ 35 years of age as of the first statin prescription (baseline), with 12 to 36 months of electronic health record activity before and after baseline. Incident use was defined as no statin prescription in 12 months prior to baseline.Main Measures: Differences in medication adherence (proportion of days covered ≥ 0.80) over 12 months from baseline and mean change in LDL-c between 12 and 24 months from baseline were measured using regression modeling, adjusting for baseline demographics and clinical, prescriber, and statin characteristics.Key Results: Among 31,252 patients with valid statin prescriptions between 2010 and 2016, 5099 eligible incident statin users (mean age, 63 years) were identified, of whom 53% were prescribed evening and 47% daily dosing instructions. No difference in likelihood of statin adherence over 12 months was observed for evening vs. daily dosing (adjusted odds ratio [OR] 0.90; 95% CI 0.75, 1.08). No differences were observed in mean change in LDL-c (adjusted mean difference 1.42 mg/dL; 95% CI - 1.02, 3.89) or likelihood of attaining LDL-c < 70 mg/dL (adjusted OR 0.83; 95% CI 0.67, 1.04) for evening vs. daily dosing over a mean of 19 months follow-up.Conclusions: Among incident statin users from a real-world clinical setting, those with daily and evening dosing instructions had similar adherence rates and mean changes in LDL-c. Given potential clinical equipoise for evening and daily dosing, clinicians should consider patient-tailored statin dosing instructions to reduce potentially unnecessary regimen complexity. [ABSTRACT FROM AUTHOR]

Background: Detecting patients with undiagnosed dementia is an important clinical challenge. Changes in medication adherence might represent an early sign of cognitive impairment. We sought to examine antihypertensive and statin adherence trajectories in community-dwelling older adults, comparing people who went on to develop dementia to those who did not.Methods: We analyzed data from Adult Changes in Thought (ACT), a population-based cohort study embedded within an integrated healthcare delivery system. Analyses included 4368 participants aged ≥65 years who had at least one follow-up visit. Research-quality dementia diagnoses were used to identify cases. We selected non-dementia control visits matched on age, sex, and study cohort that occurred at similar ACT follow-up time as the case's dementia onset; we treated this as the index date. Participants were included if they were prevalent users of either a statin or antihypertensive medication on the first day of follow up - 3 years prior to the index date. Using prescription fill dates and days supply, we calculated daily binary medication availability measures for each participant ('days covered') over 3 years leading up to the index date. We used group-based trajectory models to identify patterns of antihypertensive and statin adherence, and used conditional logistic regression to examine associations between adherence trajectories and dementia.Results: Four trajectories were identified for antihypertensive users (292 cases, 3890 control visits), including near perfect (n = 1877, 36.6% cases, 45.5% controls), high (n = 1840, 43.2% cases, 44.1% controls), moderate (n = 365, 18.5% cases, 8.0% controls) and early poor adherence (n = 100, 1.7% cases, 2.4% controls). Odds of dementia was 3 times greater for those with moderate antihypertensive adherence compared to those with near perfect adherence (adjusted OR 3.0, 95% CI 2.0, 4.3). Four trajectories were identified for statin users (148 cases, 1131 control visits), including high (n = 1004, 75.0% cases, 79.0% controls), moderate (n = 192, 19.6% cases, 14.4% controls), early poor (n = 43, 2.0% cases, 3.5% controls), and delayed poor adherence (n = 40, 3.4% cases, 3.1% controls). No association was detected between statin adherence trajectories and dementia.Conclusions: Patterns of medication adherence may be useful to identify a subset of people at higher likelihood of developing dementia. [ABSTRACT FROM AUTHOR]

Improving the quality of medication use and medication safety in older adults is an important public health priority and is of paramount importance for clinicians who care for them. We selected four important articles from 2017 that address these issues to annotate and critique, and we discuss the broader implications for optimizing medication use. A longer list of articles is given in an online appendix. The first study provides national data on the prevalence of central nervous system–active medication polypharmacy in older adults and how this has changed over a 9‐year period (2004–2013). The second study characterizes prevalence of and factors associated with nonadherence to antiepileptic drugs in 36,912 older adults with epilepsy, with an emphasis on minorities. The third study describes the extent of antibiotic use in residents of 381 long‐term care facilities (LTCF) in British Columbia, Canada, from 2007 to 2014. Finally, we discuss a meta‐analysis of 42 studies that evaluated the prevalence of hospital admissions caused by adverse drug reactions in older adults. This article is intended to provide a narrative review of important publications on medication use quality and safety for clinicians and researchers committed to optimizing medication use in older adults. J Am Geriatr Soc 66:2254–2258, 2018. [ABSTRACT FROM AUTHOR]

Background: Numerous interventions are available to boost medication adherence, but the targeting of these interventions often relies on crude measures of poor adherence. Group-based trajectory models identify individuals with similar longitudinal prescription filling patterns. Identifying distinct adherence trajectories may be more useful for targeting interventions, although the association between adherence trajectories and clinical outcomes is unknown.Objective: To examine the association between adherence trajectories for oral hypoglycemics and subsequent hospitalizations among diabetes patients.Design: Retrospective cohort study.Patients: A total of 16,256 Pennsylvania Medicaid enrollees, non-dually eligible for Medicare, initiating oral hypoglycemics between 2007 and 2009.Main Measures: We used group-based trajectory models to identify trajectories of oral hypoglycemics in the 12 months post-treatment initiation, using monthly proportion of days covered (PDC) as the adherence measure. Multivariable Cox proportional hazard models were used to examine the association between trajectories and time to first diabetes-related hospitalization/emergency department (ED) visits in the following year. We used the C-index to compare prediction performance between adherence trajectories and dichotomous cutpoints (annual PDC <80 vs. ≥80 %).Results: The mean annual PDC was 0.58 (SD 0.32). Seven trajectories were identified: perfect adherers (9 % of the cohort), nearly perfect adherers (31.4 %), moderate adherers (21.0 %), low adherers (11.0 %), late discontinuers (6.8 %), early discontinuers (9.7 %), and non-adherers with only one fill (11.1 %). Compared to perfect adherers, trajectories of moderate adherers (HR = 1.48, 95 % CI 1.25, 1.75), low adherers (HR = 1.51, 95 % CI 1.25, 1.83), and non-adherers with only one fill (HR = 1.35, 95 % CI 1.09, 1.67) had greater risk of diabetes-related hospitalizations/ED visits. Predictive accuracy was improved using trajectories compared to dichotomized cutpoints (C-index = 0.714 vs. 0.652).Conclusions: Oral hypoglycemic treatment trajectories were highly variable in this large Medicaid cohort. Low and moderate adherers and those filling only one prescription had a modestly higher risk of hospitalizations/ED visits compared to perfect adherers. Trajectory models may be valuable in identifying specific non-adherence patterns for targeting interventions. [ABSTRACT FROM AUTHOR]

Background: Poor medication adherence is a major public health problem in older adults often resulting in negative health outcomes. Objective: The objective of this review was to provide an updated summary of evidence from randomized controlled studies to determine whether interventions aimed at improving medication adherence also improve the health outcomes of older adults residing in community-based settings. Methods: Articles that assessed medication adherence interventions and related health outcomes in elderly individuals were identified through searches of MEDLINE (1970-June 2016), the Cochrane Database of Systematic Reviews (through to June 2016), and Google Scholar. Across the 12 included studies, interventions were grouped into three main categories: behavioral/educational ( n = 3), pharmacist-led ( n = 7), and reminder/simplification ( n = 2). Results: Among the behavioral/educational intervention studies, two showed improvements in both adherence and related health outcomes, whereas one found no changes in adherence or health outcomes. Among the pharmacist-led studies, three showed improvements in both adherence and related health outcomes, while three reported no changes in adherence or health outcomes. One found an improvement in adherence but not health outcomes. Among the reminder/simplification studies, both studies reported improvements in adherence without a significant impact on related health outcomes. Conclusion: This evidence-based review of medication adherence interventions in older adults revealed promising strategies in the larger context of a largely mixed body of literature. Future patient-centered and multidisciplinary interventions should be developed and tested using evidence-based principles to improve medication adherence and health outcomes in older adults. [ABSTRACT FROM AUTHOR]

Medication adherence to oral cancer therapy is a critical component to achieving optimal patient outcomes. As the US population ages, growing numbers of patients will be prescribed oral cancer therapy regimens, highlighting the need for innovative and scalable solutions. Clinical pharmacists offer tremendous promise to help patients improve their adherence to oral cancer therapy. Moreover, addition of oral chemotherapy to Centers for Medicare & Medicaid Services (CMS) medication adherence quality measures has the potential to improve care and result in better therapeutic outcomes with fewer costs for patients and payers. Future research is needed to test the use of pharmacist-managed interventions to improve adherence to oral cancer therapy. [ABSTRACT FROM AUTHOR]

Objectives To assess the association between multiple pharmacy use and medication adherence and potential drug-drug interactions ( DDIs) in older adults. Design Cross-sectional propensity score-weighted analysis. Setting 2009 claims data. Participants A nationally representative sample of 926,956 Medicare Part D beneficiaries aged 65 and older continuously enrolled in fee-for-service Medicare and Part D that year who filled one or more prescriptions at a community retail or mail order pharmacy. Measurements Multiple pharmacy use was defined as concurrent (overlapping time periods) or sequential use (non-overlapping time periods) of ≥2 pharmacies in the year. Medication adherence was calculated using a proportion of days covered of 0.80 or greater for eight therapeutic categories (beta-blockers, renin angiotensin system antagonists, calcium channel blockers, statins, sulfonylureas, biguanides (metformin), thiazolidinediones, and dipeptidyl peptidase- IV inhibitors). Potential DDIs arising from use of certain drugs across a broad set of classes were defined as the concurrent filling of two interacting drugs. Results Overall, 38.1% of the sample used multiple pharmacies. Those using multiple pharmacies (concurrently or sequentially) consistently had higher adjusted odds of nonadherence (ranging from 1.10 to 1.31, P < .001) across all chronic medication classes assessed after controlling for sociodemographic, health status, and access to care factors than single pharmacy users. The adjusted predicted probability of exposure to a DDI was also slightly higher for those using multiple pharmacies concurrently (3.6%) than for single pharmacy users (3.2%, adjusted odds ratio ( AOR) = 1.11, 95% confidence interval ( CI) = 1.08-1.15) but lower in individuals using multiple pharmacies sequentially (2.8%, AOR = 0.85, 95% CI = 0.81-0.91). Conclusions Filling prescriptions at multiple pharmacies was associated with lower medication adherence across multiple chronic medications and a small but statistically significant greater likelihood of DDIs in concurrent pharmacy users. [ABSTRACT FROM AUTHOR]

The article looks at a study on the effect of daily pill bottle alarms combined with individual or partner feedback reports on statin medication adherence. Topics covered include measurement of adherence as a key issue in implementing any adherence intervention, GlowCap bottle as medication adherence measure, and Medication Event Monitoring System as a gold standard measure of medication adherence in trial settings.

A letter to the editor is presented discussing a study on medication discrepancies and shared decision-making in the medical care of older adults.

A letter to the editor is presented which is concerned with topics which were discussed at a methodology workshop titled "Pills and Ills: Methodologic Issues in Pharmacologic Research" which was presented at the 2013 American Geriatrics Society Annual Scientific Meeting.

A letter to the editor is presented which focuses on medication nonadherence.

A response from the authors of the article "Medication Nonadherence: A Diagnosable and Treatable Medical Condition" in the 2013 issue is presented.

The authors discuss the problems and barriers associated with medication nonadherence and state that despite the widespread prevalence and cost of medication nonadherence, it is undetected in different health care settings. The author also state that most clinicians do not have proper training for screening medication nonadherence. The author further state that there is a strong demand for improving the quality of care delivered, including medication adherence.