Association between community-level social risk and spending among Medicare beneficiaries: Implications for social risk adjustment and health equity

IMPORTANCE: Payers are increasingly using approaches to risk adjustment that incorporate community-level measures of social risk with the goal of better aligning value-based payment models with improvements in health equity. OBJECTIVE: To examine the association between community-level social risk and health care spending and explore how incorporating community-level social risk influences risk adjustment for Medicare beneficiaries. DESIGN, SETTING, AND PARTICIPANTS: Using data from a Medicare Advantage plan linked with survey data on self-reported social needs, this cross-sectional study estimated health care spending health care spending was estimated as a function of demographics and clinical characteristics, with and without the inclusion of Area Deprivation Index (ADI), a measure of community-level social risk. The study period was January to December 2019. All analyses were conducted from December 2021 to August 2022. EXPOSURES: Census block group-level ADI. MAIN OUTCOMES AND MEASURES: Regression models estimated total health care spending in 2019 and approximated different approaches to social risk adjustment. Model performance was assessed with overall model calibration (adjusted R2) and predictive accuracy (ratio of predicted to actual spending) for subgroups of potentially vulnerable beneficiaries. RESULTS: Among a final study population of 61 469 beneficiaries (mean [SD] age, 70.7 [8.9] years; 35 801 [58.2%] female; 48 514 [78.9%] White; 6680 [10.9%] with Medicare-Medicaid dual eligibility; median [IQR] ADI, 61 [42-79]), ADI was weakly correlated with self-reported social needs (r = 0.16) and explained only 0.02% of the observed variation in spending. Conditional on demographic and clinical characteristics, every percentile increase in the ADI (ie, more disadvantage) was associated with a $11.08 decrease in annual spending. Directly incorporating ADI into a risk-adjustment model that used demographics and clinical characteristics did not meaningfully improve model calibration (adjusted R2 = 7.90% vs 7.93%) and did not significantly reduce payment inequities for rural beneficiaries and those with a high burden of self-reported social needs. A postestimation adjustment of predicted spending for dual-eligible beneficiaries residing in high ADI areas also did not significantly reduce payment inequities for rural beneficiaries or beneficiaries with self-reported social needs. CONCLUSIONS AND RELEVANCE: In this cross-sectional study of Medicare beneficiaries, the ADI explained little variation in health care spending, was negatively correlated with spending conditional on demographic and clinical characteristics, and was poorly correlated with self-reported social risk factors. This prompts caution and nuance when using community-level measures of social risk such as the ADI for social risk adjustment within Medicare value-based payment programs

Patient, Physician, and Payment Predictors of Statin Adherence

BACKGROUND: Although many patient, physician, and payment predictors of adherence have been described, knowledge of their relative strength and overall ability to explain adherence is limited. OBJECTIVES: To measure the contributions of patient, physician, and payment predictors in explaining adherence to statins RESEARCH DESIGN: Retrospective cohort study using administrative data SUBJECTS: 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey (BCBSNJ) who were newly prescribed a statin cholesterol-lowering medication MEASURES: Adherence to statin medication was measured during the year after the initial prescription, based on proportion of days covered (PDC). The impact of patient, physician, and payment predictors of adherence were evaluated using multivariate logistic regression. The explanatory power of these models was evaluated with C statistics, a measure of the goodness of fit. RESULTS: Overall, 36.4% of patients were fully adherent. Older patient age, male gender, lower neighborhood percent black composition, higher median income, and fewer number of emergency department (ED) visits were significant patient predictors of adherence. Having a statin prescribed by a cardiologist, a patient's primary care physician, or a US medical graduate were significant physician predictors of adherence. Lower copayments also predicted adherence. All of our models had low explanatory power. Multivariate models including patient covariates only had greater explanatory power (C = 0.613) than models with physician variables only (C = 0.566) or copayments only (C = 0.543). A fully specified model had only slightly more explanatory power (C = 0.633) than the model with patient characteristics alone. CONCLUSIONS: Despite relatively comprehensive claims data on patients, physicians, and out-of-pocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.Economic

A Patient-Centered Prescription Drug Label to Promote Appropriate Medication Use and Adherence

BACKGROUND: Patient misunderstanding of prescription drug label instructions is a common cause of unintentional misuse of medication and adverse health outcomes. Those with limited literacy and English proficiency are at greater risk. OBJECTIVE: To test the effectiveness of a patient-centered drug label strategy, including a Universal Medication Schedule (UMS), to improve proper regimen use and adherence compared to a current standard. DESIGN: Two-arm, multi-site patient-randomized pragmatic trial. PARTICIPANTS: English- and Spanish-speaking patients from eight community health centers in northern Virginia who received prescriptions from a central-fill pharmacy and who were 1) ≥30 years of age, 2) diagnosed with type 2 diabetes and/or hypertension, and 3) taking ≥2 oral medications. INTERVENTION: A patient-centered label (PCL) strategy that incorporated evidence-based practices for format and content, including prioritized information, larger font size, and increased white space. Most notably, instructions were conveyed with the UMS, which uses standard intervals for expressing when to take medicine (morning, noon, evening, bedtime). MAIN MEASURES: Demonstrated proper use of a multi-drug regimen; medication adherence measured by self-report and pill count at 3 and 9 months. KEY RESULTS: A total of 845 patients participated in the study (85.6 % cooperation rate). Patients receiving the PCL demonstrated slightly better proper use of their drug regimens at first exposure (76.9 % vs. 70.1 %, p = 0.06) and at 9 months (85.9 % vs. 77.4 %, p = 0.03). The effect of the PCL was significant for English-speaking patients (OR 2.21, 95 % CI 1.13-4.31) but not for Spanish speakers (OR 1.19, 95 % CI 0.63-2.24). Overall, the intervention did not improve medication adherence. However, significant benefits from the PCL were found among patients with limited literacy (OR 5.08, 95 % CI 1.15-22.37) and for those with medications to be taken ≥2 times a day (OR 2.77, 95 % CI 1.17-6.53). CONCLUSIONS: A simple modification to pharmacy-generated labeling, with minimal investment required, can offer modest improvements to regimen use and adherence, mostly among patients with limited literacy and more complex regimens. Trial Registration (ClinicalTrials.gov): NCT00973180, NCT01200849

Encouraging Medicare Advantage Enrollees to Switch to Higher Quality Plans: Assessing the Effectiveness of a ‘‘Nudge’’ Letter

There are considerable quality differences across private Medicare Advantage insurance plans, so it is important that beneficiaries make informed choices. During open enrollment for the 2013 coverage year, the Centers for Medicare & Medicaid Services sent letters to beneficiaries enrolled in low-quality Medicare Advantage plans (i.e., plans rated less than 3 stars for at least 3 consecutive years by Medicare) explaining the stars and encouraging them to reexamine their choices. To understand the effectiveness of these low-cost, behavioral ‘‘nudge’’ letters, we used a beneficiary-level national retrospective cohort and performed multivariate regression analysis of plan selection during the 2013 open enrollment period among those enrolled in plans rated less than 3 stars. Our analysis controls for beneficiary demographic characteristics, health and health care spending risks, the availability of alternative higher rated plan options in their local market, and historical disenrollment rates from the plans. We compared the behaviors of those beneficiaries who received the nudge letters with those who enrolled in similar poorly rated plans but did not receive such letters. We found that beneficiaries who received the nudge letter were almost twice as likely (28.0% [95% confidence interval = 27.7%, 28.2%] vs. 15.3% [95% confidence interval = 15.1%, 15.5%]) to switch to a higher rated plan compared with those who did not receive the letter. White beneficiaries, healthier beneficiaries, and those residing in areas with more high-performing plan choices were more likely to switch plans in response to the nudge. Our findings highlight both the importance and efficacy of providing timely and actionable information to beneficiaries about quality in the insurance marketplace to facilitate informed and value-based coverage decisions

Osteoporosis Telephonic Intervention to Improve Medication Adherence (OPTIMA): A Large Pragmatic Randomized Controlled Trial

Multiple studies demonstrate poor adherence to medications prescribed for chronic illnesses, including osteoporosis, but few interventions have been proven to enhance adherence. We examined the effectiveness of a telephone-based counseling program rooted in motivational interviewing to improve medication adherence for osteoporosis

Can purchasing information be used to predict adherence to cardiovascular medications? An analysis of linked retail pharmacy and insurance claims data

Objective: The use of retail purchasing data may improve adherence prediction over approaches using healthcare insurance claims alone. Design: Retrospective. Setting and participants A cohort of patients who received prescription medication benefits through CVS Caremark, used a CVS Pharmacy ExtraCare Health Care (ECHC) loyalty card, and initiated a statin medication in 2011. Outcome We evaluated associations between retail purchasing patterns and optimal adherence to statins in the 12 subsequent months. Results: Among 11 010 statin initiators, 43% were optimally adherent at 12 months of follow-up. Greater numbers of store visits per month and dollar amount per visit were positively associated with optimal adherence, as was making a purchase on the same day as filling a prescription (p<0.0001 for all). Models to predict adherence using retail purchase variables had low discriminative ability (C-statistic: 0.563), while models with both clinical and retail purchase variables achieved a C-statistic of 0.617. Conclusions: While the use of retail purchases may improve the discriminative ability of claims-based approaches, these data alone appear inadequate for adherence prediction, even with the addition of more complex analytical approaches. Nevertheless, associations between retail purchasing behaviours and adherence could inform the development of quality improvement interventions

Changes in Drug Utilization during a Gap in Insurance Coverage: An Examination of the Medicare Part D Coverage Gap

Jennifer Polinski and colleagues estimated the effect of the "coverage gap" during which US Medicare beneficiaries are fully responsible for drug costs and found that the gap was associated with a doubling in discontinuing essential medications

Medication adherence: A call for action

Poor adherence to efficacious cardiovascular related medications has led to considerable morbidity, mortality, and avoidable health care costs. This paper provides results of a recent think tank meeting in which various stakeholder groups representing key experts from consumers, community health providers, the academic community, decision-making government officials (FDA, NIH, etc), and industry scientists met to evaluate the current status of medication adherence and provide recommendations for improving outcomes. Below, we review the magnitude of the problem of medication adherence, prevalence, impact, and cost. We then summarize proven effective approaches and conclude with a discussion of recommendations to address this growing and significant public health issue of medication non adherence