Objectives. To determine whether a community health worker (CHW) intervention improved outcomes in a low-income population with multiple chronic conditions. Methods. We conducted a single-blind, randomized clinical trial in Philadelphia, Pennsylvania (2013–2014). Participants (n = 302) were high-poverty neighborhood residents, uninsured or publicly insured, and diagnosed with 2 or more chronic diseases (diabetes, obesity, tobacco dependence, hypertension). All patients set a disease-management goal. Patients randomly assigned to CHWs also received 6 months of support tailored to their goals and preferences. Results. Support from CHWs (vs goal-setting alone) led to improvements in several chronic diseases (changes in glycosylated hemoglobin: −0.4 vs 0.0; body mass index: −0.3 vs −0.1; cigarettes per day: −5.5 vs −1.3; systolic blood pressure: −1.8 vs −11.2; overall P = .08), self-rated mental health (12-item Short Form survey; 2.3 vs −0.2; P = .008), and quality of care (Consumer Assessment of Healthcare Providers and Systems; 62.9% vs 38%; P < .001), while reducing hospitalization at 1 year by 28% (P = .11). There were no differences in patient activation or self-rated physical health. Conclusions. A standardized CHW intervention improved chronic disease control, mental health, quality of care, and hospitalizations and could be a useful population health management tool for health care systems. Trial Registration. clinicaltrials.gov identifier: NCT01900470.

Purpose The number of novel oral anticancer agents is increasing, but financial barriers may limit access. We examined associations between out-of-pocket (OOP) costs and reduced and/or delayed treatment initiation. Methods This retrospective claims-based study used 2014 to 2015 data from a large, proprietary, integrated database and included Medicare and commercial insurance enrollees with a new, adjudicated prescription for any of 38 oral anticancer agents. We examined rates of claim reversal (failure to purchase approved prescription), delayed initiation (reversal with subsequent fill of same agent within 90 days after adjudication), and abandonment (reversal with no fill of same agent within 90 days after adjudication) for the index oral anticancer agent. We also examined whether patients filled any alternate oral, injectable, or infusible anticancer agent within 90 days. Logistic regressions controlled for sociodemographic, clinical, and treatment characteristics to estimate adjusted rates. Results Among the final sample (N = 38,111), risk-adjusted rates of claim reversal ranged from 13% to 67%, increasing with higher OOP costs. Although the abandonment rate was 18% overall, risk-adjusted rates were higher in greater OOP cost categories (10.0% for ≤ $10 group v 13.5% for $50.01 to $100 group, 31.7% for $100.01 to $500 group, 41.0% for $500.01 to $2,000 group, and 49.4% for > $2,000 group; P < .001 compared with ≤ $10 group). Rates remained similar after accounting for use of alternate oral, injectable, or infusible anticancer agents. Delayed initiation was also more frequent for higher OOP cost categories (3% in ≤ $10 group v 18% in > $2,000 group; P < .001). Sensitivity and subgroup analyses by insurance type, pharmacy type, sex, and indication identified similar associations. Conclusion Higher OOP costs were associated with higher rates of oral prescription abandonment and delayed initiation across cancers. Fiscally sustainable strategies are needed to improve patient access to cancer medications.

Upstream interventions – e.g. housing programs and community health worker interventions-address socioeconomic and behavioral factors that influence health outcomes across diseases. Studying these types of interventions in clinical trials raises a methodological challenge: how should researchers measure the effect of an upstream intervention in a sample of patients with different diseases? This paper addresses this question using an illustrative protocol of a randomized controlled trial of collaborative-goal setting versus goal-setting plus community health worker support among patients multiple chronic diseases: diabetes, obesity, hypertension and tobacco dependence. At study enrollment, patients met with their primary care providers to select one of their chronic diseases to focus on during the study, and to collaboratively set a goal for that disease. Patients randomly assigned to a community health worker also received six months of support to address socioeconomic and behavioral barriers to chronic disease control. The primary hypothesis was that there would be differences in patients’ selected chronic disease control as measured by HbA1c, body mass index, systolic blood pressure and cigarettes per day, between the goal-setting alone and community health worker support arms. To test this hypothesis, we will conduct a stratum specific multivariate analysis of variance which allows all patients (regardless of their selected chronic disease) to be included in a single model for the primary outcome. Population health researchers can use this approach to measure clinical outcomes across diseases.

Objective Growing interest in collaborative goal-setting has raised questions. First, are patients making the ‘right choices’ from a biomedical perspective? Second, are patients and providers setting goals of appropriate difficulty? Finally, what types of support will patients need to accomplish their goals? We analyzed goals and action plans from a trial of collaborative goal-setting among 302 residents of a high-poverty urban region who had multiple chronic conditions. Methods Patients used a low-literacy aid to prioritize one of their chronic conditions and then set a goal for that condition with their primary care provider. Patients created patient-driven action plans for reaching these goals. Results Patients chose to focus on conditions that were in poor control and set ambitious chronic disease management goals. The mean goal weight loss −16.8lbs (SD 19.5), goal HbA1C reduction was −1.3% (SD 1.7%) and goal blood pressure reduction was −9.8 mmHg (SD 19.2 mmHg). Patient-driven action plans spanned domains including health behavior (58.9%) and psychosocial (23.5%). Conclusions High-risk, low-SES patients identified high priority conditions, set ambitious goals and generate individualized action plans for chronic disease management. Practice implications Practices may require flexible personnel who can support patients using a blend of coaching, social support and navigation.

Purpose: To evaluate what drives respondent perceptions of health system organizational cultural competence.Methods: We estimated associations between survey respondent (n=3506) demographic characteristics, length of employment, position, and place of work and their reported perceptions of institutional culture.Results: In adjusted analyses, respondents self-identifying as non-Hispanic black versus non-Hispanic whites, females versus males, and lesbian/gay/bisexual/transgender/queer versus heterosexuals were significantly less likely to rank the cultural competence of their organization above average.Conclusion: Minorities and women were less likely to rank their organization as culturally competent. Organizational efforts to achieve cultural competency would benefit from measuring this factor to target their efforts.