Impact on patients' compliance with medication using prepacked blisters for multidrug medical therapy: I-COMPLY Study.

PURPOSE: Studies have supported the use of packaging interventions such as pillboxes or blister packs to improve medication adherence but have not evaluated the efficacy of these interventions in a population of low socioeconomic status. The aim of this study was to assess the effect of home-delivered pill packs on medication adherence in a low-income Black American population with Medicaid insurance. METHODS: This study was an open-label, randomized, controlled trial. The patient population studied included 80 patients followed by primary care physicians at the Cleveland Clinic. Patients were randomized to a study group who received delivery of their multidrug medical therapy, defined as a minimum of 4 medications daily, in prepackaged blisters or a control group who obtained their prescriptions from their routine pharmacy. RESULTS: The primary analysis compared the mean percentage of missed pills between the 2 groups using t-test analysis. The percentage of missed pills in the study group was significantly lower than in the control group (mean [SD]: 3.7% [6.0%] vs 17.4% [16.6%] missed daily pills; P < 0.001). The number of daily missed doses was also significantly lower in the study group (0.3 [0.5] vs 0.7 [0.6]; P = 0.002). Patients were on a mean of 8.1 (SD, 2.3) and 8.1 (SD, 2.6) medications in the study and control groups, respectively (P = 0.96). CONCLUSION: Delivery of prepackaged medications in a low-income Black American community was demonstrated to improve medication adherence. The use of prepackaged blisters for medication home delivery is a model that can be utilized on a larger scale for patients on multidrug medical therapy.

Improving Regional Blood Pressure Control: a Positive Deviance Tiered Intensity Approach.

BACKGROUND: Accelerated translation of real-world interventions for hypertension management is critical to improving cardiovascular outcomes and reducing disparities. OBJECTIVE: To determine whether a positive deviance approach would improve blood pressure (BP) control across diverse health systems. DESIGN: Quality improvement study using 1-year cross sections of electronic health record data over 5 years (2013-2017). PARTICIPANTS: Adults ≥ 18 with hypertension with two visits in 2 years with at least one primary care visit in the last year (N = 114,950 at baseline) to a primary care practice in Better Health Partnership, a regional health improvement collaborative. INTERVENTIONS: Identification of a "positive deviant" and dissemination of this system's best practices for control of hypertension (i.e., accurate/repeat BP measurement; timely follow-up; outreach; standard treatment algorithm; and communication curriculum) using 3 different intensities (low: Learning Collaborative events describing the best practices; moderate: Learning Collaborative events plus consultation when requested; and high: Learning Collaborative events plus practice coaching). MAIN MEASURES: We used a weighted linear model to estimate the pre- to post-intervention average change in BP control (< 140/90 mmHg) for 35 continuously participating clinics. KEY RESULTS: BP control post-intervention improved by 7.6% [95% confidence interval (CI) 6.0-9.1], from 67% in 2013 to 74% in 2017. Subgroups with the greatest absolute improvement in BP control included Medicaid (12.0%, CI 10.5-13.5), Hispanic (10.5%, 95% CI 8.4-12.5), and African American (9.0%, 95% CI 7.7-10.4). Implementation intensity was associated with improvement in BP control (high: 14.9%, 95% CI 0.2-19.5; moderate: 5.2%, 95% CI 0.8-9.5; low: 0.2%, 95% CI-3.9 to 4.3). CONCLUSIONS: Employing a positive deviance approach can accelerate translation of real-world best practices into care across diverse health systems in the context of a regional health improvement collaborative (RHIC). Using this approach within RHICs nationwide could translate to meaningful improvements in cardiovascular morbidity and mortality.

Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model.

BACKGROUND: Progression to diabetes mellitus (DM) is variable and the screening time interval not well defined. The American Diabetes Association and US Preventive Services Task Force suggest screening every 3 years, but evidence is limited. The objective of the study was to develop a model to predict the probability of developing DM and suggest a risk-based screening interval. METHODS: We included non-diabetic adult patients screened for DM in the Cleveland Clinic Health System if they had at least two measurements of glycated hemoglobin (HbA1c), an initial one less than 6.5% (48 mmol/mol) in 2008, and another between January, 2009 and December, 2013. Cox proportional hazards models were created. The primary outcome was DM defined as HbA1C greater than 6.4% (46 mmol/mol). The optimal rescreening interval was chosen based on the predicted probability of developing DM. RESULTS: Of 5084 participants, 100 (4.4%) of the 2281 patients with normal HbA1c and 772 (27.5%) of the 2803 patients with prediabetes developed DM within 5 years. Factors associated with developing DM included HbA1c (HR per 0.1 units increase 1.20; 95%CI, 1.13-1.27), family history (HR 1.31; 95%CI, 1.13-1.51), smoking (HR 1.18; 95%CI, 1.03-1.35), triglycerides (HR 1.01; 95%CI, 1.00-1.03), alanine aminotransferase (HR 1.07; 95%CI, 1.03-1.11), body mass index (HR 1.06; 95%CI, 1.01-1.11), age (HR 0.95; 95%CI, 0.91-0.99) and high-density lipoproteins (HR 0.93; 95% CI, 0.90-0.95). Five percent of patients in the highest risk tertile developed DM within 8 months, while it took 35 months for 5% of the middle tertile to develop DM. Only 2.4% percent of the patients in the lowest tertile developed DM within 5 years. CONCLUSION: A risk prediction model employing commonly available data can be used to guide screening intervals. Based on equal intervals for equal risk, patients in the highest risk category could be rescreened after 8 months, while those in the intermediate and lowest risk categories could be rescreened after 3 and 5 years respectively.