A comparative study assessing the incidence and degree of hyperkalemia in patients on angiotensin-converting enzyme inhibitors versus angiotensin-receptor blockers.

Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin-receptor blockers (ARB) are the most commonly prescribed anti-hypertensive medications in the United States, yet whether ACEI or ARB use is associated with a greater risk of hyperkalemia remains uncertain. Using real-world evidence from electronic health records, our study demonstrates that treatment with ACEI is associated with both a higher incidence and greater degree of hyperkalemia than treatment with ARB in adjusted models, especially in patients with chronic kidney disease. Providers should therefore consider this possible difference in hyperkalemia risk when choosing between ACEI and ARB therapy.

Predictive analytics and tailored interventions improve clinical outcomes in older adults: a randomized controlled trial.

This study explored the potential to improve clinical outcomes in patients at risk of moving to the top segment of the cost acuity pyramid. This randomized controlled trial evaluated the impact of a Stepped-Care approach (predictive analytics + tailored nurse-driven interventions) on healthcare utilization among 370 older adult patients enrolled in a homecare management program and using a Personal Emergency Response System. The Control group (CG) received care as usual, while the Intervention group (IG) received Stepped-Care during a 180-day intervention period.

A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care.

This two-arm randomized controlled trial evaluated the impact of a Stepped-Care intervention (predictive analytics combined with tailored interventions) on the healthcare costs of older adults using a Personal Emergency Response System (PERS). A total of 370 patients aged 65 and over with healthcare costs in the middle segment of the cost pyramid for the fiscal year prior to their enrollment were enrolled for the study. During a 180-day intervention period, control group (CG) received standard care, while intervention group (IG) received the Stepped-Care intervention.

Factors Influencing Exercise Engagement When Using Activity Trackers: Nonrandomized Pilot Study.

Background: It is well reported that tracking physical activity can lead to sustained exercise routines, which can decrease disease risk. However, most stop using trackers within a couple months of initial use. The reasons people stop using activity trackers can be varied and personal.

Accuracy of self-reported history of autoimmune disease: A pilot study.

Research associating the increased prevalence of familial autoimmunity with neuropsychiatric disorders is reliant upon the ascertainment of history of autoimmune diseases from relatives. To characterize the accuracy of self-report, we compared self-reported diagnoses of 18 autoimmune diseases using an online self-report questionnaire to the electronic medical record (EMR) diagnoses in 1,013 adult (age 18-70 years) patients of a primary care clinic. For the 11 diseases meeting our threshold observed prevalence, we estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for self-reported diagnoses under the assumption that EMR-based diagnoses were accurate.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

Background: Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied.

Evaluating the Impact of a Web-Based Risk Assessment System (CareSage) and Tailored Interventions on Health Care Utilization: Protocol for a Randomized Controlled Trial.

Background: Soaring health care costs and a rapidly aging population, with multiple comorbidities, necessitates the development of innovative strategies to deliver high-quality, value-based care.

Objective: The goal of this study is to evaluate the impact of a risk assessment system (CareSage) and targeted interventions on health care utilization.

Methods: This is a two-arm randomized controlled trial recruiting 370 participants from a pool of high-risk patients receiving care at a home health agency.