Hypertension screening, prevalence, treatment, and control at a large private hospital in Kampala, Uganda: A retrospective analysis.

Adult hypertension prevalence in Uganda is 27%, but only 8% are aware of their diagnosis, accordingly treatment and control levels are limited. The private sector provides at least half of care nationwide, but little is known about its effectiveness in hypertension control. We analyzed clinical data from 39 235 outpatient visits among 17 777 adult patients from July 2017 to August 2018 at Uganda's largest private hospital.

Machine Learning Methods for Precision Medicine Research Designed to Reduce Health Disparities: A Structured Tutorial.

Precision medicine research designed to reduce health disparities often involves studying multi-level datasets to understand how diseases manifest disproportionately in one group over another, and how scarce health care resources can be directed precisely to those most at risk for disease. In this article, we provide a structured tutorial for medical and public health researchers on the application of machine learning methods to conduct precision medicine research designed to reduce health disparities. We review key terms and concepts for understanding machine learning papers, including supervised and unsupervised learning, regularization, cross-validation, bagging, and boosting.

Multiple chronic conditions at a major urban health system: a retrospective cross-sectional analysis of frequencies, costs and comorbidity patterns.

Objective: To (1) examine the burden of multiple chronic conditions (MCC) in an urban health system, and (2) propose a methodology to identify subpopulations of interest based on diagnosis groups and costs.

Design: Retrospective cross-sectional study.

Setting: Mount Sinai Health System, set in all five boroughs of New York City, USA.

Satellite images and machine learning can identify remote communities to facilitate access to health services.

Objective: Community health systems operating in remote areas require accurate information about where people live to efficiently provide services across large regions. We sought to determine whether a machine learning analyses of satellite imagery can be used to map remote communities to facilitate service delivery and planning.

Materials And Methods: We developed a method for mapping communities using a deep learning approach that excels at detecting objects within images.

Machine Learning for Health Services Researchers.

Background: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.

Objective: We provide a high-level overview of machine learning for healthcare outcomes researchers and decision makers.

Methods: We introduce key concepts for understanding the application of machine learning methods to healthcare outcomes research.

Assessment of Risk of Harm Associated With Intensive Blood Pressure Management Among Patients With Hypertension Who Smoke: A Secondary Analysis of the Systolic Blood Pressure Intervention Trial.

Importance: The randomized Systolic Blood Pressure Intervention Trial (SPRINT) showed that lowering systolic blood pressure targets for adults with hypertension reduces cardiovascular morbidity and mortality in general. However, whether the overall benefit from intensive blood pressure control masks important heterogeneity in risk is unknown.

Objective: To test the hypothesis that the overall benefit observed in SPRINT masked important heterogeneity in risk from intensive blood pressure control.