Reducing Cardiovascular Disparities Through Community-Engaged Implementation Research: A National Heart, Lung, and Blood Institute Workshop Report.

Cardiovascular disparities remain pervasive in the United States. Unequal disease burden is evident among population groups based on sex, race, ethnicity, socioeconomic status, educational attainment, nativity, or geography. Despite the significant declines in cardiovascular disease mortality rates in all demographic groups during the last 50 years, large disparities remain by sex, race, ethnicity, and geography. Recent data from modeling studies, linked micromap plots, and small-area analyses also demonstrate prominent variation in cardiovascular disease mortality rates across states and counties, with an especially high disease burden in the southeastern United States and Appalachia. Despite these continued disparities, few large-scale intervention studies have been conducted in these high-burden populations to examine the feasibility of reducing or eliminating cardiovascular disparities. To address this challenge, on June 22 and 23, 2017, the National Heart, Lung, and Blood Institute convened experts from a broad range of biomedical, behavioral, environmental, implementation, and social science backgrounds to summarize the current state of knowledge of cardiovascular disease disparities and propose intervention strategies aligned with the National Heart, Lung, and Blood Institute mission. This report presents the themes, challenges, opportunities, available resources, and recommended actions discussed at the workshop.

Health information technology and hospital patient safety: a conceptual model to guide research.

BACKGROUND: The literature indicates that health information technology (IT) use may lead to some gains in the quality and safety of care in some situations but provides little insight into this variability in the results that has been found. The inconsistent findings point to the need for a conceptual model that will guide research in sorting out the complex relationships between health IT and the quality and safety of care. METHODS: A conceptual model was developed that describes how specific health IT functions could affect different types of inpatient safety errors and that include contextual factors that influence successful health IT implementation. The model was applied to a readily available patient safety measure and nationwide data (2009 AHA Annual Survey Information Technology Supplement and 2009 Healthcare Cost and Utilization Project State Inpatient Databases). FINDINGS: The model was difficult to operationalize because (1) available health IT adoption data did not characterize health IT features and extent of usage, and (2) patient safety measures did not elucidate the process failures leading to safety-related outcomes. The sample patient safety measure--Postoperative Physiologic and Metabolic Derangement Rate--was not significantly related to self-reported health IT capabilities when adjusted for hospital structural characteristics. CONCLUSION: These findings illustrate the critical need for collecting data that are germane to health IT and the possible mechanisms by which health IT may affect inpatient safety. Well-defined and sufficiently granular measures of provider's correct use of health IT functions, the contextual factors surrounding health IT use, and patient safety errors leading to health care-associated conditions are needed to illuminate the impact of health IT on patient safety.