Using IT to Improve the Quality of CVD Prevention & Management

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DESCRIPTION (Provided by the Applicant): Electronic medical records (EMR) offer the opportunity to analyze total medical care experience to determine what works and what does not, to identify patterns of care that are more or less effective, and to define the relative short-term and long-term costs and cost effectiveness of various approaches to care. This study will use EMRs in a large health-care system to: 1) identify practice variations in delivery of key CVD preventive and disease management services; 2) relate practice variation to morbid and mortal outcomes over 4-5 years among patients in the clinical practices, and also to variations over time in utilization and costs of medical care; and 3) provide feedback to managers on how guidelines adherence at the practice, health-care team, and system levels relates to morbid and mortal events, and to costs of care. Using the EMR, we will observe all health care utilization and diagnoses among a cohort of adult health plan members of a large integrated care system with at least two years of continuous plan membership prior to January 1, 2005. Observation will continue through mid-2008, providing 4-5 years (2003-2008) of longitudinal data on each individual. Using a person-time methodology that evaluates adherence to prevention and selected CVD management guidelines, we will describe variations at the practice level in CVD prevention and preventive management of patients with hypertension, hyperlipidemia, diabetes, congestive heart failure, and past myocardial infarction. We will relate those variations to morbidity, mortality, and health-care costs over the follow-up period. The estimated sample of 118,000 individuals should produce more than 12,000 major CVD events over the five years of follow-up. Patients without diabetes, hypertension, hyperlipidemia, and prior CVD will be examined separately for preventive services only. Those with prior CVD and related diagnoses will be examined for both preventive and management guidelines adherence. These data will clarify the relationships between evidence-based guidelines adherence and outcomes. That information will then be provided to managers in order to determine its impact on health-care processes and policies.