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BACKGROUND The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method(More)
BACKGROUND The electronic health record (EHR) contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and(More)
OBJECTIVE We conducted this study to investigate the rate of clinically important, extreme weight gain (EWG; ≥7% body weight gain) among all second generation antipsychotic (SGA) users in two large health care systems in the United States. STUDY DESIGN Retrospective observational cohort study. METHODS We used electronic medical record databases of two(More)
BACKGROUND A key question in care of patients with chronic hepatitis C virus (HCV) infection is beginning treatment immediately vs delaying treatment. Risks of mortality and disease progression in "real world" settings are important to assess the implications of delaying HCV treatment. METHODS This was a cohort study of HCV patients identified from 4(More)
Motivating physicians to increase productivity and maximize patient satisfaction may result in conflicted behavior, raising questions about whether one must be sacrificed for the other. To determine if high satisfaction (measured by Press Ganey patient satisfaction survey) can be achieved while maintaining high productivity (measured in McGladrey relative(More)
Heart failure (HF) prevalence is increasing and is among the most costly diseases to society. Early detection of HF would provide the means to test lifestyle and pharmacologic interventions that may slow disease progression and improve patient outcomes. This study used structured and unstructured data from electronic health records (EHR) to predict onset of(More)
Research suggests depression and alcohol misuse are highly prevalent among chronic hepatitis C (CHC) patients, which is of clinical concern. To compare ICD-9 codes for depression and alcohol misuse to validated survey instruments. Among CHC patients, we assessed how well electronic ICD-9 codes for depression and alcohol misuse predicted these disorders(More)
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