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  • 标题:Risk Factors for Unexplained Medication Discrepancies During Transitions in Care
  • 作者:Snezana Nena Osorio, MD, MS ; Erika Abramson, MD, MS ; Elizabeth R. Pfoh, MPH
  • 期刊名称:Family Medicine
  • 印刷版ISSN:0742-3225
  • 电子版ISSN:1938-3800
  • 出版年度:2014
  • 卷号:46
  • 期号:8
  • 页码:587-96
  • 出版社:Society of Teachers of Family Medicine
  • 摘要:Background and Objectives: Unexplained discrepancies between patient reported- and physician-prescribed medication regimens are an important source of potential harm to patients after hospital discharge. However, there are limited data available identifying risk factors associated with discrepancies in medications. Our objective was to describe the epidemiology of unexplained medication discrepancies and identify patient risk factors for these discrepancies. Methods: This prospective observational study is part of a larger study conducted from August 2009 to February 2011 in an academic hospital and affiliated office practices. We compared medication lists from hospital discharge, the first ambulatory visit, and patient self-report. Medication lists were gathered from the inpatient and outpatient electronic health records. Demographic and health-related predictor variables were collected through an inpatient survey and chart review. Results: Among 100 patients, 291 unexplained medication discrepancies were identified (31%, n=930). Of these, 98 had high potential for harm (34%). Omitted medications were the most common type of unexplained discrepancy (72%, n=210). In multivariable analysis, having more than five outpatient visits during the previous year and having less than high school education independently predicted a higher number of unexplained discrepancies. Having Medicaid insurance and receiving care from a third-year resident during the first follow-up visit were protective. Conclusions: Unexplained medication discrepancies are common at the first ambulatory visit post-hospital discharge and underscore the need to maintain accurate medication lists across the continuum of care. Individual-level characteristics may potentially be used to identify patients who need special attention for their medication management.
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