automated identification of acute hepatitis b using electronic medical record data to facilitate public health surveillance自动识别急性乙型肝炎使用电子病历数据促进公共卫生监测.pdf

Automated Identification of Acute Hepatitis B Using Electronic Medical Record Data to Facilitate Public Health Surveillance 1,2 3 3 2 2 1,2 Michael Klompas *, Gillian Haney , Daniel Church , Ross Lazarus , Xuanlin Hou , Richard Platt 1 Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, Massachusetts, United States of America, 2 Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 3 Massachusetts Department of Public Health, Boston, Massachusetts, United States of America Abstract Background: Automatic identification of notifiable diseases from electronic medical records can potentially improve the timeliness and completeness of public health surveillance. We describe the development and implementation of an algorithm for prospective surveillance of patients with acute hepatitis B using electronic medical record data. Methods: Initial algorithms were created by adapting Centers for Disease Control and Prevention diagnostic criteria for acute hepatitis B into electronic terms. The algorithms were tested by applying them to ambulatory electronic medical record data spanning 1990 to May 2006. A physician reviewer classified each case identified as acute or chronic infection. Additional criteria were added to algorithms in serial fashion to improve accuracy. The best algorithm was validated by applying it to prospective electronic medical record data from June 2006 through April 2008. Completeness of case capture was assessed by comparison with state health department records. Findings: A final algo