Using Automated Health Plan Data to Assess Infection Risk from Coronary Artery Bypass Surgery

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Using Automated Health Plan Data to Assess Infection Risk from Coronary Artery Bypass Surgery

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Title: Using Automated Health Plan Data to Assess Infection Risk from Coronary Artery Bypass Surgery
Author: Thompson, Kristin; Dokholyan, Rachel S.; Horan, Teresa C.; Gaynes, Robert P.; Solomon, Steven L.; Platt, Richard; Kleinman, Ken Paul; Livingston, James Michael; Bergman, Andrew L.; Mason, John H.; Sands, Kenneth Eliot Frederick

Note: Order does not necessarily reflect citation order of authors.

Citation: Platt, Richard, Ken Kleinman, Kristin Thompson, Rachel S. Dokholyan, James M. Livingston, Andrew Bergman, John H. Mason, et al. 2002. Using automated health plan data to assess infection risk from coronary artery bypass surgery. Emerging Infectious Diseases 8(12): 1433-1441.
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Abstract: We determined if infection indicators were sufficiently consistent across health plans to allow comparison of hospitals’ risks of infection after coronary artery bypass surgery. Three managed care organizations accounted for 90% of managed care in eastern Massachusetts, from October 1996 through March 1999. We searched automated inpatient and outpatient claims and outpatient pharmacy dispensing files for indicator codes suggestive of postoperative surgical site infection. We reviewed full text medical records of patients with indicator codes to confirm infection status. We compared the hospital-specific proportions of cases with an indicator code, adjusting for health plan, age, sex, and chronic disease score. A total of 536 (27%) of 1,953 patients had infection indicators. Infection was confirmed in 79 (53%) of 149 reviewed records with adequate documentation. The proportion of patients with an indicator of infection varied significantly (p<0.001) between hospitals (19% to 36%) and health plans (22% to 33%). The difference between hospitals persisted after adjustment for health plan and patients’ age and sex. Similar relationships were observed when postoperative antibiotic information was ignored. Automated claims and pharmacy data from different health plans can be used together to allow inexpensive, routine monitoring of indicators of postoperative infection, with the goal of identifying institutions that can be further evaluated to determine if risks for infection can be reduced.
Published Version: http://www.cdc.gov/ncidod/EID/index.htm
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2737830/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:8160850

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