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Infect Control Hosp Epidemiol. 2011 Aug;32(8):775-83. doi: 10.1086/660874.

Use of Medicare claims to rank hospitals by surgical site infection risk following coronary artery bypass graft surgery.

Author information

  • 1Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA. sshuang@uci.edu

Abstract

OBJECTIVE:

To evaluate whether longitudinal insurer claims data allow reliable identification of elevated hospital surgical site infection (SSI) rates.

DESIGN:

We conducted a retrospective cohort study of Medicare beneficiaries who underwent coronary artery bypass grafting (CABG) in US hospitals performing at least 80 procedures in 2005. Hospitals were assigned to deciles by using case mix-adjusted probabilities of having an SSI-related inpatient or outpatient claim code within 60 days of surgery. We then reviewed medical records of randomly selected patients to assess whether chart-confirmed SSI risk was higher in hospitals in the worst deciles compared with the best deciles.

PARTICIPANTS:

Fee-for-service Medicare beneficiaries who underwent CABG in these hospitals in 2005.

RESULTS:

We evaluated 114,673 patients who underwent CABG in 671 hospitals. In the best decile, 7.8% (958/12,307) of patients had an SSI-related code, compared with 24.8% (2,747/11,068) in the worst decile ([Formula: see text]). Medical record review confirmed SSI in 40% (388/980) of those with SSI-related codes. In the best decile, the chart-confirmed annual SSI rate was 3.2%, compared with 9.4% in the worst decile, with an adjusted odds ratio of SSI of 2.7 (confidence interval, 2.2-3.3; [Formula: see text]) for CABG performed in a worst-decile hospital compared with a best-decile hospital.

CONCLUSIONS:

Claims data can identify groups of hospitals with unusually high or low post-CABG SSI rates. Assessment of claims is more reproducible and efficient than current surveillance methods. This example of secondary use of routinely recorded electronic health information to assess quality of care can identify hospitals that may benefit from prevention programs.

PMID:
21768761
[PubMed - indexed for MEDLINE]
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