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Costs Attributable to Healthcare-Acquired Infection in Hospitalized Adults and a Comparison of Economic Methods

Roberts, Rebecca R. MD*†; Scott, R. Douglas II PhD; Hota, Bala MD§¶; Kampe, Linda M. MPH, BA, RHIA; Abbasi, Fauzia MPH, MD**; Schabowski, Shari MD*†; Ahmad, Ibrar BS*; Ciavarella, Ginevra G. DrPH, RN††; Cordell, Ralph PhD‡‡; Solomon, Steven L. MD‡‡; Hagtvedt, Reidar PhD§§; Weinstein, Robert A. MD§¶

doi: 10.1097/MLR.0b013e3181ef60a2
Original Article

Background: Hospitals will increasingly bear the costs for healthcare-acquired conditions such as infection. Our goals were to estimate the costs attributable to healthcare-acquired infection (HAI) and conduct a sensitivity analysis comparing analytic methods.

Methods: A random sample of high-risk adults hospitalized in the year 2000 was selected. Measurements included total and variable medical costs, length of stay (LOS), HAI site, APACHE III score, antimicrobial resistance, and mortality. Medical costs were measured from the hospital perspective. Analytic methods included ordinary least squares linear regression and median quantile regression, Winsorizing, propensity score case matching, attributable LOS multiplied by mean daily cost, semi-log transformation, and generalized linear modeling. Three-state proportional hazards modeling was also used for LOS estimation. Attributable mortality was estimated using logistic regression.

Results: Among 1253 patients, 159 (12.7%) developed HAI. Using different methods, attributable total costs ranged between $9310 to $21,013, variable costs were $1581 to $6824, LOS was 5.9 to 9.6 days, and attributable mortality was 6.1%. The semi-log transformation regression indicated that HAI doubles hospital cost. The totals for 159 patients were $1.48 to $3.34 million in medical cost and $5.27 million for premature death. Excess LOS totaled 844 to 1373 hospital days.

Conclusions: Costs for HAI were considerable from hospital and societal perspectives. This suggests that HAI prevention expenditures would be balanced by savings in medical costs, lives saved and available hospital days that could be used by overcrowded hospitals to enhance available services. Our results obtained by applying different economic methods to a single detailed dataset may inform future cost analyses.

From the *Department of Emergency Medicine, John H. Stroger Jr. Hospital of Cook County, Chicago, IL; †Department of Emergency Medicine, Rush University Medical College, Chicago, IL; ‡National Center for Preparedness, Detection and Control of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA; §Division of Infectious Disease, John H. Stroger Jr. Hospital of Cook County, Chicago, IL; ¶Section of Infectious Disease, Rush University Medical College, Chicago, IL; ∥Cermak Health Services, Cook County Health and Hospitals System, Chicago, IL; **Fairfax County Public Safety Occupational Health Center, Fairfax, VA; ††Nursing Services, University of Illinois at Chicago, Chicago, IL; ‡‡Coordinating Center for Health Information and Service, Centers for Disease Control and Prevention, Atlanta, GA; and §§School of Business, University of Alberta, Edmonton, Alberta, Canada.

Supported by a cooperative agreement #U50/CCU515853 between the Division of Healthcare Quality Promotion, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA and the Cook County Bureau of Health Services.

Reprints: Rebecca R. Roberts, MD, Department of Emergency Medicine, John H. Stroger, Jr. Hospital of Cook County, 1900 West Polk Street, 10th floor, Chicago, IL 60612. E-mail: rroberts@ccbh.org.

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© 2010 Lippincott Williams & Wilkins, Inc.