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Reducing Time-dependent Bias in Estimates of the Attributable Cost of Health Care–associated Methicillin-resistant Staphylococcus aureus Infections

A Comparison of Three Estimation Strategies

Nelson, Richard E. PhD*,†; Samore, Matthew H. MD*,†; Jones, Makoto MD*,†; Greene, Tom PhD; Stevens, Vanessa W. PhD*,‡; Liu, Chuan-Fen PhD§,∥; Graves, Nicholas PhD; Evans, Martin F. MD#,**; Rubin, Michael A. MD, PhD*,†

doi: 10.1097/MLR.0000000000000403
Original Articles

Background: Previous estimates of the excess costs due to health care–associated infection (HAI) have scarcely addressed the issue of time-dependent bias.

Objective: We examined time-dependent bias by estimating the health care costs attributable to an HAI due to methicillin-resistant Staphylococcus aureus (MRSA) using a unique dataset in the Department of Veterans Affairs (VA) that makes it possible to distinguish between costs that occurred before and after an HAI. In addition, we compare our results to those from 2 other estimation strategies.

Methods: Using a historical cohort study design to estimate the excess predischarge costs attributable to MRSA HAIs, we conducted 3 analyses: (1) conventional, in which costs for the entire inpatient stay were compared between patients with and without MRSA HAIs; (2) post-HAI, which included only costs that occurred after an infection; and (3) matched, in which costs for the entire inpatient stay were compared between patients with an MRSA HAI and subset of patients without an MRSA HAI who were matched based on the time to infection.

Results: In our post-HAI analysis, estimates of the increase in inpatient costs due to MRSA HAI were $12,559 (P<0.0001) and $24,015 (P<0.0001) for variable and total costs, respectively. The excess variable and total cost estimates were 33.7% and 31.5% higher, respectively, when using the conventional methods and 14.6% and 11.8% higher, respectively, when using matched methods.

Conclusions: This is the first study to account for time-dependent bias in the estimation of incremental per-patient health care costs attributable to HAI using a unique dataset in the VA. We found that failure to account for this bias can lead to overestimation of these costs. Matching on the timing of infection can reduce this bias substantially.

*Veterans Affairs Salt Lake City Health Care System

Department of Internal Medicine, University of Utah School of Medicine

Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT

§Veterans Affairs Puget Sound Health Care System

Department of Health Services, University of Washington, Seattle, WA

School of Public Health, Queensland University, Brisbane, Australia

#Lexington Veterans Affairs Medical Center

**Department of Internal Medicine, University of Kentucky, Lexington, KY

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Supported by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Health Services Research and Development Service (CDA 11-210) with R.E.N. as the principal investigator and the Centers for Disease Control and Prevention, Safety and Healthcare Epidemiology Prevention Research Development Program (contract number 200-2011-42039) with M.H.S. as the principal investigator.

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government. The authors declare no conflict of interest.

Reprints: Richard E. Nelson, PhD, 500 Foothill Blvd, Salt Lake City, UT 84148. E-mail:

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