Variations in analytical methodology for estimating costs of hospital-acquired infections: A systematic review

H. Fukuda, J. Lee, Y. Imanaka

研究成果: Contribution to journalReview article査読

18 被引用数 (Scopus)


Quantifying the additional costs of hospital-acquired infections (COHAI) is essential for developing cost-effective infection control measures. The methodological approaches to estimate these costs include case reviews, matched comparisons and regression analyses. The choice of cost estimation methodologies can affect the accuracy of the resulting estimates, however, with regression analyses generally able to avoid the bias pitfalls of the other methods. The objective of this study was to elucidate the distributions and trends in cost estimation methodologies in published studies that have produced COHAI estimates. We conducted systematic searches of peer-reviewed publications that produced cost estimates attributable to hospital-acquired infection in MEDLINE from 1980 to 2006. Shifts in methodologies at 10-year intervals were analysed using Fisher's exact test. The most frequent method of COHAI estimation methodology was multiple matched comparisons (59.6%), followed by regression models (25.8%), and case reviews (7.9%). There were significant increases in studies that used regression models and decreases in matched comparisons through the 1980s, 1990s and post-2000 (P = 0.033). Whereas regression analyses have become more frequently used for COHAI estimations in recent years, matched comparisons are still used in more than half of COHAI estimation studies. Researchers need to be more discerning in the selection of methodologies for their analyses, and comparative analyses are needed to identify more accurate estimation methods. This review provides a resource for analysts to overview the distribution, trends, advantages and pitfalls of the various existing COHAI estimation methodologies.

ジャーナルJournal of Hospital Infection
出版ステータス出版済み - 2 2011

All Science Journal Classification (ASJC) codes

  • 微生物学(医療)
  • 感染症


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