Health Services Research & Managerial Epidemiology (Aug 2017)

Potentially Preventable Hospitalizations and the Burden of Healthcare-Associated Infections

  • Andrea L. Lorden,
  • Luohua Jiang,
  • Tiffany A. Radcliff,
  • Kathleen A. Kelly,
  • Robert L. Ohsfeldt

DOI
https://doi.org/10.1177/2333392817721109
Journal volume & issue
Vol. 4

Abstract

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Background: An estimated 4% of hospital admissions acquired healthcare-associated infections (HAIs) and accounted for $9.8 (USD) billion in direct cost during 2011. In 2010, nearly 140 000 of the 3.5 million potentially preventable hospitalizations (PPHs) may have acquired an HAI. There is a knowledge gap regarding the co-occurrence of these events. Aims: To estimate the period occurrences and likelihood of acquiring an HAI for the PPH population. Methods: Retrospective, cross-sectional study using logistic regression analysis of 2011 Texas Inpatient Discharge Public Use Data File including 2.6 million admissions from 576 acute care hospitals. Agency for Healthcare Research and Quality Prevention Quality Indicator software identified PPH, and existing administrative data identification methodologies were refined for Clostridium difficile infection, central line–associated bloodstream infection, catheter-associated urinary tract infection, and ventilator-associated pneumonia. Odds of acquiring HAIs when admitted with PPH were adjusted for demographic, health status, hospital, and community characteristics. Findings: We identified 272 923 PPH, 14 219 HAI, and 986 admissions with PPH and HAI. Odds of acquiring an HAI for diabetic patients admitted for lower extremity amputation demonstrated significantly increased odds ratio of 2.9 (95% confidence interval: 2.16-3.91) for Clostridium difficile infection. Other PPH patients had lower odds of acquiring HAI compared to non-PPH patients, and results were frequently significant. Conclusions: Clinical implications include increased risk of HAI among diabetic patients admitted for lower extremity amputation. Methodological implications include identification of rare events for inpatient subpopulations and the need for improved codification of HAIs to improve cost and policy analyses regarding allocation of resources toward clinical improvements.