Public reporting of health care-associated infections (HAIs): approach to choosing HAI measures

Infect Control Hosp Epidemiol. 2011 Aug;32(8):768-74. doi: 10.1086/660873.

Abstract

Objective: To develop a method for selecting health care-associated infection (HAI) measures for public reporting.

Context: HAIs are common, serious, and costly adverse outcomes of medical care that affect 2 million people in the United States annually. Thirty-seven states have introduced or passed legislation requiring public reporting of HAI measures. State legislation varies widely regarding which HAIs to report, how the data are collected and reported, and public availability of results.

Design: The Maryland Health Care Commission developed an HAI Technical Advisory Committee (TAC) that consisted of a group of experts in the field of healthcare epidemiology, infection prevention and control (IPC), and public health. This group reviewed public reporting systems in other states, surveyed Maryland hospitals to determine the current state of IPC programs, performed a literature review on HAI measures, and developed six criteria for ranking the measures: impact, improvability, inclusiveness, frequency, functionality, and feasibility. The committee and experts in the field then ranked each of 18 proposed HAI measures. A composite score was determined for each measure.

Results: Among outcome measures, the rate of central line-associated bloodstream infections ranked highest, followed by the rate of post-coronary artery bypass grafting surgical-site infections. Among process measures, perioperative antimicrobial prophylaxis, compliance with central-line bundles, compliance with hand hygiene, and healthcare-worker influenza vaccination ranked highest.

Conclusions: Our qualitative criteria facilitated consensus on the HAI TAC and provided a useful framework for public reporting of HAI measures. Validation will be important for such approaches to be supported by the scientific community.

MeSH terms

  • Advisory Committees
  • Cross Infection / epidemiology*
  • Health Care Surveys
  • Hospitals / statistics & numerical data*
  • Humans
  • Maryland / epidemiology
  • Outcome and Process Assessment, Health Care / methods*
  • Risk Management / methods*
  • Surveys and Questionnaires