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Rethinking standardised infection rates and risk adjustment in the COVID-19 era
  1. Hojjat Salmasian1,2,
  2. Jennifer Beloff1,
  3. Andrew Resnick1,
  4. Chanu Rhee1,3,4,
  5. Meghan A Baker1,3,4,
  6. Michael Klompas1,3,4,
  7. Marc P Pimentel1,5
  1. 1 Department of Quality and Safety, Brigham and Women's Hospital, Boston, Massachusetts, USA
  2. 2 Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  3. 3 Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
  4. 4 Infectious Diseases Division, Brigham and Women's Hospital, Boston, Massachusetts, USA
  5. 5 Division of Anesthesiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
  1. Correspondence to Dr Hojjat Salmasian, Department of Quality and Safety, Brigham and Women's Hospital, Boston, MA 02115, USA; hsalmasian{at}BWH.HARVARD.EDU

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The COVID-19 pandemic has resulted in drastic changes in hospitals’ practices and their case mix. This has a direct impact on the framework used for reporting and risk-adjusting healthcare-associated infections (HAI), such as catheter-associated urinary tract infections (CAUTI) and central line-associated bloodstream infections. Metrics related to HAIs are incorporated into public and private ranking programmes for hospitals, including the Hospital Compare programme by the Center for Medicare and Medicaid Services (CMS), the Leapfrog Hospital Safety Grade, and Vizient’s Quality and Accountability Study. While the importance of preventing these infections is widely recognised, appropriately risk-adjusting HAI rates continue to be a challenge and source of debate.1 2 We believe that the changes wrought in hospitals by the COVID-19 pandemic provide a fresh opportunity to rethink our frameworks for measuring and benchmarking HAIs.

Measuring the unadjusted incidence of HAIs is not equitable, as the risk of infection varies widely between hospitals depending on the patients they serve and the services they offer—healthcare facilities that care for older or more complex patients are likely to have higher rates of HAIs compared with facilities that serve younger patients with less complex disorders, even if they implement the same rigorous infection control measures. To help make fair comparisons, the Centers for Disease Control and Prevention (CDC) calculates a standardised infection rate (SIR) for each facility based on the presumed characteristics of their patients and the type of services being provided. To this end, hospitals submit their observed HAI cases, as well as data on the population at risk (ie, the denominator) for risk adjustment, via the National Healthcare Safety Network (NHSN). An elaborate framework is used for risk adjustment of each HAI. For example, CAUTI risk adjustment is based on the number of catheter-days in each type of hospital unit (medical intensive care, medical/surgical …

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  • Correction notice The article has been corrected since it was pusblished online first. The order of authorship has changed, co-author Marc P Pimentel has been placed at the end in the order.

  • Contributors HS drafted the initial version of the manuscript. All authors revised the manuscript and contributed to the final version.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.