Can National Healthcare-Associated Infections (HAIs) Data Differentiate Hospitals in the United States?
Published online by Cambridge University Press: 14 September 2017
To determine whether patients using the Centers for Medicare and Medicaid Services (CMS) Hospital Compare website (http://medicare.gov/hospitalcompare) can use nationally reported healthcare-associated infection (HAI) data to differentiate hospitals.
Secondary analysis of publicly available HAI data for calendar year 2013.
We assessed the availability of HAI data for geographically proximate hospitals (ie, hospitals within the same referral region) and then analyzed these data to determine whether they are useful to differentiate hospitals. We assessed data for the 6 HAIs reported by hospitals to the Centers for Disease Control and Prevention (CDC).
Data were analyzed for 4,561 hospitals representing 88% of registered community and federal government hospitals in the United States. Healthcare-associated infection data are only useful for comparing hospitals if they are available for multiple hospitals within a geographic region. We found that data availability differed by HAI. Clostridium difficile infections (CDI) data were most available, with 82% of geographic regions (ie, hospital referral regions) having >50% of hospitals reporting them. In contrast, 4% of geographic regions had >50% of member hospitals reporting surgical site infections (SSI) for hysterectomies, which had the lowest availability. The ability of HAI data to differentiate hospitals differed by HAI: 72% of hospital referral regions had at least 1 pair of hospitals with statistically different risk-adjusted CDI rates (SIRs), compared to 9% for SSI (hysterectomy).
HAI data generally are reported by enough hospitals to meet minimal criteria for useful comparisons in many geographic locations, though this varies by type of HAI. CDI and catheter-associated urinary tract infection (CAUTI) are more likely to differentiate hospitals than the other publicly reported HAIs.
Infect Control Hosp Epidemiol 2017;38:1167–1171
- Original Articles
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