infection control & hospital epidemiology october 2017, vol. 38, no. 10 original article
Can National Healthcare-Associated Infections (HAIs) Data Differentiate Hospitals in the United States?
Max Masnick, PhD;1 Daniel J. Morgan, MD, MS;1,2 John D. Sorkin, MD, PhD;3 Mark D. Macek, DDS, DrPH;4 Jessica P. Brown, PhD;1 Penny Rheingans, PhD;5 Anthony D. Harris, MD, MPH1 for the CDC Prevention Epicenter Program
objective. 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.
design. Secondary analysis of publicly available HAI data for calendar year 2013.
methods. 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).
results. 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).
conclusions. 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
Healthcare-associated infection (HAI) data are reported by US hospitals to the Centers for Disease Control and Prevention (CDC) via the National Healthcare Safety Network (NHSN). These data are then reported to the public by the Centers for Medicare and Medicaid Services (CMS), with the goal of helping patients decide which hospitals to utilize. The CMS website, Hospital Compare (
http://medicare.gov/hospital compare), allows the public to search for hospitals in a geographic region, and to then compare these hospitals based on a variety of hospital quality data including HAIs. The CMS provides data for the following HAIs: (1) catheter-
associated urinary tract infection (CAUTI); (2) central line- associated bloodstream infection (CLABSI); (3) surgical site infection (SSI), separately for colon surgery and hysterectomy; (4) methicillin-resistant Staphylococcus aureus (MRSA) blood- stream infection; and (5) Clostridium difficile infection (CDI).
The CMS uses standardized infection ratios (SIRs) to
account for differences in underlying patient factors that increase HAI risk and can differ among hospitals. These SIRs are calculated by dividing the number of observed infections by the predicted number of infections for that hospital (see the Discussion section for details). The predicted numbers of infections are based on a limited set of risk characteristics that differ by HAI.1 Public reporting of HAI data requires substantial resources
from hospitals2 as well as additional resources from CDC and CMS to aggregate and publish these data. However, it is not known whether these data are useful in differentiating hospi- tals. For example, are there substantial differences in CAUTI rates among the hospitals in the Baltimore, Maryland, metro- politan area? If all hospitals in Baltimore have very low CAUTI rates, the CAUTI data are minimally informative when
Affiliations: 1. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland; 2. Veterans Affairs
Maryland Healthcare System, Baltimore, Maryland; 3. Veterans Affairs Maryland Healthcare System Geriatrics Research, Education, and Clinical Center, Baltimore, Maryland; 4. University of Maryland School of Dentistry, Baltimore, Maryland; 5. Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, Maryland.
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2017/3810-0005. DOI: 10.1017/ice.2017.179 Received February 20, 2017; accepted July 11, 2017
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