title: Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website.
abstract: BACKGROUND
  Public reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex.
  
  
  OBJECTIVE
  To assess interpretability of HAI data as presented on the Centers for Medicare and Medicaid Services Hospital Compare website among patients who might benefit from access to these data.
  
  
  METHODS
  We randomly selected inpatients at a large tertiary referral hospital from June to September 2014. Participants performed 4 distinct tasks comparing hypothetical HAI data for 2 hospitals, and the accuracy of their comparisons was assessed. Data were presented using the same tabular formats used by Centers for Medicare and Medicaid Services. Demographic characteristics and healthcare experience data were also collected.
  
  
  RESULTS
  Participants (N=110) correctly identified the better of 2 hospitals when given written descriptions of the HAI measure in 72% of the responses (95% CI, 66%-79%). Adding the underlying numerical data (number of infections, patient-time, and standardized infection ratio) to the written descriptions reduced correct responses to 60% (55%-66%). When the written HAI measure description was not informative (identical for both hospitals), 50% answered correctly (42%-58%). When no written HAI measure description was provided and hospitals differed by denominator for infection rate, 38% answered correctly (31%-45%).
  
  
  CONCLUSIONS
  Current public HAI data presentation methods may be inadequate. When presented with numeric HAI data, study participants incorrectly compared hospitals on the basis of HAI data in more than 40% of the responses. Research is needed to identify better ways to convey these data to the public.
authors.affiliation: 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
authors.forename: Max
authors.initials: M
authors.lastname: Masnick
authors.affiliation: 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Morgan
authors.affiliation: 3Veterans Affairs Maryland Healthcare System Geriatrics Research,Education, and Clinical Center,Baltimore,Maryland.
authors.forename: John D
authors.initials: JD
authors.lastname: Sorkin
authors.affiliation: 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Kim
authors.affiliation: 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
authors.forename: Jessica P
authors.initials: JP
authors.lastname: Brown
authors.affiliation: 4Department of Computer Science and Electrical Engineering,University of Maryland Baltimore County,Baltimore,Maryland.
authors.forename: Penny
authors.initials: P
authors.lastname: Rheingans
authors.affiliation: 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
authors.forename: Anthony D
authors.initials: AD
authors.lastname: Harris
mesh_terms: D000328:Adult; D000368:Aged; D055499:Catheter-Related Infections / Q000453:epidemiology / Q000523:psychology*; D014487:Centers for Medicare and Medicaid Services, U.S.; D003428:Cross Infection / Q000453:epidemiology / Q000523:psychology*; D003430:Cross-Sectional Studies; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006761:Hospitals; D006801:Humans; D007297:Inpatients; D020407:Internet; D008297:Male; D008875:Middle Aged; D014481:United States; D014552:Urinary Tract Infections / Q000453:epidemiology / Q000523:psychology*; D055815:Young Adult