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Cambridge University Press, Infection Control and Hospital Epidemiology, 02(37), p. 182-187

DOI: 10.1017/ice.2015.260

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Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website

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This paper is available in a repository.

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Abstract

BACKGROUNDPublic reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex.OBJECTIVETo 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.METHODSWe 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.RESULTSParticipants (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%).CONCLUSIONSCurrent 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.Infect. Control Hosp. Epidemiol. 2016;37(2):182–187