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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.
Masnick, Max; Morgan, Daniel J; Sorkin, John D; Kim, Elizabeth; Brown, Jessica P; Rheingans, Penny; Harris, Anthony D.
Afiliação
  • Masnick M; 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
  • Morgan DJ; 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
  • Sorkin JD; 3Veterans Affairs Maryland Healthcare System Geriatrics Research,Education, and Clinical Center,Baltimore,Maryland.
  • Kim E; 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
  • Brown JP; 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
  • Rheingans P; 4Department of Computer Science and Electrical Engineering,University of Maryland Baltimore County,Baltimore,Maryland.
  • Harris AD; 1Department of Epidemiology and Public Health,University of Maryland School of Medicine,Baltimore,Maryland.
Infect Control Hosp Epidemiol ; 37(2): 182-7, 2016 Feb.
Article em En | MEDLINE | ID: mdl-26592554
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Infecções Urinárias / Conhecimentos, Atitudes e Prática em Saúde / Infecção Hospitalar / Infecções Relacionadas a Cateter Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Infecções Urinárias / Conhecimentos, Atitudes e Prática em Saúde / Infecção Hospitalar / Infecções Relacionadas a Cateter Idioma: En Ano de publicação: 2016 Tipo de documento: Article