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Adjusting for Patient Characteristics When Analyzing Reports From Patients About Hospital Care

Datos Bibliográficos

ID9104587
AutoresJ Lee Hargraves (0000-0003-2699-4405, Center for Studying Health System Change), Ira B Wilson (0000-0002-0246-738X, autor de correspondencia), Alan M Zaslavsky (0000-0003-1072-6043), Alan Zaslavsky, Cara James, Janice D Walker, Gina Rogers, Paul D Cleary (0000-0001-7527-4354)
Año2001
Volumen39
Número6
Páginas635-641
Fecha de publicación2001-06-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-200106000-00011
PMID11404646
OpenAlexW2086812192
IdiomaEN
Citas recibidas16
Referencias citadas22

OBJECTIVES: To determine which patient characteristics are associated with reports and ratings of hospital care, and to evaluate how adjusting reports and ratings for hospital differences in such variables affects comparisons among hospitals. DESIGN: A telephone survey of a sample of patients hospitalized in 22 hospitals in a single city and a statewide mail survey of hospitalized patients. MEASURES: The surveys assessed: respect for patients' preferences, coordination of care, information exchange between patient and providers, physical care, emotional support, involvement of family and friends, and transition and continuity. The surveys also asked patients to rate their doctors, nurses, and other hospital staff. RESULTS: The variables with the strongest and most consistent associations with patient-reported problems were age and reported health status. Patient gender and education level also sometimes predicted reports and/or ratings. Models including these variables explained only between 3% and 8% of the variation in reports and ratings. CONCLUSIONS: The impact of adjusting for patient characteristics on hospital rankings was small, although a larger impact would be expected when comparing hospitals with more variability in types of patients. Nevertheless, we recommend adjusting at least for the most important predictors, such as age and health status. Such adjustment helps alleviate concerns about bias. It also may be useful to present data for certain groups of patients (ie, medical, surgical, obstetric) separately to facilitate interpretation and quality improvement efforts

Family medicine · Health care · MEDLINE · Patient satisfaction · Healthcare Policy and Management · Medicine · Nursing · Patient Satisfaction in Healthcare · Patient-Provider Communication in Healthcare

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Obras citantes distintas16
Citas por año0,67
Intervalo de citas2002 - 2017 (16)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 14
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