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Combining Multiple Indicators of Clinical Quality

An Evaluation of Different Analytic Approaches

Datos Bibliográficos

ID9101922
AutoresDan Reeves (0000-0001-6377-6859, University of Manchester, autor de correspondencia), David Reeves, Stephen Campbell (0000-0002-2328-4136, University of Manchester, autor de correspondencia), Stephen M Campbell, John Adams (0000-0002-2727-615X), Paul G Shekelle, Evangelos Kontopantelis (0000-0001-6450-5815, University of Manchester, autor de correspondencia), Evan Kontopantelis, Martin Roland (0000-0002-8533-3060, University of Manchester, autor de correspondencia), Martin O Roland
Año2007
Volumen45
Número6
Páginas489-496
Fecha de publicación2007-06-01
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/mlr.0b013e31803bb479
PMID17515775
OpenAlexW1987406862
IdiomaEN
Citas recibidas14
Referencias citadas15

OBJECTIVE: To compare different methods of combining quality indicators scores to produce composite scores that summarize the overall performance of health care providers. METHODS: Five methods for computing a composite quality score were compared: the "All-or-None," the "70% Standard," the "Overall Percentage," the "Indicator Average," and the "Patient Average." The first 2 "criterion-referenced" methods assess the degree to which a provider has reached a threshold for quality of care for each patient (100% or 70%). The remaining "absolute score" methods produce scores representing the proportion of required care successfully provided. Each method was applied to 2 quality indicator datasets, derived from audits of UK family practitioner records. Dataset A included quality indicator data for 1178 patients from 16 family practices covering 23 acute, chronic, and preventative conditions. Dataset B included data on 3285 patients from 60 family practices, covering 3 chronic conditions. RESULTS: The results varied considerably depending on the method of aggregation used, resulting in substantial differences in how providers scored. The results also varied considerably for the 2 datasets. There was more agreement between methods for dataset B, but for dataset A 6 of the 16 practices moved between the top and bottom quartiles depending upon the method used. CONCLUSIONS: Different methods of computing composite quality scores can lead to different conclusions being drawn about both relative and absolute quality among health care providers. Different methods are suited to different types of application. The main advantages and disadvantages of each method are described and discussed

Audit · Health care · Operations management · Quality (philosophy) · Quality management · Quality Score · Quartile · Statistics · Mathematics · Medicine · Patient Satisfaction in Healthcare · Primary Care and Health Outcomes

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Obras citantes distintas14
Citas por año0,78
Intervalo de citas2008 - 2022 (15)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 12
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