Literature DB >> 27452191

Creating Unidimensional Global Measures of Physician Practice Quality Based on Health Insurance Claims Data.

Grant R Martsolf1, Adam C Carle2, Dennis P Scanlon3.   

Abstract

OBJECTIVE: To explore the extent to which commonly used claims-based process quality indicators can be used to create an internally valid global composite measure of physician practice quality. DATA SOURCES: Health insurance claims data (October 2007-May 2010) from 134 physician practices in Seattle, WA. STUDY
DESIGN: We use confirmatory and exploratory factor analysis to develop theory- and empirically driven internally valid composite measures based on 19 quality indicators. DATA COLLECTION
METHODS: Health insurance claims data from nine insurance companies and self-funded employers were collected and aggregated by third-party organization. PRINCIPAL
FINDINGS: Our results did not support a single global measure using the entire set of quality indicators. We did identify an acceptable multidimensional model (RMSEA = 0.059; CFI = 0.934; TLI = 0.910). The four dimensions in our data were diabetes, depression, preventive care, and generic drug prescribing.
CONCLUSIONS: Our study demonstrates that commonly used process indicators can be used to create a small set of useful composite measures. However, the lack of an internally valid single unidimensional global measure has important implications for policy approaches meant to improve quality by rewarding "high-quality physicians." © Health Research and Educational Trust.

Entities:  

Keywords:  Quality measurement; composite measurement; physician practices

Mesh:

Year:  2016        PMID: 27452191      PMCID: PMC5441486          DOI: 10.1111/1475-6773.12533

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  20 in total

1.  How robust are hospital ranks based on composite performance measures?

Authors:  Rowena Jacobs; Maria Goddard; Peter C Smith
Journal:  Med Care       Date:  2005-12       Impact factor: 2.983

2.  Statistical methodology for classifying units on the basis of multiple-related measures.

Authors:  Armando Teixeira-Pinto; Sharon-Lise T Normand
Journal:  Stat Med       Date:  2008-04-30       Impact factor: 2.373

3.  Estimating a composite measure of hospital quality from the Hospital Compare database: differences when using a Bayesian hierarchical latent variable model versus denominator-based weights.

Authors:  Michael Shwartz; Justin Ren; Erol A Peköz; Xin Wang; Alan B Cohen; Joseph D Restuccia
Journal:  Med Care       Date:  2008-08       Impact factor: 2.983

4.  The comprehensive care project: measuring physician performance in ambulatory practice.

Authors:  Eric S Holmboe; Weifeng Weng; Gerald K Arnold; Sherrie H Kaplan; Sharon-Lise Normand; Sheldon Greenfield; Sarah Hood; Rebecca S Lipner
Journal:  Health Serv Res       Date:  2010-09-01       Impact factor: 3.402

5.  The unreliability of individual physician "report cards" for assessing the costs and quality of care of a chronic disease.

Authors:  T P Hofer; R A Hayward; S Greenfield; E H Wagner; S H Kaplan; W G Manning
Journal:  JAMA       Date:  1999-06-09       Impact factor: 56.272

6.  Validly interpreting patients' reports: using bifactor and multidimensional models to determine whether surveys and scales measure one or more constructs.

Authors:  Adam C Carle; Robert Weech-Maldonado
Journal:  Med Care       Date:  2012-09       Impact factor: 2.983

7.  Improving the reliability of physician performance assessment: identifying the "physician effect" on quality and creating composite measures.

Authors:  Sherrie H Kaplan; John L Griffith; Lori L Price; L Gregory Pawlson; Sheldon Greenfield
Journal:  Med Care       Date:  2009-04       Impact factor: 2.983

8.  A three-part model for measuring diabetes care in physician practice.

Authors:  Rebecca S Lipner; Weifeng Weng; Gerald K Arnold; F Daniel Duffy; Lorna A Lynn; Eric S Holmboe
Journal:  Acad Med       Date:  2007-10       Impact factor: 6.893

9.  Benchmarking physician performance: reliability of individual and composite measures.

Authors:  Sarah Hudson Scholle; Joachim Roski; John L Adams; Daniel L Dunn; Eve A Kerr; Donna Pillittere Dugan; Roxanne E Jensen
Journal:  Am J Manag Care       Date:  2008-12       Impact factor: 2.229

10.  Composite health plan quality scales.

Authors:  Todd Caldis
Journal:  Health Care Financ Rev       Date:  2007
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  1 in total

1.  Comparison of Approaches for Aggregating Quality Measures in Population-based Payment Models.

Authors:  Alex McDowell; Christina A Nguyen; Michael E Chernew; Kevin N Tran; J Michael McWilliams; Bruce E Landon; Mary Beth Landrum
Journal:  Health Serv Res       Date:  2018-08-22       Impact factor: 3.402

  1 in total

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