Literature DB >> 9382395

Improving the statistical approach to health care provider profiling.

C L Christiansen1, C N Morris.   

Abstract

This paper reviews and compares existing statistical methods for profiling health care providers. It recommends improvements that are based on the use of better statistical models and the adoption of more realistic, medically based criteria for judging the performance of health care providers. Unlike most profiling methods, the proposed hierarchical models allow the probability of acceptable provider performance to be calculated; thus, they can answer such questions as, "What is the probability that a given hospital's true mortality rate for cardiac surgery patients exceeded 3.33% last year?" The commonly encountered problems of regression-to-the-mean bias and small caseloads can be handled by using hierarchical models to extract more information from profiling data.

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Year:  1997        PMID: 9382395     DOI: 10.7326/0003-4819-127-8_part_2-199710151-00065

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  51 in total

1.  Whom should we profile? Examining diabetes care practice variation among primary care providers, provider groups, and health care facilities.

Authors:  Sarah L Krein; Timothy P Hofer; Eve A Kerr; Rodney A Hayward
Journal:  Health Serv Res       Date:  2002-10       Impact factor: 3.402

2.  Shrinkage estimators for a composite measure of quality conceptualized as a formative construct.

Authors:  Michael Shwartz; Erol A Peköz; Cindy L Christiansen; James F Burgess; Dan Berlowitz
Journal:  Health Serv Res       Date:  2012-06-20       Impact factor: 3.402

3.  Loss Function Based Ranking in Two-Stage, Hierarchical Models.

Authors:  Rongheng Lin; Thomas A Louis; Susan M Paddock; Greg Ridgeway
Journal:  Bayesian Anal       Date:  2006-01-01       Impact factor: 3.728

4.  Composite Measures of Health Care Provider Performance: A Description of Approaches.

Authors:  Michael Shwartz; Joseph D Restuccia; Amy K Rosen
Journal:  Milbank Q       Date:  2015-12       Impact factor: 4.911

5.  Handling over-dispersion of performance indicators.

Authors:  D J Spiegelhalter
Journal:  Qual Saf Health Care       Date:  2005-10

6.  The CABG surgery volume-outcome relationship: temporal trends and selection effects in California, 1998-2004.

Authors:  James P Marcin; Zhongmin Li; Richard L Kravitz; Jian J Dai; David M Rocke; Patrick S Romano
Journal:  Health Serv Res       Date:  2008-02       Impact factor: 3.402

7.  Does hospital performance on process measures directly measure high quality care or is it a marker of unmeasured care?

Authors:  Rachel M Werner; Eric T Bradlow; David A Asch
Journal:  Health Serv Res       Date:  2007-12-20       Impact factor: 3.402

8.  Methods for Estimating and Interpreting Provider-Specific Standardized Mortality Ratios.

Authors:  Jiannong Liu; Thomas A Louis; Wei Pan; Jennie Z Ma; Allan J Collins
Journal:  Health Serv Outcomes Res Methodol       Date:  2003

9.  A method for estimating solid organ donor potential by organ procurement region.

Authors:  C L Christiansen; S L Gortmaker; J M Williams; C L Beasley; L E Brigham; C Capossela; M E Matthiesen; S Gunderson
Journal:  Am J Public Health       Date:  1998-11       Impact factor: 9.308

10.  Hospital variation in survival after pediatric in-hospital cardiac arrest.

Authors:  Natalie Jayaram; John A Spertus; Vinay Nadkarni; Robert A Berg; Fengming Tang; Tia Raymond; Anne-Marie Guerguerian; Paul S Chan
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2014-07
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