Literature DB >> 15230938

Economic profiling of primary care physicians: consistency among risk-adjusted measures.

J William Thomas1, Kyle L Grazier, Kathleen Ward.   

Abstract

OBJECTIVE: To investigate whether different risk-adjustment methodologies and economic profiling or "practice efficiency" metrics produce differences in practice efficiency rankings for a set of primary care physicians (PCPs). DATA SOURCE: Twelve months of claims records (inpatient, outpatient, professional, and pharmacy) for an independent practice association HMO. STUDY
DESIGN: Patient risk scores obtained with six profiling risk-adjustment methodologies were used in conjunction with claims cost tabulations to measure practice efficiency of all primary care physicians who managed 25 or more members of an HMO. DATA COLLECTION: For each of the risk-adjustment methodologies, two measures of "efficiency" were constructed: the standardized cost difference between total observed (standardized actual) and total expected costs for patients managed by each PCP, and the ratio of the PCP's total observed to total expected costs (O/E ratio). Primary care physicians were ranked from most to least efficient according to each risk-adjusted measure, and level of agreement among measures was tested using weighted kappa. Separate rankings were constructed for pediatricians and for other primary care physicians.
FINDINGS: Moderate to high levels of agreement were observed among the six risk-adjusted measures of practice efficiency. Agreement was greater among pediatrician rankings than among adult primary care physician rankings, and, with the standardized difference measure, greater for identifying the least efficient than the most efficient physicians. The O/E ratio was shown to be a biased measure of physician practice efficiency, disproportionately targeting smaller sized panels as outliers.
CONCLUSIONS: Although we observed moderate consistency among different risk-adjusted PCP rankings, consistency of measures does not prove that practice efficiency rankings are valid, and health plans should be careful in how they use practice efficiency information. Indicators of practice efficiency should be based on the standardized cost difference, which controls for number of patients in a panel, instead of O/E ratio, which does not.

Entities:  

Mesh:

Year:  2004        PMID: 15230938      PMCID: PMC1361048          DOI: 10.1111/j.1475-6773.2004.00268.x

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


  9 in total

1.  A methodology for choosing a physician profiling system: the case of First Option Health Plan.

Authors:  C Nickerson; R W Rutledge
Journal:  J Health Care Finance       Date:  1999

2.  The future of physician profiling.

Authors:  L G Sandy
Journal:  J Ambul Care Manage       Date:  1999-07

3.  Economic notes: definitions of efficiency.

Authors:  S Palmer; D J Torgerson
Journal:  BMJ       Date:  1999-04-24

4.  Managing drug costs: the perception of managed care pharmacy directors.

Authors:  L M Litton; F A Sisk; M E Akins
Journal:  Am J Manag Care       Date:  2000-07       Impact factor: 2.229

5.  Longitudinal profiles of health care providers.

Authors:  Susan E Bronskill; Sharon-Lise T Normand; Mary Beth Landrum; Robert A Rosenheck
Journal:  Stat Med       Date:  2002-04-30       Impact factor: 2.373

6.  Comparing accuracy of risk-adjustment methodologies used in economic profiling of physicians.

Authors:  J William Thomas; Kyle L Grazier; Kathleen Ward
Journal:  Inquiry       Date:  2004       Impact factor: 1.730

7.  Casemix adjustment of managed care claims data using the clinical classification for health policy research method.

Authors:  M E Cowen; D J Dusseau; B G Toth; C Guisinger; M W Zodet; Y Shyr
Journal:  Med Care       Date:  1998-07       Impact factor: 2.983

8.  A comparison of a Bayesian vs. a frequentist method for profiling hospital performance.

Authors:  P C Austin; C D Naylor; J V Tu
Journal:  J Eval Clin Pract       Date:  2001-02       Impact factor: 2.431

9.  The measurement of observer agreement for categorical data.

Authors:  J R Landis; G G Koch
Journal:  Biometrics       Date:  1977-03       Impact factor: 2.571

  9 in total
  14 in total

1.  Who values information from a health plan Internet-based decision tool and why: a demographic and utilization analysis.

Authors:  Song Chen; Pinar Karaca-Mandic; Regina Levin
Journal:  Health Serv Res       Date:  2011-08-22       Impact factor: 3.402

2.  A nonparametric statistical method that improves physician cost of care analysis.

Authors:  Brent A Metfessel; Robert A Greene
Journal:  Health Serv Res       Date:  2012-04-23       Impact factor: 3.402

3.  The effect of complementary and alternative medicine claims on risk adjustment.

Authors:  Bonnie K Lind; Chad Abrams; William E Lafferty; Paula K Diehr; David E Grembowski
Journal:  Med Care       Date:  2006-12       Impact factor: 2.983

Review 4.  A systematic review of health care efficiency measures.

Authors:  Peter S Hussey; Han de Vries; John Romley; Margaret C Wang; Susan S Chen; Paul G Shekelle; Elizabeth A McGlynn
Journal:  Health Serv Res       Date:  2009-01-28       Impact factor: 3.402

5.  Who funds their health savings account and why?

Authors:  Song Chen; Anthony T Lo Sasso; Aneesh Nandam
Journal:  Int J Health Care Finance Econ       Date:  2013-09-22

6.  Regression tree boosting to adjust health care cost predictions for diagnostic mix.

Authors:  John W Robinson
Journal:  Health Serv Res       Date:  2008-04       Impact factor: 3.402

7.  Assigning ambulatory patients and their physicians to hospitals: a method for obtaining population-based provider performance measurements.

Authors:  Julie P W Bynum; Enrique Bernal-Delgado; Daniel Gottlieb; Elliott Fisher
Journal:  Health Serv Res       Date:  2007-02       Impact factor: 3.402

8.  Risk-adjusted payment and performance assessment for primary care.

Authors:  Arlene S Ash; Randall P Ellis
Journal:  Med Care       Date:  2012-08       Impact factor: 2.983

9.  Should episode-based economic profiles be risk adjusted to account for differences in patients' health risks?

Authors:  J William Thomas
Journal:  Health Serv Res       Date:  2006-04       Impact factor: 3.402

10.  Incorporating statistical uncertainty in the use of physician cost profiles.

Authors:  John L Adams; Elizabeth A McGlynn; J William Thomas; Ateev Mehrotra
Journal:  BMC Health Serv Res       Date:  2010-03-05       Impact factor: 2.655

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.