Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Association Between HEDIS Performance and Primary Care Physician Age, Group Affiliation, Training, and Participation in ACA Exchanges



There are a limited number of studies investigating the relationship between primary care physician (PCP) characteristics and the quality of care they deliver.


To examine the association between PCP performance and physician age, solo versus group affiliation, training, and participation in California’s Affordable Care Act (ACA) exchange.


Observational study of 2013-2014 data from Healthcare Effectiveness Data and Information Set (HEDIS) measures and select physician characteristics.


PCPs in California HMO and PPO practices (n = 5053) with part of their patient panel covered by a large commercial health insurance company.

Main Measures

Hemoglobin A1c testing; medical attention nephropathy; appropriate treatment hypertension (ACE/ARB); breast cancer screening; proportion days covered by statins; monitoring ACE/ARBs; monitoring diuretics. A composite performance measure also was constructed.

Key Results

For the average 35- versus 75-year-old PCP, regression-adjusted mean composite relative performance scores were at the 60th versus 47th percentile (89% vs. 86% composite absolute HEDIS scores; p < .001). For group versus solo PCPs, scores were at the 55th versus 50th percentiles (88% vs. 87% composite absolute HEDIS scores; p < .001). The effect of age on performance was greater for group versus solo PCPs. There was no association between scores and participation in ACA exchanges.


The associations between population-based care performance measures and PCP age, solo versus group affiliation, training, and participation in ACA exchanges, while statistically significant in some cases, were small. Understanding how to help older PCPs excel equally well in group practice compared with younger PCPs may be a fruitful avenue of future research.

This is a preview of subscription content, log in to check access.


  1. 1.

    Ketcham JD, Baker LC, MacIsaac D. Physician Practice Size And Variations In Treatments And Outcomes: Evidence From Medicare Patients With AMI. Health Aff (Millwood) 2007;26(1):195–205.

  2. 2.

    Casalino LP, Ramsay P, Baker LC, Pesko MF, Shortell SM. Medical Group Characteristics and the Cost and Quality of Care for Medicare Beneficiaries. Health Serv Res 2018;53(6):4970–96.

  3. 3.

    Tsugawa Y, Newhouse JP, Zaslavsky AM, Blumenthal DM, Jena AB. Physician age and outcomes in elderly patients in hospital in the US: observational study. BMJ. 2017 16;j1797.

  4. 4.

    Reid RO, Friedberg MW, Adams JL, McGlynn EA, Mehrotra A. Associations Between Physician Characteristics and Quality of Care. Arch Intern Med. [Internet]. 2010 13 [cited 2019 Jul 12];170(16). Available from: http://archinte.jamanetwork.com/article.aspx?doi=10.1001/archinternmed.2010.307

  5. 5.

    Caballero AE, Murray R, Delbanco SF. Are Limited Networks What We Hope And Think They Are? 2018 Feb 12 [cited 2019 May 1]. Available from: https://www.healthaffairs.org/do/10.1377/hblog20180208.408967/full/

  6. 6.

    Shackelton-Piccolo R, McKinlay JB, Marceau LD, Goroll AH, Link CL. Differences Between Internists and Family Practitioners in the Diagnosis and Management of the Same Patient With Coronary Heart Disease. Med Care Res Rev 2011;68(6):650–66.

  7. 7.

    Zoberi KA, Salas J, Morgan CN, Scherrer JF. Comparison of Family Medicine and General Internal Medicine on Diabetes Management. Mo Med 2017;114(3):187–94.

  8. 8.

    Higgins A, Zeddies T, Pearson SD. Measuring The Performance Of Individual Physicians By Collecting Data From Multiple Health Plans: The Results Of A Two-State Test. Health Aff (Millwood) 2011;30(4):673–81.

  9. 9.

    California Healthcare Performance Information System (CHPI): Methods for Rating Physicians and Practice Sites – Cycle 2 Prepared by: California Healthcare Performance Information System; 2016 Nov.

  10. 10.

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers; 1988.

  11. 11.

    Sedgwick P. Randomised controlled trials: understanding effect sizes. BMJ. 2015;350(mar27 2):h1690–h1690.

  12. 12.

    Shwartz M, Restuccia JD, Rosen AK. Composite Measures of Health Care Provider Performance: A Description of Approaches: Composite Measures of Health Care Provider Performance. Milbank Q 2015;93(4):788–825.

  13. 13.

    Choudhry NK, Fletcher RH, Soumerai SB. Systematic Review: The Relationship between Clinical Experience and Quality of Health Care. Ann Intern Med 2005;142(4):260–73.

  14. 14.

    Gray B, Vandergrift J, Landon B, Reschovsky J, Lipner R. Associations Between American Board of Internal Medicine Maintenance of Certification Status and Performance on a Set of Healthcare Effectiveness Data and Information Set (HEDIS) Process Measures. Ann Intern Med 2018;169(2):97.

  15. 15.

    McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, et al. The Quality of Health Care Delivered to Adults in the United States. N Engl J Med 2003;348(26):2635–45.

  16. 16.

    Levine DM, Linder JA, Landon BE. The Quality of Outpatient Care Delivered to Adults in the United States, 2002 to 2013. JAMA Intern Med 2016;176(12):1778.

  17. 17.

    Yegian J, Yanagihara D. Value Based Pay for Performance in California [Internet]. Integrated Healthcare Association; 2013 [cited 2019 May 16]. Available from: https://www.iha.org/sites/default/files/resources/issue-brief-value-based-p4p-2013.pdf

  18. 18.

    Gaines R. California Maps: How Many Primary Care and Specialist Physicians Are in Your County? [Internet]. 2017 [cited 2019 May 16]. Available from: https://www.chcf.org/publication/california-maps-primary-care-specialist-physicians-county/

  19. 19.

    Knighton AJ, Stephenson B, Savitz LA. Measuring the Effect of Social Determinants on Patient Outcomes: A Systematic Literature Review. J Health Care Poor Underserved 2018;29(1):81–106.

Download references


The authors would like to thank the California Healthcare Performance Information System for assembling one of the only multi-payer systems in California to provide validated information on provider quality performance ratings.

Author information

Correspondence to Jill R. Glassman PhD, MSW.

Ethics declarations

Conflict of Interest

The authors declare that they do not have a conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material


(DOCX 20 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Glassman, J.R., Hopkins, D.S.P., Bundorf, M.K. et al. Association Between HEDIS Performance and Primary Care Physician Age, Group Affiliation, Training, and Participation in ACA Exchanges. J GEN INTERN MED (2020). https://doi.org/10.1007/s11606-020-05642-3

Download citation


  • primary care
  • health care quality
  • HEDIS performance measures
  • physician age
  • physician characteristics