Impact of an Episode-Based Payment Initiative by Commercial Payers in Arkansas on Procedure Volume: an Observational Study

  • Julius L. ChenEmail author
  • Michael E. Chernew
  • A. Mark Fendrick
  • Joseph W. Thompson
  • Sherri Rose
Health Policy



Episode-based payment (EBP) is gaining traction among payers as an alternative to fee-for-service reimbursement. However, there is concern that EBP could influence the number of episodes.


To examine how procedure volume changed after the introduction of EBP in 2013 and 2014 under the Arkansas Health Care Payment Improvement Initiative.


Using 2011–2016 commercial claims data, we estimate a difference-in-differences model to assess the impact of EBP on the probability of a beneficiary having an episode for four procedures that were reimbursed under EBP in Arkansas: total joint replacement, cholecystectomy, colonoscopy, and tonsillectomy.


Commercially insured beneficiaries in Arkansas serve as our treatment group, while commercially insured beneficiaries in neighboring states serve as our comparison group.


Statewide implementation of EBP for various clinical conditions by two of Arkansas’ largest commercial insurers.

Main Measures

For a given procedure type, the primary outcomes are the annual rate of procedures (number of procedures per 1000 beneficiaries) and the probability of a beneficiary undergoing that procedure in a given quarter.

Key Results

The relationship between EBP and procedure volume varies across procedures. After EBP was implemented, the probability of undergoing colonoscopy increased by 17.2% (point estimate, 2.63; 95% CI, 1.18 to 4.08; p < 0.001; Arkansas pre-period mean, 15.29). The probability of undergoing total joint replacement increased by 9.9% (point estimate, 0.091; 95% CI, − 0.011 to 0.19; p = 0.08; Arkansas pre-period mean, 0.91), though this effect is not significant. There is no discernable impact on cholecystectomy or tonsillectomy volume.


We do not find clear evidence of deleterious volume expansion. However, because the impact of EBP on procedure volume may vary by procedure, payers planning to implement EBP models should be aware of this possibility.


reimbursement physician behavior health insurance health policy health economics 


Funding Information

Research reported in this study was financially supported by a grant from the Laura and John Arnold Foundation.

Compliance with Ethical Standards

Conflict of Interest

Dr. Chernew reports having equity in Archway Health, V-BID Health, Virta Health, and Paladin Healthcare Capital. He reports having consulted for the American Hospital Association, Anthem Health Insurance, Janssen Pharmaceuticals, Madalena Consulting, Merck & Company, Milliman, Navigant, Pfizer, PhRMA, Precision Health Economics, State of North Carolina, Takeda Pharmaceuticals, University of Michigan, White & Case, Amgen, J&J, Sanofi, University of Maine, McKinsey & Company, and John Freedman Healthcare. He has received research funding from the Laura and John Arnold Foundation, NIH/NIA, NBER/AHRQ, CMS via Abt Associates, MITRE/CMS, Altarum/RWJK, Peterson Center on Health Care, and The Commonwealth Fund. Dr. Fendrick reports having consulted for AbbVie, Amgen, Centivo, Community Oncology Association, Department of Defense, EmblemHealth, Exact Sciences, Freedman Health, Health at Scale Technologies, Health Management Associates, Lilly, MedZed, Penguin Pay, Risalto, Sempre Health, State of Minnesota, Wellth, and Zansors. He has received research funding from AHRQ, Boehringer-Ingelheim, Gary and Mary West Health Policy Center, Laura and John Arnold Foundation, National Pharmaceutical Council, PCORI, PhRMA, RWJ Foundation, and State of Michigan/CMS. All other authors report no relationships or potential conflicts of interest.

Supplementary material

11606_2019_5318_MOESM1_ESM.docx (2.8 mb)
ESM 1 (DOCX 2.81 MB).


  1. 1.
    Dummit LA, Kahvecioglu D, Marrufo G, et al. Association Between Hospital Participation in a Medicare Bundled Payment Initiative and Payments and Quality Outcomes for Lower Extremity Joint Replacement Episodes. JAMA. 2016;316(12):1267–1278.CrossRefGoogle Scholar
  2. 2.
    Navathe AS, Troxel AB, Liao JM, et al. Cost of Joint Replacement Using Bundled Payment Models. JAMA Intern Med. 2017;177(2):214–222.CrossRefGoogle Scholar
  3. 3.
    Joynt Maddox KE, Orav EJ, Zheng J, Epstein AM. Evaluation of Medicare’s Bundled Payments Initiative for Medical Conditions. N Engl J Med. 2018;379(3):260–269.CrossRefGoogle Scholar
  4. 4.
    Dummit LA, Marrufo G, Marshall J, et al; The Lewin Group. CMS Bundled Payments for Care Improvement Initiative Models 2-4: Year 3 Evaluation & Monitoring Annual Report. 2017. Available at: Accessed June 28, 2019.
  5. 5.
    Finkelstein A, Ji Y, Mahoney N, Skinner J. Mandatory Medicare Bundled Payment Program for Lower Extremity Joint Replacement and Discharge to Institutional Postacute Care: Interim Analysis of the First Year of a 5-Year Randomized Trial. JAMA. 2018;320(9):892–900.CrossRefGoogle Scholar
  6. 6.
    Barnett ML, Wilcock A, McWilliams JM, et al. Two-Year Evaluation of Mandatory Bundled Payments for Joint Replacement. N Engl J Med. 2019;380(3):252–262.CrossRefGoogle Scholar
  7. 7.
    Carroll C, Chernew ME, Fendrick AM, Thompson J, Rose S. Effects of Episode-Based Payment on Health Care Spending and Utilization: Evidence from Perinatal Care in Arkansas. J Health Econ. 2018;61(2018):47–62.Google Scholar
  8. 8.
    Fisher ES. Medicare’s Bundled Payment Program for Joint Replacement: Promise and Peril? JAMA. 2016;316(12):1262–1264.CrossRefGoogle Scholar
  9. 9.
    Weeks WB, Rauh SS, Wadsworth EB, Weinstein JN. The Unintended Consequences of Bundled Payments. Ann Intern Med. 2013;158(1):62–64.CrossRefGoogle Scholar
  10. 10.
    Cutler DM, Ghosh K. The Potential for Cost Savings through Bundled Episode Payments. N Engl J Med. 2012;366(12):1075–1077.CrossRefGoogle Scholar
  11. 11.
    Mechanic RE. Opportunities and Challenges for Episode-Based Payment. N Engl J Med. 2011;365(9):777–779.CrossRefGoogle Scholar
  12. 12.
    Ubel P. If We Cut Surgical Pay, Will Surgeons Cut Into More People? Forbes. 2017. Available at: Accessed 28 June 2019.
  13. 13.
    Baicker K, Chernew ME. Alternative Alternative Payment Models. JAMA Intern Med. 2017;177(2):222–223.CrossRefGoogle Scholar
  14. 14.
    Navathe AS, Liao JM, Dykstra SE, et al. Association of Hospital Participation in a Medicare Bundled Payment Program with Volume and Case Mix of Lower Extremity Joint Replacement Episodes. JAMA. 2018;320(9):901–910.CrossRefGoogle Scholar
  15. 15.
    Currently, the Arkansas EBP initiative features 20 clinical episodes, which have either been implemented, will be implemented, or are under development. Compared to the Medicare BPCI and BPCI Advanced models, the Arkansas model features a smaller number of episodes. However, the Arkansas initiative is novel in that it covers a broad scope of conditions and tests bundled payment for several conditions that are not included in the Medicare models. For example, the Arkansas model features various outpatient episodes, and it uniquely includes episodes for women’s health (e.g., perinatal care, hysterectomy), behavioral health (e.g., attention deficit hyperactivity disorder, oppositional defiant disorder), and children’s health (e.g., neonatal care, pediatric pneumonia). A list of episodes is provided on page 43 of the AHCPII statewide tracking report, which is available at: Accessed 28 June 2019.
  16. 16.
    The use of risk adjustment is common to all episode types, but the actual algorithm and which specific risk factors are included may vary slightly across payers and across episode types. In general, the risk adjustment algorithm considers diagnoses, comorbidities, procedures, and demographic characteristics drawn from a patient’s historical claims data.Google Scholar
  17. 17.
    To the extent that the analyzed episodes are sometimes performed on an emergent basis, it could dampen the impact of EBP on provider behavior. Nonetheless, we believe that emergent cases constitute a small minority of the procedures analyzed.Google Scholar
  18. 18.
    The perinatal and asthma episodes were also implemented by commercial payers and have adequate sample size. However, we chose not to study the perinatal episode because we do not expect to find a volume expansion effect, as providers cannot plausibly induce additional births. We chose not to study the asthma episode due to two reasons. First, the asthma episode is not procedure-based, and our focus is on how procedure volume responds to EBP. Second, identifying asthma episode triggers in the claims data requires accurate and detailed coding of diagnoses; however, diagnoses are not coded consistently in the MarketScan data.Google Scholar
  19. 19.
    Market Share and Enrollment of Largest Three Insurers - Large Group Market. Kaiser Family Foundation. Available at: Accessed June 28, 2019.
  20. 20.
    To construct our analytical dataset, we take repeated cross sections of continuously enrolled beneficiaries (one cross section for each year of 2011–2016). It is possible for a given beneficiary to appear in multiple cross sections over time, though this is not necessarily the case. Certain procedures that we analyze, like cholecystectomy and tonsillectomy, can only be performed on a patient once over time. Due to concern over serial correlation in the outcomes after a beneficiary undergoes these procedures, we drop that beneficiary from all cross sections following the date of the procedure.Google Scholar
  21. 21.
    We exclude the following plan types due to inadequate sample size: basic/major medical, comprehensive, exclusive provider organization, and point-of-service with capitation.Google Scholar
  22. 22.
    States that geographically border Arkansas are Missouri, Tennessee, Mississippi, Louisiana, Texas, and Oklahoma. The West South Central Census Division consists of Oklahoma, Texas, Arkansas, and Louisiana. The East South Central Census Division consists of Kentucky, Tennessee, Mississippi, and Alabama.Google Scholar
  23. 23.
    Our baseline control group differs slightly from that used in Carroll et al. (2018). We additionally include Missouri because it geographically borders Arkansas. We also include Texas. Carroll et al. include Kentucky and Oklahoma in their control group, whereas we exclude both states in our baseline specification. In a sensitivity analysis, we include Kentucky and Oklahoma in the control group, and we obtain similar results.Google Scholar
  24. 24.
    Westfall PH, Young SS. Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment. New York, NY: John Wiley & Sons; 1993.Google Scholar
  25. 25.
    Jones D, Molitor D, Reif J. What Do Workplace Wellness Programs Do? Evidence from the Illinois Workplace Wellness Study. National Bureau of Economic Research working paper 24229. Published January 2018. Revised June 2018. Available at: Accessed 28 June 2019.
  26. 26.
    We consider diagnostic and screening colonoscopies together. We include ages 40 to 49 in case EBP induces volume expansion among patients under age 50, which is the US Preventive Services Task Force’s recommended threshold for colorectal cancer screening.Google Scholar
  27. 27.
    Maratt JK, Saini SD. Colorectal Cancer Screening in the 21st Century: Where Do We Go From Here? Am J Manag Care. 2015;21(7):e447-e449.PubMedGoogle Scholar
  28. 28.
    To increase colonoscopy volume, physicians may be modifying their labor supply, readjusting effort, or changing the mix of services that they provide (e.g., displacing certain procedures with colonoscopies). While these behavioral responses are important to understand, studying them is beyond the scope of our work.Google Scholar
  29. 29.
    Arkansas Medicaid implemented EBP for total joint replacement in October 2012 and for cholecystectomy, colonoscopy, and tonsillectomy in July 2013.Google Scholar

Copyright information

© Society of General Internal Medicine 2019

Authors and Affiliations

  • Julius L. Chen
    • 1
    Email author
  • Michael E. Chernew
    • 2
  • A. Mark Fendrick
    • 3
  • Joseph W. Thompson
    • 4
  • Sherri Rose
    • 2
  1. 1.Columbia UniversityNew YorkUSA
  2. 2.Harvard Medical SchoolBostonUSA
  3. 3.University of MichiganAnn ArborUSA
  4. 4.Arkansas Center for Health ImprovementLittle RockUSA

Personalised recommendations