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Aligning incentives in health care: a multiscale decision theory approach

  • Original Article
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EURO Journal on Decision Processes

Abstract

Financial incentives offered by insurers to health care providers have been identified as a key mechanism to lower costs while improving quality of care. How to effectively design incentive programs that can align the varying objectives of health care stakeholders, as well as predict program performance and stakeholders’ decision response is an unresolved research challenge. The objective of this paper was to establish the foundation for a novel approach based on multiscale decision theory (MSDT) that can effectively model and efficiently analyze such incentive programs, and the complex health care system in general. The MSDT model captures the interdependencies of stakeholders, their decision processes, uncertainties, and how incentives impact decisions and outcomes at the payer, hospital, physician and patient level. We illustrate the modeling approach by applying it to a specific incentive program, the Medicare Shared Savings Program (MSSP) for Accountable Care Organizations (ACOs), which was introduced by the Centers for Medicare and Medicaid Services (CMS) in the United States in 2012. We focus our analysis on computed tomography (CT) use by physicians, and CT scanner investment decisions by hospitals. We determine the conditions under which the incentive program leads to the desired outcomes of cost reduction and quality of care improvements. The results have policy and managerial implications for CMS, ACOs and their members, specifically hospitals and physicians.

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References

  • Bach PB (2010) A map to bad policy—hospital efficiency measures in the Dartmouth Atlas. N Engl J Med 362(7):569–574

    Article  Google Scholar 

  • Birch S, Gafni A (1992) Cost effectiveness/utility analyses: do current decision rules lead us to where we want to be? J Health Econ 11(3):279–296

    Article  Google Scholar 

  • Boadway R, Marchand M, Sato M (2004) An optimal contract approach to hospital financing. J Health Econ 23(1):85–110

    Article  Google Scholar 

  • Brenner DJ, Hall EJ (2007) Computed tomography—an increasing source of radiation exposure. N Engl J Med 357(22):2277–2284

    Article  Google Scholar 

  • Centers for Medicare and Medicaid Services (2011a) 2012 ACO narrative quality measures specifications manual. http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/Downloads/ACO_QualityMeasures.pdf. Accessed 2 Sep 2015

  • Centers for Medicare and Medicaid Services (2011b) Medicare program; Medicare Shared Savings Program: Accountable Care Organizations. Final rule. Federal Regist 76(212):67802–67990

    Google Scholar 

  • Centers for Medicare and Medicaid Services (2014a) NHE Summary including share of GDP, CY1960-2013. http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/NHEGDP13.zip.  Cms.gov. Accessed 2 Sep 2015

  • Centers for Medicare and Medicaid Services (2014b) Fact sheets: Medicare ACOs continue to succeed in improving care, lowering cost growth. http://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2014-Fact-sheets-items/2014-11-10.html. Cms.gov. Accessed 2 Sep 2015

  • Centers for Medicare and Medicaid Services (2014c) Fast facts—all Medicare Shared Savings Program and Medicare Pioneer ACOs. http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/Downloads/PioneersMSSPCombinedFastFacts.pdf. Cms.gov. Accessed 2 Sep 2015

  • Cipriano LE, Levesque BG, Zaric GS, Loftus EV, Sandborn WJ (2012) Cost-effectiveness of imaging strategies to reduce radiation-induced cancer risk in Crohn’s disease. Inflamm Bowel Dis 18(7):1240–1248

    Article  Google Scholar 

  • de Brantes F (2013) The incentive cure: the real relief for health care. Health Care Incentives Improvement Institute, Newtown

    Google Scholar 

  • DeCamp M, Sugarman J, Berkowitz S (2014) Shared savings in accountable care organizations: how to determine fair distributions. J Am Med Assoc 311(10):1011–1012

    Article  Google Scholar 

  • Dolgov D, Durfee E (2004) Graphical models in local, asymmetric multi-agent Markov decision processes. Paper presented at the Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems-volume 2

  • Dunnick NR, Applegate KE, Arenson RL (2005) The inappropriate use of imaging studies: a report of the 2004 Intersociety Conference. J Am Coll Radiol 2(5):401–406

    Article  Google Scholar 

  • Duszak R, Allen B, Hughes DR, Husain N, Barr RM, Silva E, Donovan WD (2012) Emergency department CT of the abdomen and pelvis: preferential utilization in higher complexity patient encounters. J Am Coll Radiol 9(6):409–413

    Article  Google Scholar 

  • Farrell D, Jensen E, Kocher B, Lovegrove N, Melhem F, Mendonca L, Parish B (2008) Accounting for the cost of US health care: a new look at why Americans spend more. http://www.mckinsey.com/insights/health_systems_and_services/accounting_for_the_cost_of_us_health_care. McKinsey & Company, Special Sector Office. Accessed 2 Sep 2015

  • Filar J, Vrieze K (1997) Competitive Markov decision processes. Springer, New York

    Google Scholar 

  • Fisher ES, Shortell SM (2010) Accountable care organizations. JAMA J Am Med Assoc 304(15):1715–1716

    Article  Google Scholar 

  • Fisher ES, Staiger DO, Bynum JPW, Gottlieb DJ (2007) Creating accountable care organizations: the extended hospital medical staff. Health Aff 26(1):w44–w57

    Article  Google Scholar 

  • Focke A, Stummer C (2003) Strategic technology planning in hospital management. OR Spectrum 25(2):161–182

    Article  Google Scholar 

  • Fuloria PC, Zenios SA (2001) Outcomes-adjusted reimbursement in a health-care delivery system. Manage Sci 47(6):735–751

    Article  Google Scholar 

  • Greaney TL (2011) Accountable care organizations—the fork in the road. N Engl J Med 364:e1

  • Greenberg D, Peterburg Y, Vekstein D, Pliskin JS (2005) Decisions to adopt new technologies at the hospital level: insights from Israeli medical centers. Int J Technol Assess Health Care 21(02):219–227

    Google Scholar 

  • Henry A, Wernz C (2015) A multiscale decision theory analysis for revenue sharing in three-stage supply chains. Ann Oper Res 226(1):277–300

    Article  Google Scholar 

  • Holmstrom B, Milgrom P (1991) Multitask principal-agent analyses: incentive contracts, asset ownership, and job design. J Law Econ Organ 7:24–52

    Article  Google Scholar 

  • Institute of Medicine (1985) Assessing medical technologies. National Academy of Science Press, Washington, DC

    Google Scholar 

  • Itoh H (1992) Cooperation in hierarchical organizations: an incentive perspective. J Law Econ Organ 8(2):321–345

    Google Scholar 

  • Kaiser Family Foundation (2007) How changes in medical technology affect health care costs. Menlo Park, CA. http://www.kff.org/insurance/snapshot/chcm030807oth.cfm. Accessed 2 Sep 2015

  • Keown AJ, Martin JD (1976) An integer goal programming model for capital budgeting in hospitals. Financ Manage 5(3):28

    Article  Google Scholar 

  • Kleinmuntz DN (2007) Resource allocation decisions. In: Edwards W, Miles RJ, von Winterfeldt D (eds) Advances in decision analysis: from foundations to applications. Cambridge University Press, New York, pp 400–418

    Chapter  Google Scholar 

  • Laupacis A, Feeny D, Detsky AS, Tugwell PX (1992) How attractive does a new technology have to be to warrant adoption and utilization? Tentative guidelines for using clinical and economic evaluations. Can Med Assoc J 146(4):473–481

    Google Scholar 

  • Lee SL, Walsh AJ, Ho HS (2001) Computed tomography and ultrasonography do not improve and may delay the diagnosis and treatment of acute appendicitis. Arch Surg 136(5):556

    Article  Google Scholar 

  • Levaggi R, Moretto M, Rebba V (2009) Investment decisions in hospital technology when physicians are devoted workers. Econ Innov New Technol 18(5):487–512

    Article  Google Scholar 

  • Li LX, Collier DA (2000) The role of technology and quality on hospital financial performance. Int J Serv Ind Manag 11(3):202–224

    Article  Google Scholar 

  • Lowell KH, Bertko J (2010) The Accountable Care Organization (ACO) model: building blocks for success. J Ambul Manag 33(1):81

    Google Scholar 

  • Ma CA (1994) Health care payment systems: cost and quality incentives. J Econ Manag Strategy 3(1):93–112

    Article  Google Scholar 

  • Mesarović MD, Macko D, Takahara Y (1970) Theory of hierarchical, multilevel systems. Elsevier Science, Amsterdam

    Google Scholar 

  • Myerson RB (1997) Game theory: analysis of conflict. Harvard University Press, Cambridge

    Google Scholar 

  • Newhouse JP (1992) Medical-care costs—how much welfare loss. J Econ Perspect 6(3):3–21

    Article  Google Scholar 

  • Partrick DA, Janik JE, Janik JS, Bensard DD, Karrer FM (2003) Increased CT scan utilization does not improve the diagnostic accuracy of appendicitis in children. J Pediatr Surg 38(5):659–662

    Article  Google Scholar 

  • Pauker SG, Kassirer JP (1975) Therapeutic decision making: a cost-benefit analysis. N Engl J Med 293(5):229–234

    Article  Google Scholar 

  • Pauker SG, Kassirer JP (1980) The threshold approach to clinical decision making. N Engl J Med 302(20):1109–1117

    Article  Google Scholar 

  • Pertile P (2009) An extension of the real option approach to the evaluation of healthcare technologies: the case of positron emission tomography. Int J Healthcare Finance Econ 9(3):317–332

    Article  Google Scholar 

  • Phelps CE, Mushlin AI (1991) On the (near) equivalence of cost-effectiveness and cost-benefit analyses. Int J Technol Assess Health Care 7(01):12–21

    Article  Google Scholar 

  • Pope GC, Kautter J (2012) Minimum savings requirements in Shared Savings provider payment. Health Econ 21(11):1336–1347

    Article  Google Scholar 

  • Pope B, Deshmukh A, Johnson A, Rohack J (2014) Multilateral contracting and prevention. Health Econ 23(4):397–409

    Article  Google Scholar 

  • Puterman ML (2009) Markov decision processes: discrete stochastic dynamic programming, vol 414. Wiley, USA

    Google Scholar 

  • Rauner MS, Heidenberger K, Hermescec D, Mokic A (2011) Scope and role of strategic technology management in Austrian hospitals: a decade later. Int J Healthcare Technol Manag 12(3):250–279

    Article  Google Scholar 

  • Schneeweiß C (2003) Distributed decision making, 2nd edn. Springer, Heidelberg

    Book  Google Scholar 

  • Shields MC, Patel PH, Manning M, Sacks L (2011) A model for integrating independent physicians into accountable care organizations. Health Aff 30(1):161–172

    Article  Google Scholar 

  • Shortell SM, Casalino LP, Fisher ES (2010) How the Center for Medicare and Medicaid Innovation should test accountable care organizations. Health Aff 29(7):1293–1298

    Article  Google Scholar 

  • Smith-Bindman R (2010) Is computed tomography safe. N Engl J Med 363(1):1–4

    Article  Google Scholar 

  • Sox HC (1986) Probability theory in the use of diagnostic tests: an introduction to critical study of the literature. Ann Intern Med 104(1):60–66

    Article  Google Scholar 

  • Swets JA, Pickett RM, Whitehead SF, Getty DJ, Schnur JA, Swets JB, Freeman BA (1979) Assessment of diagnostic technologies. Science 205(4408):753–759

    Article  Google Scholar 

  • Teplensky JD, Pauly MV, Kimberly JR, Hillman AL, Schwartz JS (1995) Hospital adoption of medical technology: an empirical test of alternative models. Health Serv Res 30(3):437

    Google Scholar 

  • Turchetti G, Palla I, Pierotti F, Cuschieri A (2012) Economic evaluation of da Vinci-assisted robotic surgery: a systematic review. Surg Endosc 26(3):598–606

    Article  Google Scholar 

  • Wacht RF, Whitford DT (1976) A goal programming model for capital investment analysis in nonprofit hospitals. Financ Manage 5(2):37–47

    Article  Google Scholar 

  • Wernz C (2008) Multiscale decision-making: Bridging temporal and organizational scales in hierarchical systems. Dissertation, University of Massachusetts Amherst

  • Wernz C (2013) Multi-time-scale markov decision processes for organizational decision-making. EURO J Decis Processes 1(3):299–324

    Article  Google Scholar 

  • Wernz C, Deshmukh A (2007a) Decision strategies and design of agent interactions in hierarchical manufacturing systems. J Manuf Syst 26(2):135–143

    Article  Google Scholar 

  • Wernz C, Deshmukh A (2007b) Managing hierarchies in a flat world. Proceedings of the Industrial Engineering Research Conference, Nashville, TN

  • Wernz C, Deshmukh A (2009) An incentive-based, multi-period decision model for hierarchical systems. In: 3rd International Conference on Global Interdependence and Decision Sciences (ICGIDS), Hyderabad, India, pp 84-88

  • Wernz C, Deshmukh A (2010) Multiscale decision-making: bridging organizational scales in systems with distributed decision-makers. Eur J Oper Res 202(3):828–840

    Article  Google Scholar 

  • Wernz C, Deshmukh A (2012) Unifying temporal and organizational scales in multiscale decision-making. Eur J Oper Res 223(3):739–751

    Article  Google Scholar 

  • Wernz C, Henry A (2009) Multi-Level coordination and decision-making in service operations. Ser Sci 1(4):270–283

    Article  Google Scholar 

  • Wernz C, Gehrke I, Ball DR (2013) Managerial decision-making in hospitals with real options analysis. Inf Syst e-bus Manag 1–19

  • Wernz C, Zhang H, Phusavat K (2014) International study of technology investment decisions at hospitals. Ind Manag Data Syst 114(4):568–582

    Article  Google Scholar 

  • Yaesoubi R (2010) On the implementation of medical programs in health care systems: game-theoretic frameworks. Dissertation, North Carolina State University

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Acknowledgments

The authors thank the guest editors and referees for handling this paper and for providing constructive comments and improvement suggestions. This research was funded by the National Science Foundation under award number CMMI-1335407.

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Authors and Affiliations

  1. Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

    Hui Zhang & Christian Wernz

  2. Renown Health, Reno, NV, USA

    Anthony D. Slonim

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  1. Hui Zhang
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Correspondence to Hui Zhang.

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Zhang, H., Wernz, C. & Slonim, A.D. Aligning incentives in health care: a multiscale decision theory approach. EURO J Decis Process 4, 219–244 (2016). https://doi.org/10.1007/s40070-015-0051-3

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