Health Care Management Science

, Volume 20, Issue 2, pp 221–231 | Cite as

Complementary effect of patient volume and quality of care on hospital cost efficiency

  • Jeong Hoon Choi
  • Imsu Park
  • Ilyoung Jung
  • Asoke Dey


This study explores the direct effect of an increase in patient volume in a hospital and the complementary effect of quality of care on the cost efficiency of U.S. hospitals in terms of patient volume. The simultaneous equation model with three-stage least squares is used to measure the direct effect of patient volume and the complementary effect of quality of care and volume. Cost efficiency is measured with a data envelopment analysis method. Patient volume has a U-shaped relationship with hospital cost efficiency and an inverted U-shaped relationship with quality of care. Quality of care functions as a moderator for the relationship between patient volume and efficiency. This paper addresses the economically important question of the relationship of volume with quality of care and hospital cost efficiency. The three-stage least square simultaneous equation model captures the simultaneous effects of patient volume on hospital quality of care and cost efficiency.


Complementary effect Cost efficiency Quality of care Simultaneous equation model 



We acknowledge and appreciate the constructive comments from editors and anonymous reviewers.


  1. 1.
    Luft HS, Hunt SS, Maerki SC (1987) The Volume-Outcome Relationship: Practice-Makes-Perfect or Selective-Referral Patters? Health Services Research 22(2):157–182Google Scholar
  2. 2.
    Theokary C, Ren J (2011) An empirical study of the relations between hospital volume, teaching status and service quality. Production and Operations Management 20(3):303–318CrossRefGoogle Scholar
  3. 3.
    Carr W, Feldstein P (1967) The relationship of cost to hospital size. Inq 4:45–65Google Scholar
  4. 4.
    Preyra C, Pink G (2006) Scale and scope efficiencies through hospital consolidations. Journal of Health Economics 25(6):1049–1068CrossRefGoogle Scholar
  5. 5.
    Porter M, Teisberg E (2004) redefining competition in health care. Harvard Business Review 82(6):65–76Google Scholar
  6. 6.
    Saxena SB, Sharma A, Wong A (2013) Succeeding in hospital & health systems M&A – Why so many deals have failed, and how to succeed in the future. Strategy&,
  7. 7.
    Kaplan R, Porter M (2011) How to solve the cost crisis in the health care. Harvard Bus Rev 89:47–64Google Scholar
  8. 8.
    Cylus J, Dickensheets B (2007) Hospital multifactor productivity: a presentation and analysis of two methodologies. Health Care Financ R 29(2):49–64Google Scholar
  9. 9.
    Harris J (1977) The internal organization of hospitals: some economic implications. Bell J of Econ 8:467–482CrossRefGoogle Scholar
  10. 10.
    Menon NM, Lee B, Eldenburg L (2000) Productivity of information systems in the healthcare industry. Information Systems Research 11(1):83–92CrossRefGoogle Scholar
  11. 11.
    Tucker A, Edmondson A (2003) Why hospitals don’t learn from failures: organizational and psychological dynamics that inhibit system change. California Management Review 45(2):55–72CrossRefGoogle Scholar
  12. 12.
    Chirikos T, Sear A (2000) Measuring hospital inefficiency: a comparison of two approaches. Health Ser Res 34:1389–1408Google Scholar
  13. 13.
    Goldstein S, Ward P, Keong Leong G, Butler T (2002) The effect of location, strategy, and operations technology on hospital performance. Journal of Operations Management 20:63–75CrossRefGoogle Scholar
  14. 14.
    Rosko M, Mutter R (2008) Stochastic frontier analysis of hospital inefficiency: a review of empirical issues and an assessment of robustness. Medical Care Research and Review 65:131–166CrossRefGoogle Scholar
  15. 15.
    Romano P, Mutter R (2004) The evolving science of quality measures for hospitals: implications for studies of competition and consolidation. Int J Health Care Finance & Econ 4:131–157CrossRefGoogle Scholar
  16. 16.
    Donabedian A (2003) Explorations in quality assessment and monitoring. The definition of quality and approaches to its assessment. Ann Arbor: Health Administration Press, Vol I, 13–15Google Scholar
  17. 17.
    Bernet P, Rosko M, Valdmanis V (2008) The relationship between hospital cost inefficiency and debt ratings. Journal of Health Care Finance 34(4):66–88Google Scholar
  18. 18.
    Rosko M (2001) cost efficiency of us hospitals: a stochastic frontier approach. Health Economics 10:539–551CrossRefGoogle Scholar
  19. 19.
    Taylor D, Whellan D, Sloan F (1999) Effects of admission to a teaching hospital on the cost and quality of care for medicare beneficiaries. The New England Journal of Medicine 340:293–302CrossRefGoogle Scholar
  20. 20.
    Chen S (2006) Productivity changes in Taiwanese hospitals and the national health insurance. Service Industries Journal 26(4):459–477CrossRefGoogle Scholar
  21. 21.
    Linna M, Hakkinen U (2006) reimbursing for the costs of teaching and research in finnish hospitals: a stochastic frontier analysis. Int J Health Care Finance & Econ 6(l):83–97CrossRefGoogle Scholar
  22. 22.
    Mitchell P, Shortell S (1997) Adverse outcomes and variations in organization of care delivery. Medical Care 35(11):19–32Google Scholar
  23. 23.
    Nayar P, Ozcan Y (2008) data envelopment analysis comparison of hospital efficiency and quality. Journal of Medical Systems 32:193–199CrossRefGoogle Scholar
  24. 24.
    Rosko M, Mutter R (2011) What have we learned from the application of stochastic frontier analysis to us hospitals? Medical Care Research and Review 68(1):75–100CrossRefGoogle Scholar
  25. 25.
    Hollingsworth B (2008) the measurement of efficiency and productivity of health care delivery. Health Economics 17(10):1107–1128CrossRefGoogle Scholar
  26. 26.
    Charnes A, Cooper W, Rhodes E (1978) Measuring the efficiency of decision making units. European Journal of Operational Research 2:429–444CrossRefGoogle Scholar
  27. 27.
    Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science 30(9):1078–1092. doi: 10.1287/mnsc.30.9.1078 CrossRefGoogle Scholar
  28. 28.
    O’Neill L, Rauner M, Heidenberger K, Kraus M (2008) a cross-national comparison and taxonomy of dea-based hospital efficiency studies. Socio-Economic Planning Sciences 42(3):158–189CrossRefGoogle Scholar
  29. 29.
    Banker R, Morey R (1986) use of categorical variables in data envelopment analysis. Management Science 32(12):1613–1627CrossRefGoogle Scholar
  30. 30.
    Hollingsworth B, Smith P (2003) Use of ratios in data envelopment analysis. Applied Economics Letters 10(11):733–735CrossRefGoogle Scholar
  31. 31.
    Korhonen P, Syrjanen M (2004) resource allocation based on efficiency analysis. Management Science 50(8):1134–1144CrossRefGoogle Scholar
  32. 32.
    Banker R, Conrad R, Strauss R (1986) A comparative application of data envelopment analysis and translog methods: an illustrative study of hospital production. Management Science 32(1):30–44CrossRefGoogle Scholar
  33. 33.
    Vitaliano D, Toren M (1996) Hospital cost and efficiency in a regime of stringent regulation. Eastern Econ J 22:161–173Google Scholar
  34. 34.
    Fichtenbaum R (1983) variations in hospital cost by types of ownership. Journal of Behavioral Economics 12(2):17–35CrossRefGoogle Scholar
  35. 35.
    Rosko M (2004) Performance of U.S. Teaching Hospitals: A Panel Analysis of Cost Inefficiency. Health Care Management Science 7(16):7–16CrossRefGoogle Scholar
  36. 36.
    Mutter RL, Rosko MD, Wong HS (2008) Measuring hospital inefficiency: The effects of controlling for quality and patient burden of illness. Health Services Research 43(6):1992–2013CrossRefGoogle Scholar
  37. 37.
    Bowerman B, O’Connell R, Murphree E (2014) Business statistics in practice, 7th edn. New York, NY, McGraw-Hill IrwinGoogle Scholar
  38. 38.
    Simmons JP, Nelson LD, Simonsohn U (2011) False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science 22(11):1359–1366CrossRefGoogle Scholar
  39. 39.
    Ray G, Xue L, Barney JB (2013) Impact of information technology capital on firm scope and performance: the role of asset characteristics. Academy of Management Journal 56(4):1125–1147CrossRefGoogle Scholar
  40. 40.
    Pisano G, Bohmer R, Edmondson A (2001) organizational differences in rates of learning: evidence from the adoption of minimally invasive cardiac surgery. Management Science 47(6):752–768CrossRefGoogle Scholar
  41. 41.
    Shortell S, O’Brien J, Carman J, Foster R, Hughes E, Boerstler H, O’Connor E (1995) Assessing the impact of continuous quality improvement/total quality management: concept versus implementation. Health Services Research 30(2):377–401Google Scholar
  42. 42.
    Becker E, Sloan F (1985) Hospital ownership and preference. Economic Inquiry 23:21–36CrossRefGoogle Scholar
  43. 43.
    Hansmann H (1998) Ownership of the Firm. J Law Econ Organ 4(2):267–304Google Scholar
  44. 44.
    Sloan F, Picone G, Taylor D, Chou S (2001) Hospital ownership and cost and quality of care: is there a dime's worth of difference? Journal of Health Economics 20(1):1–21CrossRefGoogle Scholar
  45. 45.
    Hansmann H (1996) The ownership of enterprise. Harvard University Press, Cambridge, MAGoogle Scholar
  46. 46.
    Burgess JF, Wilson PW (1996) hospital ownership and technical inefficiency. Management Science 42:110–123. doi: 10.1287/mnsc.42.1.110 CrossRefGoogle Scholar
  47. 47.
    Grosskopf S, Margaritis D, Valdmanis V (2004) competitive effects on teaching hospitals. European Journal of Operational Research 154(2):515–525CrossRefGoogle Scholar
  48. 48.
    Neely S, McInturff W (1998) What Americans say about the nation’s medical schools and teaching hospitals. Report on public opinion research. Part II, Association of American Medical Colleges, Washington, DCGoogle Scholar
  49. 49.
    Mesquita LF, Brush TH (2008) Untangling safeguard and production coordination effects in long-term buyer-supplier relationships. Academy of Management Journal 51:785–807Google Scholar
  50. 50.
    Hughes R, Hunt S, Luft H (1987) effects of surgeon volume and hospital volume on quality of care in hospitals. Medical Care 25(6):489–503CrossRefGoogle Scholar
  51. 51.
    Hewitt M, Petitti D (2001) Interpreting the volume-outcome relationship in the context of cancer care. National Academies Press (US), Washington DCGoogle Scholar
  52. 52.
    Ski CF, King-Shier KM, Thompson DR (2014) Gender, socioeconomic and ethnic/racial disparities in cardiovascular disease: a time for change. International Journal of Cardiology 170(3):255–257CrossRefGoogle Scholar
  53. 53.
    Bradley EH, Herrin J, Curry L, Cherlin EJ, Wang Y, Webster TR, Drye EE, Normand ST, Krumholz HM (2010) Variation in hospital mortality rates for patients with acute myocardial infarction. The American Journal of Cardiology 106(8):1108–1112CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Jeong Hoon Choi
    • 1
  • Imsu Park
    • 2
  • Ilyoung Jung
    • 3
  • Asoke Dey
    • 1
  1. 1.College of Business AdministrationThe University of AkronAkronUSA
  2. 2.School of ManagementState University of New York at BuffaloBuffaloUSA
  3. 3.Science and Technology Policy InstituteSejong CityRepublic of Korea

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