Abstract
The case mix planning problem deals with choosing the ideal composition and volume of patients in a hospital. With many countries having recently changed to systems where hospitals are reimbursed for patients according to their diagnosis, case mix planning has become an important tool in strategic and tactical hospital planning. Selecting patients in such a payment system can have a significant impact on a hospital’s revenue. The contribution of this article is to provide the first literature review focusing on the case mix planning problem. We describe the problem, distinguish it from similar planning problems, and evaluate the existing literature with regard to problem structure and managerial impact. Further, we identify gaps in the literature. We hope to foster research in the field of case mix planning, which only lately has received growing attention despite its fundamental economic impact on hospitals.
Similar content being viewed by others
References
Abdelrasol ZY, Harraz N, Eltawil A (2013) A proposed solution framework for the operating room scheduling problems. In: Proceedings of the world congress on engineering and computer science, vol 2, pp 1149–1157
Adan I, Vissers J (2002) Patient mix optimisation in hospital admission planning: a case study. Int J Oper Prod Manag 22(4):445–461
Adan I, Bekkers J, Dellaert N, Vissers J, Yu X (2009) Patient mix optimisation and stochastic resource requirements: a case study in cardiothoracic surgery planning. Health Care Manag Sci 12(2):129–141
Baligh HH, Laughhunn DJ (1969) An economic and linear model of the hospital. Health Serv Res 4 (4):293–303
Beech R, Brough RL, Fitzsimons BA (1990) The development of a decision-support system for planning services within hospitals. J Oper Res Soc 41(11):995– 1006
Blake JT, Carter MW (2002) A goal programming approach to strategic resource allocation in acute care hospitals. Eur J Oper Res 140(3):541–561
Blake JT, Carter MW (2003) Physician and hospital funding options in a public system with decreasing resources. Socio Econ Plan Sci 37(1):45–68
Brailsford SC, Lattimer V, Tarnaras P, Turnbull J (2004) Emergency and on-demand health care: modelling a large complex system. J Oper Res Soc 55(1):34–42
Brandeau ML, Hopkins DSP (1984) A patient mix model for hospital financial planning. Inquiry 21(1):32–44
Broyles RW, Rosko MD (1986) Full cost determination: an application of pricing and patient mix policies under drgs. Health Care Manag Rev 11(3):57–68
Busse R, Schreyögg J, Smith PC (2006) Editorial: Hospital case payment systems in europe. Health Care Manag Sci 9(3):211– 213
Butler TW, Karwan KR, Sweigart JR (1992) Multi-level strategic evaluation of hospital plans and decisions. J Oper Res Soc 43(7):665–675
Butler TW, Leong GK, Everett LN (1996) The operations management role in hospital strategic planning. J Oper Manag 14(2):137–156
Calichman MV (2005) Creating an optimal operating room schedule. AORN J 81(3):580–588
Canning B, Loeb JI (1988) Case mix management. J Manag Med 3(4):372–385
Cardoen B, Demeulemeester E, Beliën J (2010) Operating room planning and scheduling: a literature review. Eur J Oper Res 201(3):921–932
Choi S, Wilhelm WE (2014) On capacity allocation for operating rooms. Comput Oper Res 44:174–184
Conrad RF, Strauss RP (1983) A multiple-output multiple-input model of the hospital industry in north carolina. Appl Econ 15(3):341–352
Dexter F, Blake JT, Penning DH, Lubarsky DA (2002a) Calculating a potential increase in hospital margin for elective surgery by changing operating room time allocations or increasing nursing staffing to permit completion of more cases: a case study. Anesth Analg 94(1):138–142
Dexter F, Blake JT, Penning DH, Sloan B, Chung P, Lubarsky DA (2002b) Use of linear programming to estimate impact of changes in a hospital’s operating room time allocation on perioperative variable costs. Anesthesiology 96(3):718– 724
Dexter F, Ledolter J, Wachtel RE (2005) Tactical decision making for selective expansion of operating room resources incorporating financial criteria and uncertainty in subspecialties’ future workloads. Anesth Analg 100(5):1425–1432
Dowling WL (1976) Hospital production: a linear programming model. Lexington Books, Lexington
Feldstein M (1967) Economic analysis for health service efficiency: econometric studies of the British National Health Service. North-Holland Publishing Company, Amsterdam
Fetter RB, Shin Y, Freeman JL, Averill RF, Thompson JD (1980) Case mix definition by diagnosis-related groups. Med Care 18(2):Supplement, 1–53
Fügener A (2015) An integrated strategic and tactical master surgery scheduling approach with stochastic resource demand. J Bus Logist (forthcoming)
Goldfarb M, Hornbrook M, Rafferty J (1980) Behavior of the multiproduct firm: A model of the nonprofit hospital system. Med Care 18(2):185–201
Guerriero F, Guido R (2011) Operational research in the management of the operating theatre: a survey. Health Care Manag Sci 14(1):89–114
Gupta D (2007) Surgical suites’ operations management. Prod Oper Manag 16(6):689–700
Hans EW, Nieberg T (2007) Operating room manager game. INFORMS Trans Educ 8(1):25–36
Hans EW, van Houdenhoven M, Hulshof PJH (2012) A framework for healthcare planning and control. In: Handbook of healthcare system scheduling, international series in operations research & management science, vol 168. Springer, US, pp 303– 320
Harper PR (2002) A framework for operational modelling of hospital resources. Health Care Manag Sci 5(3):165– 173
Hartman M, Martin AB, Benson J, Catlin A et al (2013) National health spending in 2011: overall growth remains low, but some payers and services show signs of acceleration. Health Aff 32(1):87–99
Hobbs T (1963) Linear programming as applied to the admissions of elective surgery patients at presbyterian-university hospital. Department of Industrial Engineering, University of Pittsburgh (mimeographed)
Hughes WL, Soliman SY (1985) Short-term case mix management with linear programming. Hosp Health Serv Adm 30(1):52–60
Hulshof PJ, Kortbeek N, Boucherie RJ, Hans EW, Bakker PJ (2012) Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS. Health Syst 1(2):129–175
Joustra PE, de Wit J, Van Dijk NM, Bakker PJ (2011) How to juggle priorities? An interactive tool to provide quantitative support for strategic patient-mix decisions: an ophthalmology case. Health Care Manag Sci 14(4):348– 360
Kraus M, Rauner M, Schwarz S (2010) Hospital management games: a taxonomy and extensive review. CEJOR 18(4):567– 591
Kuo PC, Schroeder RA, Mahaffey S, Bollinger RR (2003) Optimization of operating room allocation using linear programming techniques. J Am Coll Surg 197(6):889–895
Li LX, Benton W, Leong G (2002) The impact of strategic operations management decisions on community hospital performance. Journal of Operations Management 20(4):389–408
Ma G, Demeulemeester E (2013) A multilevel integrative approach to hospital case mix and capacity planning. Comput Oper Res 40(9):2198–2207
Ma G, Belien J, Demeulemeester E, Wang L (2011) Solving the case mix problem optimally by using branch-and-price algorithms. FBE Research Report KBI_1107, pp 1–33
May JH, Spangler WE, Strum DP, Vargas LG (2011) The surgical scheduling problem: Current research and future opportunities. Prod Oper Manag 20(3):392–405
Meyer GC, Taylor JW, Damewood EZ (1992) Using the operations management modeling technique of linear programming to determine optimal case mix of three cardiac services. J Cardiopulm Rehabil Prev 12(6):407–412
Milsum JH, Turban E, Vertinsky I (1973) Hospital admission systems: their evaluation and management. Manag Sci 19(6):646–666
Mulholland MW, Abrahamse P, Bahl V (2005) Linear programming to optimize performance in a department of surgery. J Am Coll Surg 200(6):861–868
Nackel J, Powell P, Goran M (1984) A practical perspective - case mix management: issues and strategies. Hosp Health Serv Adm 29(1):7–14
Nunes LGN, de Carvalho SV, Rodrigues RdCM (2009) Markov decision process applied to the control of hospital elective admissions. Artif Intell Med 47(2):159– 171
OECD (2013) Health at a Glance 2013: OECD Indicators. OECD Publishing, Paris
O’Neill L, Dexter F (2007) Tactical increases in operating room block time based on financial data and market growth estimates from data envelopment analysis. Anesth Analg 104(2):355– 368
Paat-Ahi G, Aaviksoo A, Świderek M (2014) Cholecystectomy and diagnosis-related groups (drgs): patient classification and hospital reimbursement in 11 european countries. Int J Health Policy Manag 3(7):383– 391
Pettengill J, Vertrees J (1982) Reliability and validity in hospital case-mix measurement. Health Care Financ Rev 4(2):101–128
Quentin W, Scheller-Kreinsen D, Blümel M, Geissler A, Busse R (2013) Hospital payment based on diagnosis-related groups differs in europe and holds lessons for the united states. Health Aff 32(4):713–723
Rauner MS, Schneider G, Heidenberger K (2005) Reimbursement systems and regional inpatient allocation: a non-linear optimisation model. IMA J Manag Math 16(3):217–237
Rauner MS, Kraus M, Schwarz S (2008) Competition under different reimbursement systems: the concept of an internet-based hospital management game. Eur J Oper Res 185(3):948–963
Reynolds JX (1986) Using DRGs for competitive positioning and practical business planning. Health Care Management Review 11(3):37–55
Rifai AK, Pecenka JO (1990) An application of goal programming in healthcare planning. Int J Oper Prod Manag 10(3):28–37
Robbins WA, Tuntiwongpiboom N (1989) Linear programming a useful tool in case-mix management. Healthc Financ Manage 43(6):114–116
Roth AV, Van Dierdonck R (1995) Hospital resource planning: concepts, feasibility, and framework. Prod Oper Manag 4(1):2–29
Testi A, Tanfani E, Torre G (2007) A three-phase approach for operating theatre schedules. Health Care Manag Sci 10(2):163–172
Van Merode GG, Groothuis S, Hasman A (2004) Enterprise resource planning for hospitals. Int J Med Inform 73(6):493–501
Vanberkel PT, Boucherie RJ, Hans EW, Hurink JL (2014) Optimizing the strategic patient mix combining queueing theory and dynamic programming. Comput Oper Res 43:271–279
Vissers JM (1998) Health care management modelling: a process perspective. Health Care Manag Sci 1(2):77–85
Vissers JM, Bertrand J, De Vries G (2001) A framework for production control in health care organizations. Prod Plan Control 12(6):591–604
Vissers JM, Adan IJ, Dellaert NP (2007) Developing a platform for comparison of hospital admission systems: an illustration. Eur J Oper Res 180(3):1290–1301
Young WW, Swinkola RB, Zorn DM (1982) The measurement of hospital case mix. Med Care 20(5):501–512
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hof, S., Fügener, A., Schoenfelder, J. et al. Case mix planning in hospitals: a review and future agenda. Health Care Manag Sci 20, 207–220 (2017). https://doi.org/10.1007/s10729-015-9342-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10729-015-9342-2