Structural Estimation of the Newsvendor Model: An Application to Reserving Operating Room Time

Published Online:https://doi.org/10.1287/mnsc.1070.0756

References

  • Abouleish A., Dexter F., Epstein R., Lubarsky D., Whitten C., Prough D. Labor costs incurred by anesthesiology groups because of operating rooms not being allocated and cases not being scheduled to maximize operating room efficiency. Anesthesia Analgesia (2003) 96:1109–1113CrossrefGoogle Scholar
  • Aiken L. H., Clarke S. P., Sloane D. M., Sochalski J., Silber J. H. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. J. Amer. Medical Assoc. (2002) 288:1987–1993CrossrefGoogle Scholar
  • Berry S., Levinson J., Pakes A. Automobile prices in market equilibrium. Econometrica (1995) 963(4):841–890CrossrefGoogle Scholar
  • Bickel P. J., Doksum K. A.Mathematical Statistics (2001) 2nd ed.(Prentice Hall, Upper Saddle River, NJ) Google Scholar
  • Brush T., Karnani A. Impact of plant size and focus on productivity: An empirical study. Management Sci. (1996) 42(7):1065–1081LinkGoogle Scholar
  • Cachon G., Graves S., de Kok T. Supply chain coordination with contracts. Handbooks in Operations Research and Management Science: Supply Chain Management (2003) 11(Elsevier, Amsterdam) 229–339CrossrefGoogle Scholar
  • Cachon G., Schweitzer M. Decision bias in the newsvendor problem with known demand distribution: Experimental evidence. Management Sci. (2000) 46(3):404–420LinkGoogle Scholar
  • Charnetski J. R. Scheduling operating room surgical procedures with early and late completion penalty costs. J. Oper. Management (1984) 5:91–102CrossrefGoogle Scholar
  • Chorba R. W. Potential avoidability: A statistic for controlling in-patient utilization in acute care hospitals. Management Sci. (1976) 22(6):694–700LinkGoogle Scholar
  • Cohen M. A., Ho T. H., Ren J. Z., Terwiesch C. Measuring imputed cost in the semiconductor equipment supply chain. Management Sci. (2003) 49(12):1653–1670LinkGoogle Scholar
  • Dexter F., Ledolter J. Bayesian prediction bounds and comparisons of operating room times even for procedures with few or no historical data. Anesthesiology (2005) 103:1259–1267CrossrefGoogle Scholar
  • Dexter F., Traub R. How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time. Anesthesia Analgesia (2002) 94:933–942CrossrefGoogle Scholar
  • Dexter F., Epstein R., Marsh H. M. A statistical analysis of weekday operating room anesthesia group staffing costs at nine independently managed surgical suites. Anesthesia Analgesia (2001) 92:1493–1498CrossrefGoogle Scholar
  • Dexter F., Ledolter J., Wachtel R. Tactical decision making for selective expansion of operating room resources incorporating financial criteria and uncertainty in subspecialties' future workloads. Anesthesia Analgesia (2005a) 100:1425–1432CrossrefGoogle Scholar
  • Dexter F., Traub R., Macario A. How to release allocated operating room time to increase efficiency: Predicting which surgical service will have the most underutilized operating room time. Anesthesia Analgesia (2003) 96:507–512CrossrefGoogle Scholar
  • Dexter F., Macario A., Epstein R., Ledolter J. Validity and usefulness of a method to monitor surgical services' average bias in scheduled case durations. Canadian J. Anesthesia (2005b) 52:935–939CrossrefGoogle Scholar
  • Green L. V., Brandeau M. L., Sainfort F., Pierskalla W. P. Capacity planning and management in hospitals. Operations Research and Health Care: A Handbook of Methods and Applications (2004) (Kluwer Academic Publishers, Norwell, MA) 15–42Google Scholar
  • Green L. V., Meissner J. Developing insights for nurse staffing. (2002) . Working paper, Columbia Business School, New YorkGoogle Scholar
  • Green L. V., Nguyen V. Strategies for cutting hospital beds: The impact on patient service. Health Services Res. (2001) 36:421–442Google Scholar
  • Green L. V., Savin S., Murray M. Providing timely access to care: What is the right patient panel size? Joint Commission J. on Quality and Patient Safety (2007) 33(4):211–218CrossrefGoogle Scholar
  • Green L. V., Savin S., Wang B. Managing competing demands in a medical diagnostic facility. (2003) . Working paper, Columbia Business School, New YorkGoogle Scholar
  • Huang X. A planning model for requirement of emergency beds. J. Math. Appl. Medicine Biol. (1995) 12:345–353CrossrefGoogle Scholar
  • Kahneman D., Tversky A.Choices, Values and Frames (2000) (Cambridge University, Cambridge, UK) CrossrefGoogle Scholar
  • Kwak N. K., Lee C. A linear programming model for human resource allocation in a health-care organization. J. Medical Systems (1997) 21:129–140CrossrefGoogle Scholar
  • Lieberman M. B., Demeester L. Inventory reduction and productivity growth: Linkages in the Japanese automotive industry. Management Sci. (1999) 45(4):466–485LinkGoogle Scholar
  • May J., Strum D., Vargas L. Fitting the lognormal distribution to surgical procedure times. Decision Sci. (2000) 31(1):129–148CrossrefGoogle Scholar
  • Milne R. G., Abebe A., Torsney B. The impact of teaching on hospital costs: A budgetary approach to non-market institutions. J. Oper. Res. Soc. (1989) 40(12):1089–1098CrossrefGoogle Scholar
  • Mueller C. W., McCloskey J. C. Nurses' job satisfaction: A proposed measure. Nursing Res. (1990) 39(2):113–117CrossrefGoogle Scholar
  • Pell J., Sirel J., Marsden A., Ford I., Cobbe S. Effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: Cohort study. British Medical J. (2001) 322:1385–1388CrossrefGoogle Scholar
  • Porteus E. L.Foundations of Stochastic Inventory Theory (2002) (Stanford Business Books, Stanford, CA) CrossrefGoogle Scholar
  • Reiss P., Wolak F. Structural econometric modeling: Rationales and examples from industrial organization. (2006) . Working paper, Stanford University, Stanford, CA, http://www.stanford.edu/preiss/makeit.pdfGoogle Scholar
  • Rust J. Optimal replacement of GMC bus engines: An empirical model of Harold Zucher. Econometrica (1987) 55(5):999–1033CrossrefGoogle Scholar
  • Shader K., Broome M. E., Broome C. D., West M. E., Nash M. Factors influencing satisfaction and anticipated turnover for nurses in an academic medical center. J. Nursing Administration (2001) 31(4):210–216CrossrefGoogle Scholar
  • Smith-Daniels V. A., Schweikhart S. B., Smith-Daniels D. E. Capacity management in health care services: Review and future research directions. Decision Sci. (1988) 19:889–919CrossrefGoogle Scholar
  • Stachota E., Normandin P., O'Brien N., Clary M., Krukow B. Reasons registered nurses leave or change employment status. J. Nursing Administration (2003) 33(2):111–117CrossrefGoogle Scholar
  • Strum D., May J., Vargas L. Modeling the uncertainty of surgical procedure times. Anesthesiology (2000a) 92(4):1160–1167CrossrefGoogle Scholar
  • Strum D., Vargas L., May J. Surgical subspecialty block utilization and capacity planning: A minimal cost analysis model. Anesthesiology (1999) 90(4):1176–1185CrossrefGoogle Scholar
  • Strum D., May J., Sampson A., Vargas L. Estimating times of surgeries with two component procedures. Anesthesiology (2003) 98(1):232–240CrossrefGoogle Scholar
  • Strum D., Sampson A., May J., Vargas L. Surgeon and type of anesthesia predict variability in surgical procedure times. Anesthesiology (2000b) 92:1454–1466CrossrefGoogle Scholar
  • Strum D., Vargas L., May J., Bashein G. Surgical suite utilization and capacity planning: A minimal cost analysis model. J. Medical Systems (1997) 21(5):309–322CrossrefGoogle Scholar
  • Thompson T. P., Brown H. N. Turnover of licensed nurses in skilled nursing facilities. Nursing Econom. (2002) 20(2):66–69Google Scholar
  • Urbach D. R., Bell C. M., Austin P. C. Differences in operative mortality between high- and low-volume hospitals in Ontario for 5 major surgical procedures: Estimating the number of lives potentially saved through regionalization. Canadian Medical Assoc. Res. J. (2003) 168(11):1409–1414Google Scholar
  • Weiss E. N. Models for determining estimated start times and case ordering in hospital operating rooms. IIE Trans. (1990) 22:143–150CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.