Journal of Medical Systems

, Volume 18, Issue 5, pp 251–265 | Cite as

A scheduling model for hospital residents

  • Irem Ozkarahan


When medical students finish their school they must go through a horrendous apprenticeship known as hospital residency to be able to practice medicine. During residency, they work at least 16-hr a day, 5-days a week, with 2 or 3 nights on-call. These can turn into 36-hr shifts. This means that many patients are being treated by exhausted novices, who are therefore much more likely to make mistakes. It was one such mistake, leading to the death of a New York woman, which led to serious attempts to reforming working hours of residents. In this paper, we developed a decision model which attempts to schedule residents based on the requirements of the residency program as well as the desires of residents as to days-off, weekends, on-call nights, etc.


Medical Student Decision Model Residency Program Schedule Model Hospital Resident 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Arthur, J., Contributions to the Theory and Applications of Goal Programming, Ph.D. Dissertation, Purdue Univ. 1977.Google Scholar
  2. 2.
    Association of American Medical Colleges, Resident Supervision and Hours.J. Med. Ed. 63(5):419–426, May 1988.Google Scholar
  3. 3.
    Colford, J.M., McPhee, S.J. The raveled sleeve of care: Managing the stresses of residency training.JAMA 261(6):890–894, 1989.Google Scholar
  4. 4.
    Denaro Dire, D., N. Y. limits interns' hours.Mod. Healthcare 18(25):4, 1988.Google Scholar
  5. 5.
    Editorials, No turning back: A blueprint for residency reform.JAMA 261(6):909–910, Feb. 1989.Google Scholar
  6. 6.
    Expert-Choice-Based on The Analytical Hierarchy Process, The Decision Support Software Co., Pittsburgh, PA, 1983.Google Scholar
  7. 7.
    Jones, F., American Association of Medical Colleges Staff Report, Nov. 1992.Google Scholar
  8. 8.
    Lee, S., Goal Programming Methods for Multiple Objective Integer Programs, Op. Research Div. Pub. No. 2, AIIE Inc., Atlanta, Georgia, 1979.Google Scholar
  9. 9.
    Ozkarahan, I., Flexible Nursing Scheduling Support System, Ph.D. Dissertation, Arizona State University, 1987.Google Scholar
  10. 10.
    Saaty, T.L.,The Analytic Hierarchy Process McGraw-Hill, New York, 1980.Google Scholar
  11. 11.
    Schrage, K.,Linear, Integer and Quadratic Programming With Lindo, User's Manual The Scientific Press, Palo Alto, CA, 1984.Google Scholar
  12. 12.
    Siha, S., and Linn, R.J., Zero-one goal programming decision making for selecting technology alternatives: Proc. of AIIE Symposium on Manufacturing and Productivity, 200–206, Toronto, May 1989.Google Scholar
  13. 13.
    Sherali, H.D., Equivalent weights for lexicographic multi-objective programs: Characterizations and computations:Eur. J. Ops. Res. 11(4):367–379, 1982.Google Scholar
  14. 14.
    Sherali, H.D., and Soyster, A.L., Preemptive and non-preemptive multi-objective programming: Relationships and counter examples:J. Optim. Theory Appl. 39(2):173–186, 1983.Google Scholar
  15. 15.
    Sitompul, D., and Randhawa, S.U., Nurse scheduling models: A state of the art review.J. Soc. Health Systems 2(1):62–72 (Spring 1990).Google Scholar
  16. 16.
    Winston, L.W.,Operations Research: Applications and Algorithms PWS-Kent Pub. Co., Boston, MA, 1987.Google Scholar

Copyright information

© Plenum Publishing Corporation 1994

Authors and Affiliations

  • Irem Ozkarahan
    • 1
  1. 1.Department of Industrial EngineeringDokuz Eylul UniversityIzmirTurkey

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