Keywords

operating room scheduling, fuzzy Delphi method, fuzzy set theory, desirability function

 

Authors

  1. Chen, Chung-Kuang
  2. Lin, Cecilia*
  3. Hou, Tung-Hsu**
  4. Wang, Shu-Hui***
  5. Lin, Hong-Mau****

ABSTRACT

Background: Most operating room (OR) scheduling is done by scheduling personnel based on experience or heuristics. Such often results in excessive overtime for medical personnel and poor resource-use efficiencies.

 

Purpose: This study was designed to employ an integrated OR scheduling performance evaluation model (IOSPEM), which integrates quantitative and qualitative multiple objectives, to the improvement of OR scheduling quality.

 

Methods: The fuzzy Delphi method was used to obtain the weight values of time factor, cost factor, and risk factor. The fuzzy set theory was applied to transform qualitative risk measures into quantitative values. The desirability function was utilized to integrate time, cost, and risk factors to develop the IOSPEM. The simulated annealing algorithm was used to develop the scheduling system and test proposed model performance.

 

Results: The proposed IOSPEM successfully integrated the quantitative and qualitative indices into a sole quantitative index. Experiment results show that the IOSPEM incorporating the simulated annealing algorithm is able to obtain the most efficient OR schedule and is helpful in reducing costs and fatigue risks.

 

Conclusions and Implications for Practice: Operating room scheduling will be made more objective and efficient if OR scheduling personnel can simultaneously consider the cost, fatigue risk, and other factors in scheduling. Cost of each OR room should be considered to set appropriate cost coefficients in practical application of the IOSPEM. It is also suggested that other indices (e.g., OR overtime costs and OR nurse fatigue risks) also be considered in the proposed model so as to better reflect the actual scheduling environment. The procedure and methods implemented in this study may be used as the basis for further developing more effective and efficient OR scheduling systems.