Examinator: Kristofer Bengtsson
Healthcare staff scheduling has been renowned for its correlation with service quality, care outcome, and staff turnover rate. Nevertheless, the complexity of the process usually impedes the hospital from achieving those goals. Particularly at the emergency department of Siriraj Hospital, the complications in scheduling are expedited by the high number of registered nurses (RNs) and the policy for ensuring adequate care service. To enhance the efficacy of human resource management, this thesis investigates the optimization model’s capability in the on-duty scheduling of RNs.
The scheduling requirements were collected from the interviews with four stakeholders from the management team and the governed staff. The service blueprint was created to visualize the scheduling process, and the mathematical model was formulated following the collected requirements. There are two optimization models developed in this study, i.e., the mixed integer programming (MIP) model and the genetic algorithm (GA) model. Two sets of scheduling data for testing the models were obtained from the past RNs schedules in May-June and July-August 2021.
The performance comparison between the MIP and GA model demonstrated the inefficiency of GA in optimizing the highly constrained problem, as it can provide only 3.95% of evaluation metrics with better outcomes than MIP. In comparing manual and MIP-optimized schedules, both approaches provide more than half of the evaluation metrics with unchanged outcomes, thus having comparable performance in optimizing most of the schedule’s features.
However, MIP can significantly optimize 24% to 25% of the metrics while having only 6.58% to 9.21% of the metrics with deteriorated outcomes compared to the manual approach. As a result, the MIP optimization model possesses more superior performance than the GA model and manual approach in optimizing the scheduling of RNs at the emergency department of Siriraj Hospital.
The MIP optimization in reducing work stress, promoting staff satisfaction, providing fairness, conforming to the policy, and cutting scheduling time can lead to excellence in service quality and care outcome while lowering the turnover rate. Consequently, the optimization of healthcare staff scheduling with the MIP model exerts the capability of human resource management to its greater extent.
Welcome to the presentation.