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Developing the Pathologists' Monthly Assignment Schedule: A Case Study at the Division of Anatomical Pathology of The
Amine Montazeri1, Jonathan Patrick1, Wojtek Michalowski1
1Telfer School of Management, University of Ottawa, Ottawa, ON.
Insights
Clinical managers can now optimize pathologist scheduling with a new decision support tool. This model streamlines the assignment of daily pathology requests, considering complex constraints for efficient workload distribution.
Area of Science:
- * Anatomical Pathology
- * Operations Research
- * Healthcare Management
Background:
- * Manually assigning daily pathology requests to pathologists is time-consuming and complex.
- * Pathology divisions face significant challenges due to large request volumes and diverse pathologist sub-specialties.
- * Dynamic changes require frequent recalculation of assignment schedules, considering numerous constraints.
Purpose of the Study:
- * To develop an analytics optimization model for creating optimal monthly assignment schedules.
- * To embed this model into a decision support tool for clinical managers.
- * To improve the efficiency and feasibility of pathologist workload distribution.
Main Methods:
- * Development of an analytics optimization model.
- * Integration of the model into a user-friendly decision support tool.
- * Validation of the tool using real-world data from a hospital's anatomical pathology division.
Main Results:
- * The decision support tool effectively determines optimal monthly assignment schedules.
- * The model successfully incorporates constraints such as pathologist availability and sub-specialty mix.
- * The tool provides a validated solution for a complex operational problem.
Conclusions:
- * The developed decision support tool significantly enhances the process of assigning pathology requests.
- * This optimization model offers a feasible and efficient solution for clinical managers in anatomical pathology.
- * The validated tool can be applied to improve resource allocation and scheduling in similar healthcare settings.
Abstract:
In the Division of Anatomical Pathology of a teaching hospital at the beginning of each month, clinical managers assign expected daily pathology requests to the pathologists on duty. Since the number of these requests is usually large and a division employs a number of pathologists with different sub-specialties, the size of the problem is significant and finding a feasible assignment schedule manually is time-consuming. Moreover, every time there is a need to change, a new assignment schedule needs to be developed taking into account all the pre-defined constraints including pathologists' availability, sub-specialty mix, teaching/research releases, etc. In this paper we describe an analytics optimization model embedded in a decision support tool that helps the clinical managers of the division determine the optimal monthly assignment schedule. The decision support tool has been validated using data from the Division of Anatomical Pathology at The Ottawa Hospital in Ottawa, Ontario, Canada.
