| Literature DB >> 26958230 |
Amine Montazeri1, Jonathan Patrick1, Wojtek Michalowski1, Diponkar Banerjee2.
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.Mesh:
Year: 2015 PMID: 26958230 PMCID: PMC4765654
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076