Literature DB >> 26958230

Developing the Pathologists' Monthly Assignment Schedule: A Case Study at the Division of Anatomical Pathology of The Ottawa Hospital.

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


  1 in total

1.  Genetic algorithm for scheduling of laboratory personnel.

Authors:  J C Boyd; J Savory
Journal:  Clin Chem       Date:  2001-01       Impact factor: 8.327

  1 in total
  1 in total

1.  Predictive Analytics to Support Real-Time Management in Pathology Facilities.

Authors:  Lysanne Lessard; Wojtek Michalowski; Wei Chen Li; Daniel Amyot; Fawaz Halwani; Diponkar Banerjee
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.