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. 2017 Feb 10:2016:772-778.
eCollection 2016.

Predictive Analytics to Support Real-Time Management in Pathology Facilities

Lysanne Lessard  1 , Wojtek Michalowski  2 , Wei Chen Li  2 , Daniel Amyot  2 , Fawaz Halwani  3 , Diponkar Banerjee  3
Affiliations

Predictive Analytics to Support Real-Time Management in Pathology Facilities

Lysanne Lessard et al. AMIA Annu Symp Proc. .

Abstract

Predictive analytics can provide valuable support to the effective management of pathology facilities. The introduction of new tests and technologies in anatomical pathology will increase the volume of specimens to be processed, as well as the complexity of pathology processes. In order for predictive analytics to address managerial challenges associated with the volume and complexity increases, it is important to pinpoint the areas where pathology managers would most benefit from predictive capabilities. We illustrate common issues in managing pathology facilities with an analysis of the surgical specimen process at the Department of Pathology and Laboratory Medicine (DPLM) at The Ottawa Hospital, which processes all surgical specimens for the Eastern Ontario Regional Laboratory Association. We then show how predictive analytics could be used to support management. Our proposed approach can be generalized beyond the DPLM, contributing to a more effective management of pathology facilities and in turn to quicker clinical diagnoses.

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Figures

Figure 1.
Figure 1.
Pathology surgical specimen process at the DPLM
Figure 2.
Figure 2.
Proposed systems architecture at the DPLM
See this image and copyright information in PMC

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