From Data to Intelligence for Health Workforce Planning: Insights From Integrated Primary Care Workforce Planning in Toronto

To make good decisions, health leaders need information about their communities and the health workforce available to meet their needs. Raw data and indicators of population needs and workforce capacity must be transformed into usable intelligence that can support decision-making. Using the case study of integrated primary care workforce planning in Toronto, we outline our workforce planning framework, and with a focus on workforce analysis, describe the inputs and outputs that are needed for planning, key steps in the conversion of data to intelligence, and the impact of the approach. Raw data flow from data partners through a planning model into a six-step workforce analysis that renders the results of data analysis, modelling, synthesis and visualization relevant, and accessible to planners and decision-makers. We highlight important challenges and considerations related to data standardization, comprehensiveness, granularity, accessibility, and timeliness, and envision a system that more effectively supports workforce planning and decision-making.

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Publication Details

Journal
Healthcare Management Forum
Published
2025-10-28
DOI
https://doi.org/10.1177/08404704251365552
Primary Topic
Healthcare Operations and Scheduling Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

From Data to Intelligence for Health Workforce Planning: Insights From Integrated Primary Care Workforce Planning in Toronto

Cynthia Damba, Nathalie Sava, Ruth Trainor, Sarah Simkin et al.
Healthcare Management Forum
Healthcare Operations and Scheduling Optimization
article

From Data to Intelligence for Health Workforce Planning: Insights From Integrated Primary Care Workforce Planning in Toronto

Cynthia Damba, Nathalie Sava, Ruth Trainor, Sarah Simkin, Rachel Frohlich, Ivy Lynn Bourgeault, Bahja Farah
article en

Abstract

To make good decisions, health leaders need information about their communities and the health workforce available to meet their needs. Raw data and indicators of population needs and workforce capacity must be transformed into usable intelligence that can support decision-making. Using the case study of integrated primary care workforce planning in Toronto, we outline our workforce planning framework, and with a focus on workforce analysis, describe the inputs and outputs that are needed for planning, key steps in the conversion of data to intelligence, and the impact of the approach. Raw data flow from data partners through a planning model into a six-step workforce analysis that renders the results of data analysis, modelling, synthesis and visualization relevant, and accessible to planners and decision-makers. We highlight important challenges and considerations related to data standardization, comprehensiveness, granularity, accessibility, and timeliness, and envision a system that more effectively supports workforce planning and decision-making.

Healthcare Management ForumVol. 38(1_suppl)
University of Ottawa (CA), Toronto Public Health (CA), Canadian Women's Health Network (CA), Public Health Ontario (CA)
Openalex Percentile: Top 52%
Healthcare Operations and Scheduling Optimization
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From Data to Intelligence for Health Workforce Planning: Insights From Integrated Primary Care Workforce Planning in Toronto — Cynthia Damba, Nathalie Sava, et al. · Healthcare Management Forum (2025) | TGRS Research Map | TGRS