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.
Simkin et al. (Tue,) studied this question.