The Public Health Workforce Calculator in a Post-COVID Era.
A new tool, the Public Health Workforce Calculator ("Workforce Calculator"), was developed near the onset of the COVID pandemic to help agencies estimate the staffing they would need to fully implement the Foundational Public Health Services (FPHS). The data underlying the Workforce Calculator algorithm was from pre-pandemic time periods.
To assess whether the Workforce Calculator continues to reliably estimate staffing need in a peri-COVID context.
Local health departments participated in the National Association of County and City Health Officials Profile survey, which for a random half of agencies, stratified by jurisdiction size, contained a module that asked them to estimate the FTE they would need to fully implement FPHS. For each of the 108 valid responding agencies, these data were compared with the Workforce Calculator output that the agency would have received to assess whether the Workforce Calculator was concordantly estimating staffing needs.
We assessed concordance between the reported staffing needs and the Workforce Calculator's estimates, both graphically and quantitatively, using Lin's concordance correlation coefficient.
For most FPHS categories, the Workforce Calculator systematically underestimated the amount of staffing needed for full implementation relative to agencies' reported needs.
Post-COVID staffing needs systematically appear more substantial than the pre-COVID data on which the Workforce Calculator was based. An update to the Workforce Calculator using post-COVID data would benefit end users.
To assess whether the Workforce Calculator continues to reliably estimate staffing need in a peri-COVID context.
Local health departments participated in the National Association of County and City Health Officials Profile survey, which for a random half of agencies, stratified by jurisdiction size, contained a module that asked them to estimate the FTE they would need to fully implement FPHS. For each of the 108 valid responding agencies, these data were compared with the Workforce Calculator output that the agency would have received to assess whether the Workforce Calculator was concordantly estimating staffing needs.
We assessed concordance between the reported staffing needs and the Workforce Calculator's estimates, both graphically and quantitatively, using Lin's concordance correlation coefficient.
For most FPHS categories, the Workforce Calculator systematically underestimated the amount of staffing needed for full implementation relative to agencies' reported needs.
Post-COVID staffing needs systematically appear more substantial than the pre-COVID data on which the Workforce Calculator was based. An update to the Workforce Calculator using post-COVID data would benefit end users.