The equivalent value (EV)-based workload assessment of primary healthcare workers in Beijing, China.

BACKGROUND

Quantitative methods for estimating the workload of primary healthcare (PHC) workers are essential for improving the performance of PHC institutions. However, measuring the workload of PHC workers is challenging due to the diverse and complex range of services covered by PHC. This study aims to use an equivalent value (EV)-based approach to assess the workload of PHC workers and inform policymakers about the current workload burden in Beijing, China.

METHODS

The EV-based workload assessment system was designed by three main steps: identifying the list of essential PHC service items provided by PHC workers, quantifying the EV of each service item, and calculating the corresponding workload for PHC workers and community health centers (CHCs). The study included 18 CHCs, which were divided into three groups based on population density and topography: Group I (eight urban CHCs), Group II (six CHCs in semi-mountainous areas), and Group III (four CHCs in mountainous areas). Data were collected from local health information system, which automatically collected real-time service volume data for 500 PHC service items at 18 CHCs in the sample district in Beijing from 2017 to 2021.

RESULTS

This study identified 503 essential PHC service items and defined their EVs. The theoretical full-capacity workload per PHC worker was 6024 EVs, serving as the base workload. The actual annual workload per PHC worker was 7240.0 EVs during 2017-2021. The base workload per budgeted position for the three types of CHCs was 6468.6 EVs for Group I, 5268.5 EVs for Group II, and 5038.7 EVs for Group III. Compared with the actual workload of 7702.3 EVs, 6568.3 EVs, and 5979.0 EVs in each group, respectively, all PHC workers in the sample district were overburdened during the study period.

CONCLUSIONS

The EV-based method provides a feasible solution for comprehensively assessing the workload of publicly funded PHC institutions in other regions. This study offers valuable insights to help local policymakers understand the workload burden of PHC workers, objectively evaluate their performance, and guide future health workforce planning.