Activity-Based Algorithm for Translating Observed Outpatient Activity into Specialist Working-Hour Requirements Within Community Health Center Catchment Areas

Background/Objectives: In Italy, Ministerial Decree 77/2022 provides the regulatory framework for reorganizing community-based care around community health centers and hub-and-spoke territorial networks. However, translating territorial allocation into specialist working-hour requirements remains a key operational challenge, particularly in low-density and mountainous areas. This study developed an activity-based workload model to translate observed outpatient cardiology activity into estimated specialist working-hour requirements within the hub-and-spoke community health center network of local health authority (ASL 1) Avezzano-Sulmona-L’Aquila, Abruzzo, Italy. Methods: A second-stage workforce planning analysis was conducted using the baseline 30 min territorial configuration from a previously defined allocation framework. Municipal-level outpatient cardiology administrative data for 2019 were linked to standardized procedure scheduling durations and aggregated across the catchments of three hub centers and eight spoke centers according to predefined municipality-to-node assignments. Procedure volumes were converted into annual and weekly workload hours and then into nominal 36 h weekly specialist-schedule equivalents. The resulting estimates represent a pre-pandemic, utilization-based workload scenario derived from observed activity; they should not be interpreted as direct measures of underlying population demand, epidemiological need, or unmet need, nor as validated staffing requirements. Results: The reference network covered 286,832 residents and included 44,039 outpatient cardiology procedures, corresponding to 12,719.8 annual workload hours. These volumes generated 244.6 weekly workload hours, equivalent to 6.79 nominal 36 h weekly specialist-schedule equivalents. Workload was unevenly distributed across the network: the L’Aquila and Sulmona hubs accounted for the largest annual workloads, with 3014.9 and 2894.3 h, respectively, whereas Trasacco was the spoke center with the highest observed workload, with 1775.5 h. Population-standardized indicators showed substantial variation in workload intensity across the catchments, indicating that catchment population size alone did not adequately capture the observed workload differences. Conclusions: Activity-based workload estimation adds an operational workforce layer to hub-and-spoke territorial planning. By translating observed outpatient service-use volumes into specialist working-hour requirements, the model provides a transparent and potentially transferable framework to support the operational planning of community health centers in geographically complex settings. The approach is adaptable to other specialties, territories, and service configurations where comparable activity data, standardized scheduling durations, and territorial assignment inputs are available.