A composite and synthetic index of potentially avoidable hospitalization in adults to assess primary care quality: an application across Italian geopolitical areas

Background Avoidable hospitalizations for Ambulatory Care Sensitive Conditions (ACSC) are key proxy indicators of Primary Care (PC) services quality. Challenges in Italy's National Health Service, worsened by COVID-19, have spurred outpatient care reforms to ultimately reduce avoidable hospitalizations. Objective To provide a synthetic, composite and cross-national index of avoidable hospitalizations in adults, for evaluating PC services performance. Methods Nine avoidable hospitalization indicators for 2017-2019 and 2020-2022 were calculated from discharge data of Italian hospitals. Their standardized z-scores, grouped into five nosological areas, were equally weighted to ensure balanced representation. A final synthetic index for each area was classified into one of five Jenks clusters. Results The national hospitalization rate decreased from 148.17 per 1,000 residents in 2017-2019 to 125.98 in 2020-2022. Before COVID-19, the “low” clusters were 11, whereas the “high” clusters were 14. In 2020-2022, the "low" and "high" clusters changed to 13 and 10, showing a mild improvement. The “medium-low” and “medium-high” clusters reported significant changes, from 29 to 39 and from 29 to 20, respectively. The “medium” clusters have remained essentially unchanged (from 36 to 37). Conclusions The index distribution offers three main insights: consistently low values suggest efficient PC services; high values may indicate weak strategies or ineffective PC policies; heterogeneous distribution shows fragmented policies, implying better integration and evaluation. Despite potential biases involving patient behaviors and healthcare system factors, the synthetic index offers an evaluation tool for PC performance, reducing access inequalities, and guiding targeted improvements.