Assessment of the regional healthcare services' resilience during the COVID-19 pandemic: the Italian model
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Center of Epidemiology, Biostatistics and Medical Information Technology, Università Politecnica delle Marche, Italy
Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Italy
Center of Epidemiology, Biostatistics and Medical Information Technology, Italy
Department of Biomedical Sciences and Public Health, Università Politecnica delle Marche, Italy
Department of Health Activities and Epidemiological Observatory, Italy
Regional Health Authority, Sicily Region, Italy
Department of Epidemiology, Lazio Regional Health Service, Italy
Regional Health Agency of Marche, Italy
Department of Health Planning, Italian Health Ministry, Italy
Publication date: 2023-04-27
Popul. Med. 2023;5(Supplement):A1932
Background and Objective: The Italian Ministry of Health monitors the regional healthcare provided to citizens through annual indicators. The COVID-19 pandemic forced healthcare services to change to manage SARS-CoV-2 infections. A “dedicated system” is needed to monitor the healthcare provided by regions in 2020. The aim of the study is to experiment the “dedicated system” in three regions (R1, R2, R3). Methods: Two process indicators were evaluated: PDTA-06.1 (% of new women operated for breast cancer with a mammography within 60 days prior to surgery), and PDTA-AMI (% of hospitalized subjects with an Acute Myocardial Infarction-STEMI diagnosis treated with PTCA within 2 days). For both indicators, the 2020 and 2017-2019 cohorts were identified through healthcare utilization databases and matched using propensity score. Four COVID-19 periods were compared: pre-pandemic (P1: January 1-February 19), first wave (P2: February 20-May 3), restrictions easing (P3: May 4-September 30), second wave (P4: October 1-December 31). The effect of the cohort (2020 vs. 2017-2020), periods (P1 vs. P2, P3, P4), and their interaction were estimated using multiple Cox (PDTA-06.1) and logistic (PDTA-AMI) models. Hazard ratios (HR) and 95% Confidence Interval (95%CI) were reported. Results PDTA-06.1: The interaction term shows that in 2020 the timeliness of breast cancer surgery decreases as P2 exposure time increases (R1: HR=0.67, 95% CI 0.58-0.77), while it increases as P3 (R1: HR=1.52, 95%CI 1.36-1.70; R2: HR=1.76, 95%CI 1.18-2.64) and P4 exposure time (R2: HR=1.69, 95%CI 1.04-2.75) increases. PDTA-AMI: The probability of timely receiving PTCA treatment during 2020 periods did not change in any region. Conclusions: The reduction in timeliness observed during the first wave was subsequently regained (PDTA-06.1), demonstrating the health service’s resilience. The acute treatment (PDTA-AMI) was ensured as in previous years. The “dedicated system” is a useful tool to analyse the impact of the pandemic on healthcare service.
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