The First 110,593 COVID-19 Patients Hospitalised in Lombardy: A Regionwide Analysis of Case Characteristics, Risk Factors and Clinical Outcomes.

Objectives: To describe the monthly distribution of COVID-19 hospitalisations, deaths and case-fatality rates (CFR) in Lombardy (Italy) throughout 2020. Methods: We analysed de-identified hospitalisation data comprising all COVID-19-related admissions from 1 February 2020 to 31 December 2020. The overall survival (OS) from time of first hospitalisation was estimated using the Kaplan-Meier method. We estimated monthly CFRs and performed Cox regression models to measure the effects of potential predictors on OS. Results: Hospitalisation and death peaks occurred in March and November 2020. Patients aged ≥70 years had an up to 180 times higher risk of dying compared to younger patients [70-80: HR 58.10 (39.14-86.22); 80-90: 106.68 (71.01-160.27); ≥90: 180.96 (118.80-275.64)]. Risk of death was higher in patients with one or more comorbidities [1: HR 1.27 (95% CI 1.20-1.35); 2: 1.44 (1.33-1.55); ≥3: 1.73 (1.58-1.90)] and in those with specific conditions (hypertension, diabetes). Conclusion: Our data sheds light on the Italian pandemic scenario, uncovering mechanisms and gaps at regional health system level and, on a larger scale, adding to the body of knowledge needed to inform effective health service planning, delivery, and preparedness in times of crisis.

A commentary on the value of hospital data for covid-19 pandemic surveillance and planning.

Hospital data for covid-19 surveillance, planning and modelling are challenging to find worldwide in public aggregation portals. Detailed covid-19 hospital data provides insights into covid-19's health burden including identifying which sociodemographic groups are at greatest risk of covid-19 morbidity and mortality. Timely hospital data is the best source of information for actionable forecasts and projection models of hospital capacity, including critical resources such as intensive care unit beds and ventilators that take time to plan or procure. A challenge to generate timely and detailed hospital data is the reliance on separation or discharge abstracts and census counts. What are needed are well-maintained lists of patients hospitalized with covid-19. From the standpoint of public health and health services researchers and practitioners, we describe the role of hospital data for studying covid-19, why admission data are hard to find, and how improved data infrastructure can meet surveillance and planning needs in the near future. Modern hospital electronic health records can create covid-19 patient lists and these decision support tools are increasingly used for research. These tools can generate patient lists that are transmitted and combined with public health data systems.