JMIR Publications

ABSTRACT

Background:

In Italy, it has been difficult to accurately quantify hospital admissions of patients with a COVID-19 diagnosis using the Hospital Information System (HIS), mainly due to the heterogeneity of codes used in the hospital discharge records (HDR) during the different waves.

Objective:

The objective of the study was to define a specific combination of codes to identify the COVID-19 hospitalisations within the HIS and to investigate the risk factors associated with mortality due to COVID-19 among patients admitted to the Italian hospitals in 2020.

Methods:

A retrospective study was conducted using the HDR, provided by more than 1,300 public and private Italian hospitals. Inpatient hospitalisations were detected by implementing an algorithm based on specific ICD-9-CM codes combinations. Hospitalisations were analyzed by different clinical presentations associated with diagnoses of COVID-19. In addition, two multivariable Cox regression models were performed among “due to COVID-19” patients from 1st January 2020 to 31st December 2020, in order to investigate potential risk factors associated with 30-day death and the temporal changes over the course of the pandemic; in particular, the 30-day death rates during the first and the second waves were analysed by the three main geographical areas (North, Centre, South and Islands) and by wards of discharge (ordinary and intensive care).

Results:

We identified a total of 325,810 hospitalisations with COVID-19-related diagnosis codes, of which 73.4% classified as “due to COVID-19”, 14.5% as “SARS-CoV-2 positive, but not due to COVID-19”, and 12.1% as “suspected COVID-19” hospitalisations. The cohort of “due to COVID-19” patients included 205,048 patients, with a median age of 72 years and with higher prevalence of male (almost 61%). The overall 30-day death rate among patients in hospital due to COVID-19 was 9.9 per 1,000 person-days. Mortality was lower for women (HR= 0.83; P<.001) and for patients coming from High Migration Pressure Countries (HMPC), especially Northern Africans (HR= 0.65; P<.001) and Central-Eastern Europeans (HR= 0.66; P<.001), compared to patients coming from Italy and Developed Countries. In the southern regions and Islands, mortality was higher compared to the northern regions (HR= 1.17; P<.001), especially during the second wave among patients with a transfer in Intensive Care Units (HR= 2.52; P<.001).

Conclusions:

To our knowledge, the algorithm is the first attempt to define, at national level, selection criteria for identifying COVID-19 hospitalisations within the Hospital Information System. The implemented algorithm will be used to monitor the pandemic overtime and the patients selected in 2020 will be followed-up in the next years in order to assess the long term COVID-19 effects.