Previously submitted to: JMIR Public Health and Surveillance (no longer under consideration since Jun 29, 2026)
Date Submitted: Apr 2, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic
ABSTRACT
Background:
Background:
In Italy on the 21st of February, the first patient was tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Codogno hospital in the Lombardy region. From that date, the Regional Emergency Medical Services (EMS) Trust (Azienda Regionale Emergenza Urgenza, AREU) of the Lombardy region decided to apply Business Intelligence (BI) to the management of EMS during the epidemic.
Objective:
Objective:
The aim of the study is to assess in this context the impact of BI on EMS management outcomes.
Methods:
Methods:
Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, in February 2020, AREU is using BI daily to track the number of first aid requests received from 112 (Public Safety Answering Point 1). BI analyses the number of requests that have been classified as respiratory and/or infectious episodes during the telephone dispatch interview. Moreover, BI allows analysing the pattern of the epidemic, identifying the numerical trend of episodes in each municipality (increasing, stable, decreasing).
Results:
Results:
AREU decides to reallocate in the territory the resources based on real-time data recorded and elaborated by BI. Indeed, based on that data, the numbers of vehicles and personnel have been implemented in the municipalities that registered more episodes and where the clusters are supposed to be. BI has been of paramount importance in taking timely decisions on the management of EMS during COVID-19 outbreak in the Lombardy region.
Conclusions:
Conclusion: Even if there is little evidence-based literature focused on BI impact within the health care, this study suggests that BI can be usefully applied to promptly identify clusters and patterns of the SARS-CoV-2 epidemic and, consequently, make informed decisions that can improve the EMS management response to the outbreak.
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