Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic.
Journal
Acta bio-medica : Atenei Parmensis
ISSN: 2531-6745
Titre abrégé: Acta Biomed
Pays: Italy
ID NLM: 101295064
Informations de publication
Date de publication:
11 May 2020
11 May 2020
Historique:
received:
17
04
2020
accepted:
17
04
2020
entrez:
19
5
2020
pubmed:
19
5
2020
medline:
23
5
2020
Statut:
epublish
Résumé
On the 21st of February, the first patient was tested positive for SARS-CoV-2 at Codogno hospital in the Lombardy region. From that date, the Regional Emergency Medical Services (EMS) Trust (AREU) of the Lombardy region decided to apply Business Intelligence (BI) to the management of EMS during the epidemic. The aim of the study is to assess in this context the impact of BI on EMS management outcomes. Since the beginning of the COVID-19 outbreak, AREU is using BI daily to track the number of first aid requests received from 112. BI analyses the number of requests that have been classified as respiratory and/or infectious episodes during the telephone dispatch interview. Moreover, BI allows identifying the numerical trend of episodes in each municipality (increasing, stable, decreasing). 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. Conclusions: 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.
Sections du résumé
BACKGROUND AND AIM OF THE WORK
OBJECTIVE
On the 21st of February, the first patient was tested positive for SARS-CoV-2 at Codogno hospital in the Lombardy region. From that date, the Regional Emergency Medical Services (EMS) Trust (AREU) of the Lombardy region decided to apply Business Intelligence (BI) to the management of EMS during the epidemic. 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 COVID-19 outbreak, AREU is using BI daily to track the number of first aid requests received from 112. BI analyses the number of requests that have been classified as respiratory and/or infectious episodes during the telephone dispatch interview. Moreover, BI allows 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. Conclusions: 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.
Identifiants
pubmed: 32420923
doi: 10.23750/abm.v91i2.9557
pmc: PMC7569617
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
39-44Références
Nat Commun. 2019 Sep 2;10(1):3932
pubmed: 31477707
Lancet Digit Health. 2020 May;2(5):e218-e220
pubmed: 32518898
Lancet. 2020 Apr 11;395(10231):1225-1228
pubmed: 32178769
Stud Health Technol Inform. 2017;235:579-583
pubmed: 28423859
Euro Surveill. 2020 Mar;25(9):
pubmed: 32156327
Lancet Digit Health. 2020 Apr;2(4):e166-e167
pubmed: 32289116
Lancet. 2020 Mar 14;395(10227):e49-e50
pubmed: 32119824
JAMA. 2020 Apr 28;323(16):1545-1546
pubmed: 32167538