Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic

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Giuseppe Maria Sechi
Maurizio Migliori
Gabriele Dassi
Andrea Pagliosa
Rodolfo Bonora
Aurea Oradini-Alacreu http://orcid.org/0000-0003-2975-6859
Anna Odone http://orcid.org/0000-0002-5657-9774
Carlo Signorelli
Alberto Zoli
AREU COVID-19 Response Team

Keywords

Business Intelligence; Emergency Medical Services; SARS-CoV-2; COVID-19; coronavirus; Italy

Abstract

Background and aim of the work: 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: 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: 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.

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References

1. Azienda Regionale Emergenza Urgenza. http://www.areu.lombardia.it/
2. Chen H, Chiang R.H.L., and Storey V.C., Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36(4), 2012, pp. 1165-1188.
3. Loewen L, Roudsari A. Evidence for Business Intelligence in Health Care: A Literature Review. Stud Health Technol Inform. 2017;235:579-583. Review.

4. Remuzzi A., Remuzzi G. COVID-19 and Italy: what next? Lancet. 2020 Mar

5. Spiteri G, Fielding J, Diercke M, Campese C, Enouf V, Gaymard A, Bella A, Sognamiglio P, Sierra Moros MJ, Riutort AN, Demina YV, Mahieu R, Broas M, Bengnér M, Buda S, Schilling J, Filleul L, Lepoutre A, Saura C, Mailles A, Levy-Bruhl D, Coignard B, Bernard-Stoecklin S, Behillil S, van der Werf S, Valette M, Lina B, Riccardo F, Nicastri E, Casas I, Larrauri A, Salom Castell M, Pozo F, Maksyutov RA, Martin C, Van Ranst M, Bossuyt N, Siira L, Sane J, Tegmark-Wisell K, Palmérus M, Broberg EK, Beauté J, Jorgensen P, Bundle N, Pereyaslov D, Adlhoch C, Pukkila J, Pebody R, Olsen S, Ciancio BC. First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020. Euro Surveill. 2020 Mar;25(9).

6. Grasselli G., Pesenti A., Cecconi M. Critical case utilization for the COVID-19 outbreak in Lombardy, Italy. JAMA Online first March 13, 2020.

7. Spina S, Marrazzo F, Migliari M, Stucchi R, Sforza A, Fumagalli R. The response of Milan’s Emergency Medical System to the COVID-19 outbreak in Italy. Lancet 2020; 395:e49-e50

8. D.G.R. nº1964 del 06-07-2011. Soccorso sanitario extraospedaliero- aggiornamento n. DGR 37434/1998, n. 45819/1999, n. 16484/2004 e n. 1743/2006

9. McCall B. COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread. Lancet Digit Health 2020. doi: 10.1016/S2589-7500(20)30054-6

10. Buckee C. Improving epidemic surveillance and response: big data is dead, long live big data. Lancet Digit Health. 2020 Mar. doi: 10.1016/S2589-7500(20)30059-5

11. George DB, Taylor W, Shaman J, Rivers C, Paul B, O'Toole T, Johansson MA, Hirschman L, Biggerstaff M, Asher J, Reich NG. Technology to advance infectious disease forecasting for outbreak management. Nat Commun. 2019 Sep 2;10(1):3932. doi: 10.1038/s41467-019-11901-7.

12. Ashrafi N, Kelleher L, & Kuilboer J-P. (2014). The impact of business intelligence on healthcare delivery in the USA. Interdisciplinary Journal of Information, Knowledge, and Management, 9, 117-130.