ArticleActa bio-medica : Atenei Parmensis2020
Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic.
Article in Acta bio-medica : Atenei Parmensis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- Mandatory First-Aid Training in the Workplace: An Epidemiological Assessment of the Use of Acetylsalicylic Acid Therapy.Epidemiologia (Basel, Switzerland) · 2025Article
- Usefulness of business intelligence to guide antimicrobial treatment decision in infections by infrequent microorganism such asRevista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2025Article
- Emergency medical service interventions and experiences during pandemics: A scoping review.PloS one · 2024Article
- The Emergency Performance of the Hungarian Ambulance Service during the COVID-19 Pandemic.Healthcare (Basel, Switzerland) · 2022Article
- Changes to the Major Trauma Pre-Hospital Emergency Medical System Network before and during the 2019 COVID-19 Pandemic.Journal of clinical medicine · 2022Article
- Smart-working policies during COVID-19 pandemic: a way to reduce work-related traumas?Internal and emergency medicine · 2022Article
- Cardiopulmonary resuscitation missed by bystanders: Collateral damage of coronavirus disease 2019.Acta anaesthesiologica Scandinavica · 2022Article
- The Impact of COVID-19 on Lombardy Region ST-Elevation Myocardial Infarction Emergency Medical System Network-A Three-Year Study.Journal of clinical medicine · 2022Article
- [COVID-19 Stress test for ensuring emergency healthcare: strategy and response of emergency medical services in Berlin].Der Anaesthesist · 2021Review
- The Italian Covid-19 Phase 2 in Piacenza: results of the first semester of 2020 and future prospective of new orthopedics surgical procedures.Acta bio-medica : Atenei Parmensis · 2020Article
- COVID-19 mortality rate in nine high-income metropolitan regions.Acta bio-medica : Atenei Parmensis · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and aim of the workOn 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.
methodsSince 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).
resultsAREU 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.