0000000000711796

AUTHOR

Silvia Priori

showing 2 related works from this author

Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

2018

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrh…

Decision support systemProcess (engineering)Computer scienceBig datacomputer.software_genre01 natural sciencesClinical decision support systemlcsh:QA75.5-76.9503 medical and health sciences0302 clinical medicinebig datalcsh:AZ20-999Health care030212 general & internal medicine0101 mathematicsdata analyticsdata integrationImplementationbusiness.industry010102 general mathematicslearning health care cyclelcsh:History of scholarship and learning. The humanitiesData scienceData warehousedata warehouseslcsh:Electronic computers. Computer sciencebusinesscomputerData integrationFrontiers in Digital Humanities
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Reduction of hospitalizations for myocardial infarction in Italy in the COVID-19 era

2020

Abstract Aims To evaluate the impact of the COVID-19 pandemic on patient admissions to Italian cardiac care units (CCUs). Methods and Results We conducted a multicentre, observational, nationwide survey to collect data on admissions for acute myocardial infarction (AMI) at Italian CCUs throughout a 1 week period during the COVID-19 outbreak, compared with the equivalent week in 2019. We observed a 48.4% reduction in admissions for AMI compared with the equivalent week in 2019 (P < 0.001). The reduction was significant for both ST-segment elevation myocardial infarction [STEMI; 26.5%, 95% confidence interval (CI) 21.7–32.3; P = 0.009] and non-STEMI (NSTEMI; 65.1%, 95% CI 60.3–70.3; P …

MaleMyocardial Infarction030204 cardiovascular system & hematologySettore MED/110302 clinical medicineAcute myocardial infarction Cardiac care units STEMI Aged Aged 80 and over COVID-19 Female Hospitalization Humans Italy Male Middle Aged SARS-CoV-2 Betacoronavirus Coronavirus Infections Myocardial Infarction Pandemics Pneumonia ViralCase fatality rate80 and overMedicine030212 general & internal medicineMyocardial infarctionViralAged 80 and overAcute myocardial infarction; Cardiac care units; COVID-19; SARS-CoV2; STEMI; Aged; Aged 80 and over; Female; Hospitalization; Humans; Italy; Male; Middle Aged; Betacoronavirus; Coronavirus Infections; Myocardial Infarction; Pandemics; Pneumonia ViralMiddle AgedHospitalizationItalyFemaleCardiology and Cardiovascular MedicineCoronavirus InfectionsHumanmedicine.medical_specialtyPneumonia ViralFast Track Clinical ResearchCardiac care unitsAcute myocardial infarctionSTEMI03 medical and health sciencesBetacoronavirusCardiac care unitHumansAcute myocardial infarction; COVID-19; Cardiac care units; SARS-CoV2; STEMIcardiovascular diseasesPandemicsAgedBetacoronaviruPandemicbusiness.industryCoronavirus InfectionSARS-CoV-2COVID-19Pneumoniamedicine.diseaseacute myocardial infarction; cardiac care units; COVID-19; SARS-CoV2; STEMIConfidence intervalRelative riskEmergency medicineSettore MED/11 - MALATTIE DELL'APPARATO CARDIOVASCOLARESARS-CoV2Myocardial infarction complicationsObservational studyMyocardial infarction diagnosisbusinessComplication
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