Mattias Ohlsson
Professor
The skåne emergency medicine (SEM) cohort
Författare
Summary, in English
BACKGROUND: In the European Union alone, more than 100 million people present to the emergency department (ED) each year, and this has increased steadily year-on-year by 2-3%. Better patient management decisions have the potential to reduce ED crowding, the number of diagnostic tests, the use of inpatient beds, and healthcare costs.
METHODS: We have established the Skåne Emergency Medicine (SEM) cohort for developing clinical decision support systems (CDSS) based on artificial intelligence or machine learning as well as traditional statistical methods. The SEM cohort consists of 325 539 unselected unique patients with 630 275 visits from January 1st, 2017 to December 31st, 2018 at eight EDs in the region Skåne in southern Sweden. Data on sociodemographics, previous diseases and current medication are available for each ED patient visit, as well as their chief complaint, test results, disposition and the outcome in the form of subsequent diagnoses, treatments, healthcare costs and mortality within a follow-up period of at least 30 days, and up to 3 years.
DISCUSSION: The SEM cohort provides a platform for CDSS research, and we welcome collaboration. In addition, SEM's large amount of real-world patient data with almost complete short-term follow-up will allow research in epidemiology, patient management, diagnostics, prognostics, ED crowding, resource allocation, and social medicine.
Avdelning/ar
- EpiHealth: Epidemiology for Health
- Internmedicin - epidemiologi
- MultiPark: Multidisciplinary research focused on Parkinson´s disease
- EXODIAB: Excellence of Diabetes Research in Sweden
- Kardiovaskulär forskning - hypertoni
- LU profilområde: Naturbaserade framtidslösningar
- EPI@LUND
- Kirurgi och folkhälsa
- eSSENCE: The e-Science Collaboration
- Beräkningsvetenskap för hälsa och miljö
- LU profilområde: Naturlig och artificiell kognition
- Artificiell intelligens och thoraxkirurgisk vetenskap (AICTS)
- Akutsjukvård
- Avdelningen för arbets- och miljömedicin
- Centrum för miljö- och klimatvetenskap (CEC)
- Electrocardiology Research Group - CIEL
Publiceringsår
2024-04-26
Språk
Engelska
Sidor
1-8
Publikation/Tidskrift/Serie
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
Volym
32
Dokumenttyp
Artikel i tidskrift
Förlag
BioMed Central (BMC)
Ämne
- Health Care Service and Management, Health Policy and Services and Health Economy
Nyckelord
- Humans
- Sweden
- Emergency Service, Hospital/statistics & numerical data
- Emergency Medicine
- Female
- Male
- Decision Support Systems, Clinical
- Cohort Studies
- Artificial Intelligence
- Adult
Aktiv
Published
Projekt
- AIR Lund - Artificially Intelligent use of Registers
Forskningsgrupp
- Internal Medicine - Epidemiology
- Cardiovascular Research - Hypertension
- EPI@LUND
- Surgery and public health
- Computational Science for Health and Environment
- Artificial Intelligence in CardioThoracic Sciences (AICTS)
- Emergency medicine
- Electrocardiology Research Group - CIEL
ISBN/ISSN/Övrigt
- ISSN: 1757-7241