The skåne emergency medicine (SEM) cohort

• 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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Health Care Service and Management, Health Policy and Services and Health Economy (hsv//eng)

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Health Sciences (hsv//eng)

Keyword

Humans

Sweden

Emergency Service, Hospital/statistics & numerical data

Emergency Medicine

Female

Male

Decision Support Systems, Clinical

Cohort Studies

Artificial Intelligence

Adult

Artificial intelligence

IDC

Publication and Content Type

art (subject category)

ref (subject category)