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Could a computer-based system including a prevalence function support emergency medical systems and improve the allocation of life support level?

Gellerstedt, Martin, 1966- (författare)
Högskolan Väst,Avd för datavetenskap och informatik,Department of Informatics, University of Western Sweden, Sweden
Bång, Angela (författare)
Högskolan i Borås,Institutionen för Vårdvetenskap
Herlitz, Johan, 1949 (författare)
Högskolan i Borås,Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine,Division of Cardiology, Sahlgrenska University Hospital, Göteborg, Sweden,[external],Institutionen för Vårdvetenskap
 (creator_code:org_t)
London, UK : Lippincott Williams & Wilkins, Ltd. 2006
2006
Engelska.
Ingår i: Eur J Emerg Med. - London, UK : Lippincott Williams & Wilkins, Ltd.. - 0969-9546 .- 1473-5695. ; 13:5, s. 290-4
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • OBJECTIVES: To evaluate whether a computer-based decision support system could be useful for the emergency medical system when identifying patients with acute myocardial infarction (AMI) or life-threatening conditions and thereby improve the allocation of life support level. METHODS: Patients in the Municipality of Goteborg who dialled the dispatch centre due to chest pain during a period of 3 months. To analyse the relationship between patient characteristics (according to a case record form used during an interview) and the response variables (AMI or life-threatening condition), multivariate logistic regression was used. For each patient, the probability of AMI/life-threatening condition was estimated by the model. We used these probabilities retrospectively to allocate advanced life support or basic life support. This model allocation was then compared with the true allocation made by the dispatchers. RESULTS: The sensitivity, that is, the percentage of AMI patients allocated to advanced life support, was 85.7% in relation to the true allocation made by the dispatchers. The corresponding sensitivity regarding allocation made by the model was 92.4% (P=0.17). The specificity was also slightly higher for the model allocation than the dispatcher allocation. Among the 15 patients with AMI who were allocated to basic life support by the dispatchers, nine died (eight during and one after hospitalization). Among the eight patients with AMI allocated to basic life support by the model, only one patient died (in hospital) (P=0.02). CONCLUSION: A computer-based decision support system including a prevalence function could be a valuable tool for allocating the level of life support. The case record form, however, used for the interview can be refined and a model based on a larger sample and confirmed in a prospective study is recommended.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)
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)

Nyckelord

*Advanced Cardiac Life Support
Aged
*Decision Support Systems
Clinical
Emergency Medical Services/*methods
Female
Health Care Rationing/methods
Humans
Logistic Models
Male
Multivariate Analysis
Myocardial Infarction/diagnosis/*therapy
Prevalence
Sensitivity and Specificity
Sweden
Triage/*methods
Informatics and systems science
Informatics

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