Subscribe to RSS
Please copy the URL and add it into your RSS Feed Reader.
https://www.thieme-connect.de/rss/thieme/en/10.1055-s-00035037.xml
Methods Inf Med 1996; 35(03): 242-255
DOI: 10.1055/s-0038-1634663
DOI: 10.1055/s-0038-1634663
Original Article
FreeCall, a System for Emergency-Call-Handling Support
Further Information
Publication History
Publication Date:
20 February 2018 (online)
Abstract:
This article describes a system for the optimization of the pre-hospital assessment of emergency, in cases involving thoraco-abdominal complaints and consciousness problems. This assessment is performed by nurses on the basis of a telephone interview at ambulance dispatch centers. The system has a body of biomedical and policy knowledge available to guide the interview and to provide advice.
-
References
- 1 Van der Does E, Lubsen J. Acute Coronary Events in General Practice: the Imminent Myocardial Infarction Rotterdam Study. (PhD thesis) Rotterdam: Erasmus University; 1978
- 2 Beunderman R. Het Hart Verdraagt geen Uitstel. (PhD thesis). University of Amsterdam; 1993. (in Dutch).
- 3 Herlitz J, Hartford M, Blohm M. et al. Effect of a media campaign on delay times and ambulance use in suspected acute myocardial infarction. Am J Cardiol 1989; 64: 90-3.
- 4 Sramek M, Post W, Koster RW. Telephone triage of cardiac emergency calls by dispatchers: a prospective study of 1386 emergency calls. Brit Heart J 1994; 71: 440-5.
- 5 Leprohon J. Nursing Clinical Decision Making in the Context of Emergency Telephone Interactions. (PhD thesis) Montreal: McGill University; 1991
- 6 Adams ID, Chan M, Clifford PC. et al. Computer-aided diagnosis of acute abdominal pain: a multicentred study. Brit Med J 1986; 293: 800-4.
- 7 Goldman L, Cook EF, Brand DA. et al. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med 1988; 318: 797-803.
- 8 Pozen MW, D’Agostino RB, Selker HP, Sytkowski PA, Hood WB. Predictive instrument to improve coronary-care-unit admission practices in acute ischemic heart disease. N Engl J Med 1984; 320: 1273-8.
- 9 Wyatt J. Lessons learnt from the field trial of ACORN, an expert system to advise on chest pain. In: Proceedings Medlnfo 89. Barber B, Cao D, Qin D, Wagner G. ed. Amsterdam: North-Holland; 1989: 111-5.
- 10 NRV. Nationale Raad voor de Volksgezondheid. Advies Kwaliteit van de Ambulancehulpverlening. Technical report. Zoetermeer: 1990. (in Dutch).
- 11 Post WM, Neerincx M, de Greef P, Koster R. A design method for cognitive support applied to emergency call handling. Int J Human-Comput Stud. (acc for publ.).
- 12 Post WM. Knowledge Technology in Pre-Hospital Emergency Management. (PhD thesis). University of Amsterdam; 1996
- 13 Post WM, Wielinga BJ, de Hoog R, Schreiber ATh. Organization modelling in Common KADS: the emergency medical service. (subm for publ).
- 14 Sramek M. Free Call in Acute Myocardial Ischemia: a Support System for Dispatching. (PhD thesis). University of Amsterdam; 1993
- 15 Newell A. The knowledge level. Artif Intell 1982; 18: 87-127.
- 16 Clancey WJ. Heuristic classification. Artif Intell 1985; 27: 289-350.
- 17 Wielinga BJ, Breuker JA. Models of expertise. In: Proceedings ECAI-86 1986; 306-8.
- 18 Van Heijst G, Lanzola G, Schreiber ATh, Stefanelli M. Foundations for a methodology for medical KBS development. Knowl Acquisition 1994; 6: 355-433.
- 19 Schreiber ATh, Wielinga BJ, Akkermans JM, Van de Velde W, Anjewierden A. CML: The CommonKADS conceptual modelling language. In: A Future for Knowledge Acquisition. Proceedings of the 8th European Knowledge Acquisition Workshop EKAW ’94. Volume 867 of Lecture Notes in Artificial Intelligence. Berlin, Heidelberg: Springer-Verlag; 1994: 1-25.
- 20 Pople H. Heuristic methods for imposing structure on ill-structured problems: The structuring in medical diagnosis. In: Artif Intell Med. Szolovits P. ed. Boulder CO: Westview Press; 1982: 119-90.
- 21 Clancey WJ, Letsinger R. NEOMYCIN: Reconfiguring a rulebased expert system for application to teaching. In: Readings in Medical Artificial Intelligence: the First Decade. Clancey WJ, Shortliffe EH. eds. Reading Mass.: Addison-Wesley; 1984: 361-81.
- 22 Patil RS. Artificial intelligence techniques for diagnostic reasoning in medicine. In: Exploring Artificial Intelligence: Survey Talks from the National Conferences on Artificial Intelligence. Shobe HE. eds. San Mateo California: Morgan Kaufmann; 1988: 347-79.
- 23 Ramoni M, Stefanelli M, Magnani L, Barosi G. An epistemological framework for medical knowledge based systems. IEEE Trans SMC 1992; 22: 1-14.
- 24 Buchanan BG, Shortliffe EH. Rule-based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project. Reading Mass: Addison Wesley; 1984
- 25 Weiss SM, Kulikowski CA, Amarel S, Safir A. A model-based method for computer-aided medical decision making. Artif Intell 1978; 11: 145-72.
- 26 Console L, Torasso P. Hypothetical reasoning in causal models. Intern J Intell Systems 1990; 5: 83-124.
- 27 Patel VL, Evans DA, Kaufman DR. A cognitive framework for doctor-patient interaction. In: Cognitive Science in Medicine. Evans DA, Patel VL. eds. Cambridge Mass.: MIT Press; 1989: 257-31.
- 28 Wyatt J, Spiegelhalter D. Evaluating medical expert systems: what to test and how. Med Inform 1990; 15: 205-17.