Methods Inf Med 1992; 31(03): 193-203
DOI: 10.1055/s-0038-1634870
Original Article
Schattauer GmbH

An Intelligent Computer-Assisted Instruction System Designed for Rural Health Workers in Developing Countries

P. Aegerter
1   Inserm U 88, Paris
,
B. Auvert
1   Inserm U 88, Paris
,
V. Gilbos
2   Médecins Sans Frontières, Paris
,
F. Andrianiriana
2   Médecins Sans Frontières, Paris
,
W. E. Bertrand
3   Tulane School of Public Health, New-Orleans, USA
,
X. Emmanuelli
2   Médecins Sans Frontières, Paris
,
E. Benillouche
1   Inserm U 88, Paris
,
M. F. Landre
1   Inserm U 88, Paris
,
D. Bos
1   Inserm U 88, Paris
› Author Affiliations
Further Information

Publication History

Publication Date:
08 February 2018 (online)

Abstract:

This paper describes an intelligent computer-assisted instruction system that was designed for rural health workers in developing countries. This system, called Consult-EAO, includes an expert module and a coaching module. The expert module, which is derived from the knowledge-based decision support system Tropicaid, covers most of medical practice in developing countries. It allows for the creation of outpatient simulations without the help of a teacher. The student may practice his knowledge by solving problems with these simulations. The system gives some initial facts and controls the simulation during the session by guiding the student toward the most efficient decisions. All student answers are analyzed and, if necessary, criticized. The messages are adapted to the situation due to the pedagogical rules of the coaching module. This system runs on PC-compatible computer.

 
  • REFERENCES

  • 1 WHO. Primary Health Care; Report of the International Conference on Primary Health Care. “Health for ALL” Series no 1. Geneva: World Health Organisation; 1978
  • 2 WHO. Education and Training of Nurses, Teachers and Managers, with Special Regard to Primary Health Care. Technical Report Series no 708. Geneva: World Health Organisation; 1984
  • 3 Kulakow AM. Application of informatics to health care services and training in developing countries. In: Pagès JC, Grémy F, Anderson J. eds. Meeting the Challenge: Informatics and Medical Education. Amsterdam: North-Holland Publ Comp; 1983: 307-12.
  • 4 Goldberger H, Schwenn P. Man-machine symbiosis in the assistance and training of rural health-workers: a proposal. In: Pages JC, Grémy F, Anderson J. eds. Meeting the Challenge: Informatics and Medical Education. Amsterdam: North-Holland Publ Comp; 1983: 295-306.
  • 5 Bertrand WE, Arminana R, Auvert B. Microcomputer applications in the health and social service sectors of developing countries. In: Bhalla AS, James D. eds. New Technologies and Development. Boulder/London: Lynne Rienner Publ; 1988: 127-36.
  • 6 Uplekar MW, Antia NH, Dhumale PS. Sympmedl: computer program for primary health care. Brit Med J 1988; 297: 841-3.
  • 7 Kastner JK, Dawson CR, Weiss SM, Kern KB, Kulikowski CA. An expert consultation system for frontline health workers in primary eye care. J Med Systems 1984; 08: 389-97.
  • 8 Wuwongse V, Yusof K. Experiences in the development of a medial expert system. In: Barber B, Coa D, Qin D, Wagner G. eds. MEDJNF0 89. Amsterdam: North-Holland Publ Comp; 989 244-7.
  • 9 Auvert B, Aegertcr P, Gilbos V. et al. TROPICAID: A portable expert system for medical decision-aid in developing countries. In: Salamon R, Blum B, Jørgensen M. eds. MED INFO 86. Amsterdam: North-Holland Publ Comp; 1986: 222-24.
  • 10 Porenta G, Pfahringer B, Hoberstofer M, Trappl R. A decision support system for village health workers in developing countries. App Artif Intell 1988; 02: 47.
  • 11 Eamairi J, Malasit P, Songsilvilai S, Chong-stitvatana P. Intelligent tutor for medical teaching. In: Proceedings of the Regional Symposium on Computer Science and its Application. Bangkok. 1987
  • 12 Wenger E. Artificial Intelligence and Tutoring Systems. Los Altos: Morgan Kaufmann Publ; 1988
  • 13 Clancey WJ, Letsinger R. NEOMYCIN: Reconfiguring a rule-based expert system for application to teaching. In: Clancey WJ, Shortliffe EH. eds. Readings in Medical Artificial Intelligence: The First Decade. New York: Addison-Wesley; 1984: 361-81.
  • 14 Fieschi M, Joubert M, Fieschi D, Botti G, Michel C, Proudhon H. The Sphynx project. In: De Lotto I, Stefanelli M. eds. Artificial Intelligence in Medicine. Amsterdam: Elsevier Science Publ; 1985: 107-19.
  • 15 Minsky M. A framework for representing knowledge. In: Winston PH. ed. The Psychology of Computer Vision. New York: McGraw-Hill; 1975: 211-77.
  • 16 Pople HE. Evolution of an expert system: from Internist to Caduceus. In: De Lotto I, Stafanelli M. eds. Artificial Intelligence in Medicine. Amsterdam: Elsevier Science Publ; 1985: 179-208.
  • 17 WHO. Selection of Essential Drugs. Technical Report Series no 641. Geneva: World Health Organisation; 1980
  • 18 Pauker SG, Gorry GA, Kassirer JP, Schwartz WB. Toward the simulation of clinical cognition: taking a present illness by computer. Amer J Med 1976; 60: 981-95.
  • 19 Werner D. Where There is No Doctor. London: Macmillan; 1981
  • 20 Essex BJ. Diagnostic Pathways in Clinical Medicine. Medicine in the Tropics Series. Edinburgh: Churchill Livingstone; 1980
  • 21 Kassirer JP, Kopelman RI. Cognitive errors in diagnosis: instantiation, classification and consequences. Am J Med 1989; 86: 433-40.
  • 22 Goldstein IP. The genetic graph: a representation for the evolution of procedural knowledge. Int J Man-Machine Studies 1979; 11: 51-77.
  • 23 Self J. Student models: what use are they?. In: Lewis R, Ercoli P. eds. Proceedings of Artificial Intelligence Tools in Education. Amsterdam: North-Holland Publ Comp; 1987
  • 24 De Dombal FT, Staniland JR, Clamp SE. Geographical variation in disease presentation. Med Decis Making 1981; 01: 59-69.
  • 25 Marcenmac P, Herin-Aime D. Transferring knowledge in an object oriented context. In: Proceedings of the Fifth International Conference on Technology and Education. Edinburgh 1988: 456-60.
  • 26 Parker RC, Miller RA. Creation of realistic appearing simulated patient cases using the INTERN1ST-1/QMR knowledge base and interrelationship properties of manifestations. Meth Inform Med 1989; 28: 346-51.
  • 27 Schmidt HG, Norman GR, Boshuizen HPA. A cognitive perspective on medical expertise: theory and implications. Acad Med 1990; 19: 611-21.
  • 28 Elstein AS, Schulman LS, Sprafka SA. Medical problem solving: a ten-year retrospective. Eval and the Health Professions 1990; 13: 5-36.
  • 29 Turner CW, Lincoln MJ, Haug P. et al. Iliad Training Effects: A Cognitive Model and Empirical Findings. In: Clayton PD. ed. Proceedings of the Fifteenth Annual Symposium on Computer Applications in Medical Care. New York: McGraw-Hill; 1991: 68-72.
  • 30 Clancey WJ. From Guidon to Neomycin and Heracles in twenty short lessons. ONR Tech Rep 15. STAN-CS-87-1172. Stanford Univ Calif. 1986
  • 31 McCoy KF. Generating context-sensitive responses to object-related misconceptions. Artif Intell 1989; 41: 157-95.
  • 32 Auvert B, Aegerter P, Van Look F. et al. A hand-held decision-aid system designed for rural health workers. Comp Biomed Res 1986; 19: 80-9.
  • 33 Linderholm O. Mind Melding. How far can the human interface go?. Byte (Special Edition) 1991; 11: 41-6.
  • 34 Gill KS. Artificial intelligence and social action: education and training. In: Goran-zon B, Josefson I. eds. Knowledge, Skills and Artificial Intelligence. Berlin: Springer-Verlag; 1987: 77-92.