Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-15T19:29:21.670Z Has data issue: false hasContentIssue false

Data Bases for the Assessment of Medical Technologies: Examples from Europe

Published online by Cambridge University Press:  10 March 2009

Felix Gutzwiller
Affiliation:
University of Lausanne
Richard Chrzanowski
Affiliation:
University of Lausanne
Fred Paccaud
Affiliation:
University of Lausanne

Abstract

The assessment of medical technologies has to answer several questions ranging from safety and effectiveness to complex economical, social, and health policy issues. The type of data needed to carry out such evaluation depends on the specific questions to be answered, as well as on the stage of development of a technology.

Basically two types of data may be distinguished: (a) general demographic, administrative, or financial data which has been collected not specifically for technology assessment; (b) the data collected with respect either to a specific technology or to a disease or medical problem.

On the basis of a pilot inquiry in Europe and bibliographic research, the following categories of type (b) data bases have been identified: registries, clinical data bases, banks of factual and bibliographic knowledge, and expert systems. Examples of each category are discussed briefly. The following aims for further research and practical goals are proposed: criteria for the minimal data set required, improvement to the registries and clinical data banks, and development of an international clearinghouse to enhance information diffusion on both existing data bases and available reports on medical technology assessments.

Type
Special Section: Technology Assessment and the Alteration of Medical Practices
Copyright
Copyright © Cambridge University Press 1988

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

A classified bibliography of controlled trials in perinatal medicine 1940–1984. Oxford: Oxford University Press, 1985.Google Scholar
Braakman, R.Data bank of head injuries in three countries. Scottish Medical Journal, 1978, 23, 107–8.CrossRefGoogle ScholarPubMed
Bernstein, L., Siegel, E., & Goldstein, C.The hepatitis knowledge base. Annals of Internal Medicine, 1980, 93, 169–81.CrossRefGoogle ScholarPubMed
Bertrand, M. E. The need for central registration of procedures: The French experience. In The Mainz Symposium of the European Society of Cardiology. Abstracts. Mainz, 1986, 19.Google Scholar
Cristiani, P., Quaglini, S., Stefanelli, M., Barosi, G., & Berzuini, A. Microanemia: An expert system running on microcomputer. In Salomon, R., Blum, B., & Joergensen, M. (eds.), Medinfo 86. Amsterdam: Elsevier, 1986, 8791.Google Scholar
De, Dombal F. et al. , Clinical information science in Leeds. A review. Leeds: ULIS, 1985.Google Scholar
De Wals, Ph., & Lechat, M. (eds.). Eurocat report 1. Surveillance of congenital anomalies. Years 1980–1983. Bruxelles: Catholic University of Louvain, 1986.Google Scholar
Eggimann, B., Paccaud, F., & Gutzwiller, F.Utilisation de la coronarographie en Suisse: Une étude de population. Schweizerische medizinische Wochenschrift, 1987, 117, 747–55.Google Scholar
English, T. A., Bailey, A. R., Dark, J. F., & Williams, W. G.The UK cardiac surgical register 1977–1982. British Medical Journal, 1984, 289, 1205–8.CrossRefGoogle Scholar
European Coronary Surgery Study Group. Long term results of prospective randomised study of coronary artery bypass surgery in stable angina pectoris. Lancet, 1982, 1173–80.CrossRefGoogle Scholar
Feinleib, M.Data bases, data banks and data dredging: The agony and the ecstasy. Journal of Chronic Diseases, 1984, 37, 783–90.CrossRefGoogle ScholarPubMed
Haux, R., Langner, K., Repges, R., & Sauerbrey, U. An expert system for diagnosis and therapy of endocarditis. In DeLotto, I. & Stefanelli, M. (eds.), Artificial intelligence in medicine. Amsterdam: Elsevier, 1985, 339–51.Google Scholar
Institute of Medicine. Assessing medical technologies. Washington, DC: National Academy Press, 1985Google Scholar
Jannssen, R., & Reuter, R. Interactive analysis of transplant data. In DeLotto, I., Stefanelli, M. (eds.), Artificial intelligence in medicine. Amsterdam: Elsevier, 1985, 451–55.Google Scholar
Jeunemaitre, X., Degulet, P., Morice, V. et al. , An expert system connected to a hypertensive patient data base. In Salamon, R., Blum, B., & Joergensen, M. (eds.), Medinfo 86. Amsterdam: Elsevier, 1986, 262–65.Google Scholar
Jennett, B. Personal communication, 09 1986.Google Scholar
Jennett, B.High technology medicine. Oxford: Oxford University Press. 1986.Google Scholar
Laszlo, J.Health registry and clinical data base technology. Journal of Chronic Diseases, 1985, 1, 6778.CrossRefGoogle Scholar
Lips, K. J., Van, der Sluys Veer J., Struyvenberg, A., & Geerdink, R.Genetic predisposition to cancer in man. American Journal of Medicine, 1985, 73, 305–7.CrossRefGoogle Scholar
Modell, B.Chorionic villus sampling. Lancet, 1985, 1, 737–40.CrossRefGoogle ScholarPubMed
Pryor, D., Califf, R., Harrell, F. et al. , Clinical data bases. Medical Care, 1985, 5, 623–47.CrossRefGoogle Scholar
The EC/lC Bypass Study Group. Failure of extracranial-intracranial arterial bypass to reduce the risk of ischemic stroke: Results of an international randomized trial. New England Journal of Medicine, 1985, 313, 1191–200.CrossRefGoogle Scholar
Waterhouse, J., Muir, C., Shanmugaratnam, K., & Powell, J.Cancer incidence infive continents. Volume IV. Lyon: International Agency for Research on Cancer, 1982.Google Scholar
Witte, J. The European registry: Scopes, available data and perspectives. In The Mainz Syinposium of the European Society of Cardiology. Abstracts. Mainz, 1986, 6.Google Scholar