The DOI matches its Crossref record.
A Method for the Detailed Assessment of the Appropriateness of Medical Technologies
Abstract
The standard way to assess medical technologies is to conduct a randomized clinical trial. Patients are randomly assigned to groups receiving alternative treatments, and outcomes are monitored over a long period of time. For example, some victims of left main coronary artery disease may undergo coronary artery bypass surgery, and others may receive medical treatment with nitroglycerine and beta blockers. Comparison of five-year mortality and morbidity in the two groups helps to determine the relative appropriateness of the two procedures. In addition, information about quality of life and cost can also be collected and compared.
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Citations
Cited by
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Treatment of complex PTSD: results of the ISTSS expert clinician survey on best practices.
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Metadata
- Authors
- Brook, R. H., Chassin, M. R., Fink, A., Solomon, D. H., Kosecoff, J., & Park, R. E.
- Venue
- International Journal of Technology Assessment in Health Care
- Publisher
- Cambridge University Press (CUP)
- Published
- 1986-01
- Volume
- 2
- Issue
- 1
- Pages
- 53-63
- ISSN
- 0266-4623 (ISSN-L)
- 1471-6348
- OpenAlex
- W2089889400
- Cited by
- 762
- References
- 0
- FWCI
- 1.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Method for the Detailed Assessment of the Appropriateness of Medical Technologies. https://app.cochat.ai/papers/10.1017/s0266462300002774
- The paper
- Brook, R. H., Chassin, M. R., Fink, A., Solomon, D. H., Kosecoff, J., & Park, R. E. (1986). A Method for the Detailed Assessment of the Appropriateness of Medical Technologies. International Journal of Technology Assessment in Health Care. https://doi.org/10.1017/s0266462300002774
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.