Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-24T15:22:13.089Z Has data issue: false hasContentIssue false
  • English
  • Français

Technology Assessment Using Insurance Claims: Example of Prostatectomy

Published online by Cambridge University Press:  10 March 2009

Elliott S. Fisher ,
David J. Malenka ,
John E. Wennberg  and
Noralou P. Roos
Elliott S. Fisher
Affiliation:
Dartmouth Medical School; Veterans Administration Medical Center
David J. Malenka
Affiliation:
Dartmouth Medical School
John E. Wennberg
Affiliation:
Dartmouth Medical School
Noralou P. Roos
Affiliation:
University of Manitoba
Get access Rights & Permissions [Opens in a new window]

Abstract

This article describes the findings of an ongoing assessment of prostatectomy that relied on the use of administrative data bases. Examples of the use of claims data for monitoring outcomes and treatment comparisons are provided, as well as a discussion of the strengths and limitations of administrative data for technology assessment.

Type
Special Section: Measuring Health Care Effectiveness: Use of Large Data Bases for Technology and Quality Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 6 , Issue 2 , January 1990 , pp. 194 - 202
Copyright
Copyright © Cambridge University Press 1990

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

REFERENCES

1Barnes, B. A. Discarded operations: Surgical innovation by trial and error. In Bunker, J. P., Barnes, B. A., & Mosteller, F. (eds.), Costs, risks and benefits of surgery. London: Oxford University Press, 1977, 109–24.Google Scholar
2Barry, M. J., Mulley, A. G., Fowler, F. J., & Wennberg, J. E.Watchful waiting vs. immediate transurethral resection for symptomatic prostatism: The importance of patients' preferences. Journal of the American Medical Association, 1988, 259, 3010–17.CrossRefGoogle ScholarPubMed
3Byar, D. P.Why data bases should not replace randomized clinical trials. Biometrics, 1980, 16, 247–59.Google Scholar
4Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R.A new method for classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Disease, 1987, 40, 373–83.CrossRefGoogle ScholarPubMed
5Chassin, M. R., Brook, R. H., Park, R. E. et al. , Variations in the use of medical and surgical practices by the Medicare population. New England Journal of Medicine, 1986, 314, 285–90.CrossRefGoogle ScholarPubMed
6Coronary Drug Project Research Group. Influence of adherence to treatment and response of cholesterol on mortality in the coronary drug project. New England Journal of Medicine, 1981, 304, 634–37.Google Scholar
7Eddy, D. M.The quality of medical evidence. Health Affairs, 1988, 7, 19–32.CrossRefGoogle ScholarPubMed
8Fowler, F. J., Wennberg, J. E., Timothy, R. P. et al. , Symptom status and quality of life following prostatectomy. Journal of the American Medical Association, 1988, 259, 3018–22.CrossRefGoogle ScholarPubMed
9Grayhack, J. T., & Sadlowski, R. W. Results of surgical treatment of benign prostatic hyperplasia. In Grayhack, , Wilson, , & Scherbenske, (eds.), Benign prostatic hyperplasia, 125–134, DHEW Publication No. NIH, 76–1113. Workshop sponsored by the Kidney Disease and Urology Program of the National Institute of Arthritis, Metabolism and Digestive Diseases, NIH, 1975.Google Scholar
10Hatten, J.Medicare's common denominator: The covered population. Health Care Financing Review, 1980, 2, 53–63.Google ScholarPubMed
11Jencks, S. F., Williams, D. K., & Kay, T. L.Assessing hospital associated deaths from discharge data: The role of length of stay and comorbidities. Journal of the American Medical Association, 1988, 260, 2240–46.CrossRefGoogle ScholarPubMed
12Lave, J., Dobson, A., & Walton, C.The potential use of health care financing administration data sets for health care services research. Health Care Financing Review, 1983, 5, 93–98.Google ScholarPubMed
13Malenka, D. J., Roos, N., Fisher, E. S. et al. , Further study of the increased mortality following transurethral prostatectomy: A chart based analysis. Submitted.Google Scholar
14Moses, L. E., & Brown, B. W.Experiences with evaluating the safety and efficacy of medical technologies. Annual Review of Public Health, 1984, 5, 267–92.CrossRefGoogle ScholarPubMed
15Paul-Shaheen, P., Clark, J. D., & Williams, D.Small area analysis, a review and analysis of the North American literature. Journal of Health Politics, Policy and Law, 1987, 12, 741–809.CrossRefGoogle ScholarPubMed
16Roos, L. L., Nicol, P. J., & Cageorge, S. M.Using administrative data for longitudinal research: Comparisons with primary data collection. Journal of Chronic Disease, 1987, 40, 41–49.CrossRefGoogle ScholarPubMed
17Roos, N. P., Wennberg, J. E., Malenka, D. J. et al. , Mortality and reoperation after open and transurethral resection of the prostate for benign prostatic hyperplasia. New England Journal of Medicine, 1989, 320, 1120–24.CrossRefGoogle ScholarPubMed
18Roper, W. L., Winkenwerder, W., Hackbarth, O. M., & Krakauer, H.Effectiveness in health care: An initiative to evaluate and improve medical practice. New England Journal of Medicine, 1988, 319, 1197–1202.CrossRefGoogle ScholarPubMed
19Stanley, K. E.Prognostic factors for survival in patients with inoperable lung cancer. Journal of the National Cancer Institute, 1980, 65, 25–33.Google ScholarPubMed
20Wennberg, J. E., Roos, N. P., Sola, L. et al. , Use of claims data systems to evaluate health care outcomes: Mortality and reoperation following prostatectomy. Journal of the American Medical Association, 1987, 257, 933–36.CrossRefGoogle ScholarPubMed
21Wennberg, J. E.Dealing with medical practice variations: A proposal for action. Health Affairs, 1984, 3, 6–33.CrossRefGoogle ScholarPubMed