Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-25T04:20:16.713Z Has data issue: false hasContentIssue false
  • English
  • Français

Peaks and Pits of Using Large Data Bases to Measure Quality of Care

Published online by Cambridge University Press:  10 March 2009

Ann Barry Flood
Ann Barry Flood
Affiliation:
University of lllinois, Urbana–Champaign
Get access Rights & Permissions [Opens in a new window]

Abstract

This review of the advantages (peaks) and problems (pits) of large data bases to study quality contrasts their suitability with randomized control trials. Researchers need to advise policymakers and others about when statistically significant differences in quality are also politically and socially significant and deserve responsible reactions.

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. 253 - 262
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

1Brook, R. H., & Lohr, K. A.Efficacy, effectiveness, variations, and quality: Boundary- crossing research. Medical Care, 1985, 23, 710–22.CrossRefGoogle ScholarPubMed
2Bunker, J. P., Forrest, W. H. Jr, Mosteller, F., & Vandam, L. D.The national halothane study. Bethesda, MD: National Institute of General Medical Sciences, 1969.Google Scholar
3Cromwell, J., Mitchell, J. B., & Stason, W. B.Learning by doing in CABG surgery. Medical Care, 1990, 28, 6–18.CrossRefGoogle ScholarPubMed
4Donabedian, A.Evaluating the quality of medical care. Milbank Memorial Fund Quarterly, 1966, 44, 166–203.CrossRefGoogle ScholarPubMed
5Donabedian, A.The definition of quality and approaches to its assessment. Vol 1: Explorations in quality assessment and monitoring. Ann Arbor, MI: Health Administration Press, 1980.Google Scholar
6Dyck, F. J., Murphy, F. A., Murphy, J. K. et al. , The effect of surveillance on the number of hysterectomies in the Province of Saskatchewan. New England Journal of Medicine, 1977, 296, 1326–28.CrossRefGoogle ScholarPubMed
7Flood, A. B., Ewy, W., Scott, W. R. et al. , The relationship between intensity and duration of medical services and outcomes for hospitalized patients. Medical Care, 1979, 17, 1088–1102.CrossRefGoogle ScholarPubMed
8Flood, A. B., Johnson, P. A., Davis, C. A. et al. , Abstracts of the breast cancer symposium annual meetings. San Antonio, TX: Breast Cancer Symposium, 1987.Google Scholar
9Flood, A. B., & Scott, W. R.Hospital structure and performance. Baltimore, MD: John Hopkins University Press, 1987.Google Scholar
10Flood, A. B., & Scott, W. R.Professional power and professional effectiveness: The power of the surgical staff and the quality of surgical care in hospitals. Journal of Health and Social Behavior, 1978, 19, 240–54.CrossRefGoogle ScholarPubMed
11Flood, A. B., Scott, W. R., & Ewy, W.Does practice make perfect? Part I: The relation between hospital volume and outcomes for selected diagnostic categories. Medical Care, 1984a, 22, 98–114.CrossRefGoogle ScholarPubMed
12Flood, A. B., Scott, W. R., & Ewy, W.Does practice make perfect? Part II: The relation between volume and outcomes and other hospital characteristics. Medical Care, 1984b, 22, 115–25.CrossRefGoogle ScholarPubMed
13Garber, A. M., Fuchs, V. R., & Silverman, J. F.Case mix, costs, and outcomes: Differences between faculty and community services in a university hospital. New England Journal of Medicine, 1984, 310, 1231–37.CrossRefGoogle ScholarPubMed
14Gradison, W. Jr, A view from the House of Representatives. Presentation to Conference: Measuring health care effectiveness: The use of large data sets for technology assessment and quality assessment.Washington, DC,September 7–8, 1989.Google Scholar
15Joint Commission on Accreditation of Healthcare Organizations (JCAHO). The joint commission's agenda for change. Chicago: JCAHO, 1986.Google Scholar
16Kahn, K. L., Kosecoff, J., Chassin, M. R. et al. , Measuring the clinical appropriateness of the use of a procedure: Can we do it? Medical Care, 1988, 26, 415–22.CrossRefGoogle ScholarPubMed
17Kind, E. A., Fowles, J., & McCoy, C. E. Effectiveness of the primary practice profile in changing physician practice styles. Presentation at American Medical Review Research Center Annual Meetings,Washington, DC,September 10, 1987.Google Scholar
18Krakauer, H. Current uses of large data sets to assess technologies. Presentation to Conference: Measuring health care effectiveness: The use of large data sets for technology assessment and quality assessment.Washington, DC,September 7–8, 1989.Google Scholar
19Lewis, C., Linet, M. S., & Abeloff, M. D.Compliance with cancer therapy by patients and physicians. American Journal of Medicine, 1983, 74, 673–78.CrossRefGoogle ScholarPubMed
20Moses, L. E. A framework for technology assessment and quality assessment. Presentation to Conference: Measuring health care effectiveness: The use of large data sets for technology assessment and quality assessment.Washington, DC,September 7–8, 1989.Google Scholar
21Moses, L. E., & Mosteller, E.Institutional differences in postoperative death rates: Commentary on some of the findings of the National Halothane Study. Journal of the American Medical Association, 1968, 203, 492–94.CrossRefGoogle ScholarPubMed
22McNeil, B. Strengths and weaknesses of large data sets for technology assessment. Presentation to Conference: Measuring health care effectiveness: The use of large data sets for technology assessment and quality assessment.Washington, DC,September 7–8, 1989.Google Scholar
23Roos, N. P.Hysterectomy: Variations in rates across small areas and across physicians' practices. American Journal of Public Health. 1984, 74, 327–35.CrossRefGoogle ScholarPubMed
24Ross, 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 Scholar
25Sackett, D. L., & Snow, J. C. The magnitude of compliance and noncompliance. In Haynes, R. B., Taylor, D. W., & Sackett, D. L. (eds.), Compliance in health care. Baltimore, MD: Johns Hopkins University Press, 1979, 11–22.Google Scholar
26Sharp, K. Organizational determinants of quality surgical care. Ph.D. thesis, Urbana- Champaign: University of Illinois, 1986.Google Scholar
27Wennberg, J. E., Blowers, L., Parker, P., & Gittelsohn, A. M.Changes in tonsillectomy rates associated with feedback and review. Pediatrics, 1977, 59, 821–26.CrossRefGoogle ScholarPubMed
28Wennberg, J., & Gittelsohn, A.Variation in medical care among small areas. Scientific American, 1982, 246, 811–824.CrossRefGoogle ScholarPubMed
29Wennberg, 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 A merican Medical Association, 1987, 257, 933–36.CrossRefGoogle ScholarPubMed
30Wilson, P. A., Griffith, J. R., & Tedeschi, P. J.Does race affect hospital use? American Journal of Public Health, 1985, 75, 263–69.CrossRefGoogle ScholarPubMed
31Winslow, C. M., Kosecoff, J. B., Chassin, M. et al. , The appropriateness of performing coronary artery bypass surgery. Journal of the American MedicalAssociation. 1988, 260, 505–09.CrossRefGoogle ScholarPubMed
32Yergan, J., Flood, A. B., loGerfo, J. P., & Diehr, P.Relationship between patient race and the intensity of hospital services. Medical Care, 1987, 25, 592–603.CrossRefGoogle ScholarPubMed
33Yusuf, S. Strengths and weaknesses of large data sets for technology assessment. Presentation to Conference: Measuring health care effectiveness: The use of large data sets for technology assessment and quality assessment.Washington, DC,September 7–8, 1989.Google Scholar