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Using clinical databases to evaluate healthcare interventions

Published online by Cambridge University Press:  08 January 2010

Sheila Harvey ,
Kathy Rowan ,
David Harrison  and
Nick Black
Sheila Harvey
Affiliation:
London School of Hygiene & Tropical Medicine
Kathy Rowan
Affiliation:
Intensive Care National Audit & Research Centre
David Harrison
Affiliation:
Intensive Care National Audit & Research Centre
Nick Black
Affiliation:
London School of Hygiene & Tropical Medicine
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Abstract

Objectives: The aim of this study was to test the feasibility of conducting rigorous, nonrandomized studies (NRSs) of healthcare interventions using existing clinical databases in terms of the following: recruiting a large representative sample of hospitals, identifying eligible cases, matching cases to controls to achieve similar baseline characteristics, making meaningful comparisons of outcomes, and carrying out subgroup analyses.

Methods: Data were extracted from the Intensive Care National Audit & Research Centre's Case Mix Programme Database to investigate the impact of management with a pulmonary artery catheter (PAC) in intensive care unit (ICU) patients. Participating ICUs were invited to collect additional data for the analysis. Patients managed with a PAC were matched to control patients on their propensity score. Hospital mortality was then compared between the two groups.

Results: Of 117 eligible ICUs, 68 (58 percent) agreed to participate, of which 57 (84 percent) collected additional data. Although a slightly higher proportion of larger ICUs in university hospitals participated, the patient case-mix was similar to that in nonparticipating ICUs. Almost all patients managed with a PAC (98 percent) were successfully matched to patients managed without a PAC. The two groups were similar for baseline characteristics. However, hospital mortality was worse for PAC patients than for non-PAC patients (odds ratio, 1.28; 95 percent confidence interval, 1.06–1.55). Subgroup analysis suggested that the impact of management with a PAC was modified by severity of illness.

Conclusions: Rigorous NRSs are feasible if they are based on data from high-quality clinical databases. However, the reliability of estimated treatment effects from such studies requires further investigation.

Keywords

Nonrandomized studiesCase-mix adjustmentPropensity scoresPulmonary artery catheterClinical databases
Type
METHODS
Information
International Journal of Technology Assessment in Health Care , Volume 26 , Issue 1 , January 2010 , pp. 86 - 94
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

1. Afessa, B, Spencer, S, Khan, W, et al. Association of pulmonary artery catheter use with in-hospital mortality. Crit Care Med. 2001;29:1145–1148.CrossRefGoogle ScholarPubMed
2. Altman, DG, Schulz, KF, Moher, D, et al. The revised CONSORT statement for reporting randomized trials: Explanation and elaboration. Ann Intern Med. 2001;134:663–694.Google Scholar
3. Barton, S. Which clinical studies provide the best evidence? The best RCT still trumps the best observational study. BMJ. 2000;321:255–256.CrossRefGoogle ScholarPubMed
4. Black, N. Why we need observational studies to evaluate the effectiveness of health care. BMJ. 1996;312:1215–1218.CrossRefGoogle ScholarPubMed
5. Byar, DP. Why data bases should not replace randomized clinical trials. Biometrics. 1980;36:337–342.Google Scholar
6. Canto, JG, Kiefe, CI, Williams, OD, Barron, HV, Rogers, WJ. Comparison of outcomes research with clinical trials using preexisting data. Am J Cardiol. 1999;84:923–927, A6.Google ScholarPubMed
7. Chittock, DR, Dhingra, VK, Ronco, JJ, et al. Severity of illness and risk of death associated with pulmonary artery catheter use. Crit Care Med. 2004;32:911–915.Google Scholar
8. Connors, AF Jr, Speroff, T, Dawson, NV, et al. The effectiveness of right heart catheterization in the initial care of critically ill patients. SUPPORT Investigators. JAMA. 1996;276:889–897.CrossRefGoogle ScholarPubMed
9. Cook, D, Heyland, D, Marshall, J. On the need for observational studies to design and interpret randomized trials in ICU patients: A case study in stress ulcer prophylaxis. Intensive Care Med. 2001;27:347–354.CrossRefGoogle ScholarPubMed
10. DocDat.Org. http://www.docdat.org (accessed October 4, 2007).Google Scholar
11. Feinstein, AR, Horwitz, RI. Problems in the “evidence” of “evidence-based medicine”. Am J Med. 1997;103:529–535.CrossRefGoogle Scholar
12. Guyatt, G. A randomized control trial of right-heart catheterization in critically ill patients. Ontario Intensive Care Study Group. J Intensive Care Med. 1991;6:91–95.CrossRefGoogle ScholarPubMed
13. Harrison, DA, Brady, AR, Rowan, K. Case mix, outcome and length of stay for admissions to adult, general critical care units in England, Wales and Northern Ireland: The Intensive Care National Audit & Research Centre Case Mix Programme Database. Crit Care. 2004;8:R99–R111.Google Scholar
14. Harrison, DA, Parry, GJ, Carpenter, JR, Short, A, Rowan, K. A new risk prediction model for critical care: The Intensive Care National Audit & Research Centre (ICNARC) model. Crit Care Med. 2007;35:1091–1098.CrossRefGoogle Scholar
15. Harvey, S, Harrison, DA, Singer, M, et al. for the PAC-Man study collaboration. Assessment of the clinical effectiveness of pulmonary artery catheters in management of patients in intensive care (PAC-Man): A randomised controlled trial. Lancet. 2005;366:472–477.Google Scholar
16. Hlatky, MA, Califf, RM, Harrell, FE Jr, et al. Comparison of predictions based on observational data with the results of randomized controlled clinical trials of coronary artery bypass surgery. J Am Coll Cardiol. 1988;11:237–245.Google Scholar
17. Horwitz, RI, Viscoli, CM, Clemens, JD, Sadock, RT. Developing improved observational methods for evaluating therapeutic effectiveness. Am J Med. 1990;89:630–638.CrossRefGoogle ScholarPubMed
18. Murdoch, SD, Cohen, AT, Bellamy, MC. Pulmonary artery catheterization and mortality in critically ill patients. Br J Anaesth. 2000;85:611–615.Google Scholar
19. Padkin, A, Rowan, K, Black, N. Using high quality clinical databases to complement the results of randomised controlled trials: The case of recombinant human activated protein C. BMJ. 2001;323:923–926.CrossRefGoogle ScholarPubMed
20. Peters, SG, Afessa, B, Decker, PA, et al. Increased risk associated with pulmonary artery catheterization in the medical intensive care unit. J Crit Care. 2003;18:166–171.Google Scholar
21. Pocock, SJ, Elbourne, DR. Randomized trials or observational tribulations? N Engl J Med. 2000;342:1907–1909.CrossRefGoogle ScholarPubMed
22. Rhodes, A, Cusack, RJ, Newman, PJ, Grounds, RM, Bennett, ED. A randomised, controlled trial of the pulmonary artery catheter in critically ill patients. Intensive Care Med. 2002;28:256–264.Google Scholar
23. Rosenbaum, PR, Rubin, DB. The central role of the propensity score in observational studies for causal effects. Bioimetrika. 1983;70:41–55.CrossRefGoogle Scholar
24. Sakr, Y, Vincent, JL, Reinhart, K, et al. Use of the pulmonary artery catheter is not associated with worse outcome in the ICU. Chest. 2005;128:2722–2731.Google Scholar
25. Wunsch, H, Brady, AR, Rowan, K. Impact of exclusion criteria on case mix, outcome, and length of stay for the severity of disease scoring methods in common use in critical care. J Crit Care. 2004;19:67–74.Google Scholar
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