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Value of Information of a clinical prediction rule: Informing the efficient use of healthcare and health research resources

Published online by Cambridge University Press:  24 January 2008

Sonia Singh ,
Bohdan Nosyk ,
Huiying Sun ,
James Malcolm Christenson ,
Grant Innes  and
Aslam Hayat Anis
Sonia Singh
Affiliation:
University of British Columbia and Peace Arch Hospital
Bohdan Nosyk
Affiliation:
St. Paul's Hospital
Huiying Sun
Affiliation:
St. Paul's Hospital
James Malcolm Christenson
Affiliation:
University of British Columbia and St. Paul's Hospital
Grant Innes
Affiliation:
University of British Columbia and St. Paul's Hospital
Aslam Hayat Anis
Affiliation:
University of British Columbia and St. Paul's Hospital
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Abstract

Objectives: The aim of this study was to estimate the potential cost-effectiveness and expected value of perfect information of a recently derived clinical prediction rule for patients presenting to emergency departments with chest discomfort.

Methods: A decision analytic model was constructed to compare the Early Disposition Prediction Rule (EDPR) with the current standard of care. Results were used to calculate the potential cost-effectiveness of the EDPR, as well as the Value of Information in conducting further research. Study subjects were adults presenting with chest discomfort to two urban emergency departments in Vancouver, British Columbia, Canada. The clinical prediction rule identifies patients who are eligible for early discharge within 3 hours of presentation to the emergency department. The outcome measure used was inappropriate emergency department discharge of patients with acute coronary syndrome (ACS).

Results: The incremental cost-effectiveness ratio of the EDPR in comparison to usual care was (negative) $2,999 per inappropriate ACS discharge prevented, indicating a potential cost-savings in introducing the intervention. The expected value of perfect information was $16.3 million in the first year of implementation, suggesting a high benefit from conducting further research to validate the decision rule.

Conclusions: The EDPR is likely to be cost-effective; however, given the high degree of uncertainty in the estimates of costs and patient outcomes, further research is required to inform the decision to implement the intervention. The potential health and monetary benefits of this clinical prediction rule outweigh the costs of doing further research.

Keywords

Expected value of perfect informationValue of InformationAcute coronary syndromeChest discomfortCost-effectiveness analysis
Type
RESEARCH REPORTS
Information
International Journal of Technology Assessment in Health Care , Volume 24 , Issue 1 , January 2008 , pp. 112 - 119
Copyright
Copyright © Cambridge University Press 2008

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