Using the net benefit regression framework to construct cost-effectiveness acceptability curves

An example using data from a trial of external loop recorders versus Holter monitoring for ambulatory monitoring of "community acquired" syncope

Jeffrey S Hoch, Marie Antoinette Rockx, Andrew D. Krahn

Research output: Contribution to journalArticle

85 Citations (Scopus)

Abstract

Background: Cost-effectiveness acceptability curves (CEACs) describe the probability that a new treatment or intervention is cost-effective. The net benefit regression framework (NBRF) allows cost-effectiveness analysis to be done in a simple regression framework. The objective of the paper is to illustrate how net benefit regression can be used to construct a CEAC. Methods: One hundred patients referred for ambulatory monitoring with syncope or presyncope were randomized to a one-month external loop recorder (n = 49) or 48-hour Holter monitor (n = 51). The primary endpoint was symptom-rhythm correlation during monitoring. Direct costs were calculated based on the 2003 Ontario Health Insurance Plan (OHIP) fee schedule combined with hospital case costing of labour, materials, service and overhead costs for diagnostic testing and related equipment. Results: In the loop recorder group, 63.27% of patients (31/49) had symptom recurrence and successful activation, compared to 23.53% in the Holter group (12/51). The cost in US dollars for loop recording was $648.50 and $212.92 for Holter monitoring. The incremental cost-effectiveness ratio (ICER) of the loop recorder was $1,096 per extra successful diagnosis. The probability that the loop recorder was cost-effective compared to the Holter monitor was estimated using net benefit regression and plotted on a CEAC. In a sensitivity analysis, bootstrapping was used to examine the effect of distributional assumptions. Conclusion: The NBRF is straightforward to use and interpret. The resulting uncertainty surrounding the regression coefficient relates to the CEAC. When the link from the regression's p-value to the probability of cost-effectiveness is tentative, bootstrapping may be used.

Original languageEnglish (US)
Article number68
JournalBMC Health Services Research
Volume6
DOIs
StatePublished - Jun 6 2006
Externally publishedYes

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Ambulatory Monitoring
Ambulatory Electrocardiography
Syncope
Cost-Benefit Analysis
Costs and Cost Analysis
Fee Schedules
Ontario
Health Insurance
Uncertainty
Recurrence
Equipment and Supplies

ASJC Scopus subject areas

  • Health Policy

Cite this

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title = "Using the net benefit regression framework to construct cost-effectiveness acceptability curves: An example using data from a trial of external loop recorders versus Holter monitoring for ambulatory monitoring of {"}community acquired{"} syncope",
abstract = "Background: Cost-effectiveness acceptability curves (CEACs) describe the probability that a new treatment or intervention is cost-effective. The net benefit regression framework (NBRF) allows cost-effectiveness analysis to be done in a simple regression framework. The objective of the paper is to illustrate how net benefit regression can be used to construct a CEAC. Methods: One hundred patients referred for ambulatory monitoring with syncope or presyncope were randomized to a one-month external loop recorder (n = 49) or 48-hour Holter monitor (n = 51). The primary endpoint was symptom-rhythm correlation during monitoring. Direct costs were calculated based on the 2003 Ontario Health Insurance Plan (OHIP) fee schedule combined with hospital case costing of labour, materials, service and overhead costs for diagnostic testing and related equipment. Results: In the loop recorder group, 63.27{\%} of patients (31/49) had symptom recurrence and successful activation, compared to 23.53{\%} in the Holter group (12/51). The cost in US dollars for loop recording was $648.50 and $212.92 for Holter monitoring. The incremental cost-effectiveness ratio (ICER) of the loop recorder was $1,096 per extra successful diagnosis. The probability that the loop recorder was cost-effective compared to the Holter monitor was estimated using net benefit regression and plotted on a CEAC. In a sensitivity analysis, bootstrapping was used to examine the effect of distributional assumptions. Conclusion: The NBRF is straightforward to use and interpret. The resulting uncertainty surrounding the regression coefficient relates to the CEAC. When the link from the regression's p-value to the probability of cost-effectiveness is tentative, bootstrapping may be used.",
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