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 dollars and 212.92 dollars for Holter monitoring. The incremental cost-effectiveness ratio (ICER) of the loop recorder was 1,096 dollars 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.
journal_name
BMC Health Serv Resjournal_title
BMC health services researchauthors
Hoch JS,Rockx MA,Krahn ADdoi
10.1186/1472-6963-6-68subject
Has Abstractpub_date
2006-06-06 00:00:00pages
68issn
1472-6963pii
1472-6963-6-68journal_volume
6pub_type
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