Improving Efficiency and Value in Palliative Care with Net Benefit Regression: An Introduction to a Simple Method for Cost-Effectiveness Analysis with Person-Level Data

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

The objective of this article is to illustrate how to do cost-effectiveness analysis (CEA) using net-benefit regression and to explain how this method provides all of the benefits CEA can provide for improving efficiency and value in palliative care. We use a hypothetical data set with person-level data to demonstrate the net-benefit regression framework. Cost and effect data are combined with assumptions about willingness to pay to produce a net-benefit variable for each study participant. This net-benefit variable is the dependent variable in a net-benefit regression. In the simplest formulation, the regression coefficient on the treatment indicator variable estimates the difference in value between extra benefits and extra costs. The estimate and its confidence interval provide policy-relevant information. Net-benefit regression can be used with data from clinical trials or from administrative data sets. The results can be used to help develop policy, with an aim toward improving efficiency and value in health care.

Original languageEnglish (US)
Pages (from-to)54-61
Number of pages8
JournalJournal of Pain and Symptom Management
Volume38
Issue number1
DOIs
StatePublished - Jul 2009
Externally publishedYes

Fingerprint

Palliative Care
Cost-Benefit Analysis
Clinical Trials
Confidence Intervals
Delivery of Health Care
Costs and Cost Analysis
Datasets
Therapeutics

Keywords

  • Cost-effectiveness analysis
  • incremental cost-effectiveness ratio
  • incremental net benefit
  • net-benefit regression

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine
  • Clinical Neurology
  • Nursing(all)

Cite this

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