Literature DB >> 2493538

Time preference for health in cost-effectiveness analysis.

J Lipscomb1.   

Abstract

In program evaluation, should a predicted health status gain of 1 quality-adjusted life year (QALY) occurring 10 years from now be valued the same as a 1-QALY increase realizable 5 years from now? Or 1 year from now? If not, how should these future gains (or losses) be evaluated from a present-time perspective? Such questions arise frequently in cost-effectiveness analyses of disease prevention-health promotion programs. This report argues there are actually two distinct interpretations of time preference jointly relevant in many multiperiod program evaluations. 1) In ongoing programs where both present and future population cohorts are, in effect, vying for resources, decision makers must establish a relative social weighting of cohorts by specifying (now) the dollar worth of any unit QALY gain achievable in each. This is a problem of intergenerational equity in the resource allocation process. 2) Individuals, in any cohort, may possess a time preference for the sequence of events comprising their own multiperiod health outcomes. Current models, typically discounting future health gains to present value at some constant rate (r), can well accommodate the first interpretation but not (simultaneously) the second. In response, this report introduces a two-step evaluation procedure featuring the "scenario strategy," a holistic multiattribute preference approach to evaluating multiperiod health outcomes. It allows one to isolate statistically time preference effects at the individual or group level and to incorporate them naturally into the overall evaluation of multiperiod outcomes. A survey-based example and an appendix illustrate the main points.

Mesh:

Year:  1989        PMID: 2493538     DOI: 10.1097/00005650-198903001-00019

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  16 in total

Review 1.  Handling uncertainty in cost-effectiveness models.

Authors:  A H Briggs
Journal:  Pharmacoeconomics       Date:  2000-05       Impact factor: 4.981

2.  Measurement of short term health effects in economic evaluations.

Authors:  A M Holmes
Journal:  Pharmacoeconomics       Date:  1998-02       Impact factor: 4.981

3.  Discounting in cost-effectiveness analysis of healthcare programmes.

Authors:  D A Katz; H G Welch
Journal:  Pharmacoeconomics       Date:  1993-04       Impact factor: 4.981

4.  Time preference for health gains versus health losses.

Authors:  L D MacKeigan; L N Larson; J R Draugalis; J L Bootman; L R Burns
Journal:  Pharmacoeconomics       Date:  1993-05       Impact factor: 4.981

5.  The validity and reproducibility of a work productivity and activity impairment instrument.

Authors:  M C Reilly; A S Zbrozek; E M Dukes
Journal:  Pharmacoeconomics       Date:  1993-11       Impact factor: 4.981

6.  Canadian guidelines for economic evaluation of pharmaceuticals. Canadian Collaborative Workshop for Pharmacoeconomics.

Authors:  G W Torrance; D Blaker; A Detsky; W Kennedy; F Schubert; D Menon; P Tugwell; R Konchak; E Hubbard; T Firestone
Journal:  Pharmacoeconomics       Date:  1996-06       Impact factor: 4.981

7.  On sale: future health care. The paradox of discounting.

Authors:  T G Ganiats
Journal:  West J Med       Date:  1992-05

8.  Holistic preferences for 1-year health profiles describing fluctuations in health: the case of chronic obstructive pulmonary disease.

Authors:  Maureen P M H Rutten-van Mölken; Martine Hoogendoorn; Leida M Lamers
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

Review 9.  Sensitivity analysis in cost-effectiveness studies: from guidelines to practice.

Authors:  Rahul Jain; Michael Grabner; Eberechukwu Onukwugha
Journal:  Pharmacoeconomics       Date:  2011-04       Impact factor: 4.981

10.  A cost-benefit analysis of a cardiovascular disease prevention trial, using folate supplementation as an example.

Authors:  J Hornberger
Journal:  Am J Public Health       Date:  1998-01       Impact factor: 9.308

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