Literature DB >> 8528428

The use of condition specific outcome measures in economic appraisal.

J Brazier1, S Dixon.   

Abstract

Despite growing concern over the use of health utility measures in economic evaluations of health care programmes, economists have been reluctant to use the wealth of knowledge contained within studies using condition specific outcome measures (CSOMs). Problems with the measurement properties of many CSOMs means that the scope for their use in economic appraisal is extremely limited. This paper examines the potential uses of CSOMs in economics, namely: to provide valid descriptive material, to provide scales for comparing the effectiveness of interventions and to 'validate' the descriptive accuracy of economic measures of benefit. It is argued that valid descriptive information is essential for economic appraisal, no matter which method of evaluation is used. Generic measures have been criticised for being too narrow and insensitive to the consequences of specific conditions. CSOMs offer a rich source of information to produce quality adjusted life years (QALYs) but two potential methods, one of mapping health states from one scale to a QALY classification (such as Rosser), and the other, developing 'exchange rates' between scales are unsatisfactory. A more rigorous approach would necessitate a major research programme of revaluing existing CSOMs using preference based methods. Another interesting avenue of research would be to use the information from CSOMs to construct health scenarios for valuation. Given the current state of development of outcome measures, it seems advisable to use CSOMs alongside economic measures in trials. Such a strategy would help demonstrate the usefulness of economic measures to clinicians and to reconcile the two measures.

Mesh:

Year:  1995        PMID: 8528428     DOI: 10.1002/hec.4730040402

Source DB:  PubMed          Journal:  Health Econ        ISSN: 1057-9230            Impact factor:   3.046


  19 in total

1.  Measuring outcomes in economic evaluations. This economics note is misleading.

Authors:  S Dixon; C Green
Journal:  BMJ       Date:  1999-09-11

2.  Health-related quality of life research and the capability approach of Amartya Sen.

Authors:  M A Verkerk; J J Busschbach; E D Karssing
Journal:  Qual Life Res       Date:  2001       Impact factor: 4.147

3.  Using the effect size to model change in preference values from descriptive health status.

Authors:  Kristy Sanderson; Gavin Andrews; Justine Corry; Helen Lapsley
Journal:  Qual Life Res       Date:  2004-09       Impact factor: 4.147

4.  Deriving a preference-based measure for cancer using the EORTC QLQ-C30.

Authors:  Donna Rowen; John Brazier; Tracey Young; Sabine Gaugris; Benjamin M Craig; Madeleine T King; Galina Velikova
Journal:  Value Health       Date:  2011 Jul-Aug       Impact factor: 5.725

5.  Validity and feasibility of the use of condition-specific outcome measures in economic evaluation.

Authors:  Elly A Stolk; Jan J V Busschbach
Journal:  Qual Life Res       Date:  2003-06       Impact factor: 4.147

6.  Measuring health outcomes.

Authors:  J Cairns
Journal:  BMJ       Date:  1996-07-06

7.  Constructing health state preference values from descriptive quality of life outcomes: mission impossible?

Authors:  J V Chancellor; D Coyle; M F Drummond
Journal:  Qual Life Res       Date:  1997-03       Impact factor: 4.147

8.  Utility estimation in chronic obstructive pulmonary disease: a preference for change?

Authors:  Jennifer Petrillo; Floortje van Nooten; Paul Jones; Maureen Rutten-van Mölken
Journal:  Pharmacoeconomics       Date:  2011-11       Impact factor: 4.981

9.  Quality-of-life evaluation in chronic wounds: comparative analysis of three disease-specific questionnaires.

Authors:  Matthias Augustin; Katrin Baade; Kristina Heyer; Patricia E Price; Katharina Herberger; Thomas Wild; Michael Engelhardt; Eike S Debus
Journal:  Int Wound J       Date:  2017-09-06       Impact factor: 3.315

10.  Quality-of-life assessment in osteoporosis: health-status and preference-based measures.

Authors:  Anna N A Tosteson; Cristina S Hammond
Journal:  Pharmacoeconomics       Date:  2002       Impact factor: 4.981

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