Literature DB >> 17249853

Measuring preferences for cost-utility analysis: how choice of method may influence decision-making.

Christine M McDonough1, Anna N A Tosteson.   

Abstract

Preferences for health are required when the economic value of healthcare interventions are assessed within the framework of cost-utility analysis. The objective of this paper was to review alternative methods for preference measurement and to evaluate the extent to which the method may affect healthcare decision-making. Two broad approaches to preference measurement that provide societal health state values were considered: (i) direct measurement; and (ii) preference-based health state classification systems. Among studies that compared alternative preference-based systems, the EQ-5D tended to provide larger change scores and more favourable cost-effectiveness ratios than the Health Utilities Index (HUI)-2 and -3, while the SF-6D provided smaller change scores and less favourable ratios than the other systems. However, these patterns may not hold for all applications. Empirical evidence comparing systems and decision-making impact suggests that preferences will have the greatest impact on economic analyses when chronic conditions or long-term sequelae are involved. At present, there is no clearly superior method, and further study of cost-effectiveness ratios from alternative systems is needed to evaluate system performance. Although there is some evidence that incremental cost-effectiveness ratio (ICER) thresholds (e.g. $US50,000 per QALY gained) are used in decision-making, they are not strictly applied. Nonetheless, as ICERs rise, the probability of acceptance of a new therapy is likely to decrease, making the differences in QALYs obtained using alternative methods potentially meaningful. It is imperative that those conducting cost-utility analyses characterise the impact that uncertainty in health state values has on the economic value of the interventions studied. Consistent reporting of such analyses would provide further insight into the policy implications of preference measurement.

Mesh:

Year:  2007        PMID: 17249853      PMCID: PMC3046553          DOI: 10.2165/00019053-200725020-00003

Source DB:  PubMed          Journal:  Pharmacoeconomics        ISSN: 1170-7690            Impact factor:   4.981


  133 in total

1.  The practicality and validity of directly elicited and SF-36 derived health state preferences in patients with low back pain.

Authors:  William Hollingworth; Richard A Deyo; Sean D Sullivan; Scott S Emerson; Darryl T Gray; Jeffrey G Jarvik
Journal:  Health Econ       Date:  2002-01       Impact factor: 3.046

2.  A comparison of the Assessment of Quality of Life (AQoL) with four other generic utility instruments.

Authors:  G Hawthorne; J Richardson; N A Day
Journal:  Ann Med       Date:  2001-07       Impact factor: 4.709

3.  How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?

Authors:  Bruce R Schackman; Heather Taffet Gold; Patricia W Stone; Peter J Neumann
Journal:  Pharmacoeconomics       Date:  2004       Impact factor: 4.981

4.  Predicting EuroQoL EQ-5D preference scores from the SF-12 Health Survey in a nationally representative sample.

Authors:  William F Lawrence; John A Fleishman
Journal:  Med Decis Making       Date:  2004 Mar-Apr       Impact factor: 2.583

Review 5.  Common methodological flaws in economic evaluations.

Authors:  Michael Drummond; Mark Sculpher
Journal:  Med Care       Date:  2005-07       Impact factor: 2.983

6.  Estimation of utilities for the effects of depression from the SF-12.

Authors:  L A Lenert; C D Sherbourne; C Sugar; K B Wells
Journal:  Med Care       Date:  2000-07       Impact factor: 2.983

7.  Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets.

Authors:  Aki Tsuchiya; John Brazier; Jennifer Roberts
Journal:  J Health Econ       Date:  2005-11-04       Impact factor: 3.883

8.  Modeling valuations for EuroQol health states.

Authors:  P Dolan
Journal:  Med Care       Date:  1997-11       Impact factor: 2.983

9.  A comparison of scoring weights for the EuroQol derived from patients and the general public.

Authors:  D Polsky; R J Willke; K Scott; K A Schulman; H A Glick
Journal:  Health Econ       Date:  2001-01       Impact factor: 3.046

10.  A comparison of techniques for eliciting patient preferences in patients with benign prostatic hyperplasia.

Authors:  Mark W Schulz; Jack Chen; Henry H Woo; Martin Keech; Maria E Watson; Peter J Davey
Journal:  J Urol       Date:  2002-07       Impact factor: 7.450

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  38 in total

1.  Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes.

Authors:  Mangala Rajan; Kuan-Chi Lai; Chin-Lin Tseng; Shirley Qian; Alfredo Selim; Lewis Kazis; Leonard Pogach; Anushua Sinha
Journal:  Qual Life Res       Date:  2012-03-06       Impact factor: 4.147

2.  Current Status and Future Prospects of Clinical Psychology: Toward a Scientifically Principled Approach to Mental and Behavioral Health Care.

Authors:  Timothy B Baker; Richard M McFall; Varda Shoham
Journal:  Psychol Sci Public Interest       Date:  2008-11-01

3.  Lessons from trial-based cost-effectiveness analyses of mental health interventions: why uncertainty about the outcome, estimate and willingness to pay matters.

Authors:  Jeffrey S Hoch; Carolyn S Dewa
Journal:  Pharmacoeconomics       Date:  2007       Impact factor: 4.981

4.  Evaluating a falls prevention intervention in older home care recipients: a comparison of SF-6D and EQ-5D.

Authors:  Maria Bjerk; Therese Brovold; Jennifer C Davis; Astrid Bergland
Journal:  Qual Life Res       Date:  2019-07-30       Impact factor: 4.147

5.  The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common?

Authors:  Uwe Konerding; Jörn Moock; Thomas Kohlmann
Journal:  Qual Life Res       Date:  2009-09-01       Impact factor: 4.147

Review 6.  Estimates of utility weights in hemophilia: implications for cost-utility analysis of clotting factor prophylaxis.

Authors:  Scott D Grosse; Shraddha S Chaugule; Joel W Hay
Journal:  Expert Rev Pharmacoecon Outcomes Res       Date:  2015-01-14       Impact factor: 2.217

7.  Predicting EQ-5D-US and SF-6D societal health state values from the Osteoporosis Assessment Questionnaire.

Authors:  C M McDonough; M R Grove; A D Elledge; A N A Tosteson
Journal:  Osteoporos Int       Date:  2011-04-12       Impact factor: 4.507

8.  Valuing benefits to inform a clinical trial in pharmacy : do differences in utility measures at baseline affect the effectiveness of the intervention?

Authors:  Michela Tinelli; Mandy Ryan; Christine Bond; Anthony Scott
Journal:  Pharmacoeconomics       Date:  2013-02       Impact factor: 4.981

9.  Interchangeability of the EQ-5D and the SF-6D, and comparison of their psychometric properties in a spinal postoperative Spanish population.

Authors:  Carmen Selva-Sevilla; Paula Ferrara; Manuel Gerónimo-Pardo
Journal:  Eur J Health Econ       Date:  2020-02-17

Review 10.  Using qualitative methods to inform the trade-off between content validity and consistency in utility assessment: the example of type 2 diabetes and Alzheimer's disease.

Authors:  Clare McGrath; Diana Rofail; Elizabeth Gargon; Linda Abetz
Journal:  Health Qual Life Outcomes       Date:  2010-02-12       Impact factor: 3.186

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