Measuring the cost-effectiveness of treatments for people with multiple sclerosis: Beyond quality-adjusted life-years.

Multiple sclerosis cost-effectiveness cost-effectiveness analysis health-related quality of life quality of life quality-adjusted life-years

Journal

Multiple sclerosis (Houndmills, Basingstoke, England)
ISSN: 1477-0970
Titre abrégé: Mult Scler
Pays: England
ID NLM: 9509185

Informations de publication

Date de publication:
Mar 2022
Historique:
pubmed: 4 9 2020
medline: 17 3 2022
entrez: 4 9 2020
Statut: ppublish

Résumé

It is a familiar story. A promising multiple sclerosis (MS) treatment clears the three regulatory hurdles of safety, quality and efficacy, only to fall at the fourth: cost-effectiveness. This has led to concerns about the validity of the measures typically used to quantify treatment effects in cost-effectiveness analyses and in 2012, in the United Kingdom, the National Institute for Health and Care Excellence called for an improvement in the cost-effectiveness framework for assessing MS treatments. This review describes what is meant by cost-effectiveness in health/social care funding decision-making, and usual practice for assessing treatment benefits. We detail the use of the quality-adjusted life-year (QALY) in resource allocation decisions, and set out limitations of this approach in the context of MS. We conclude by highlighting methodological and policy developments which should aid addressing these limitations.

Sections du résumé

BACKGROUND BACKGROUND
It is a familiar story. A promising multiple sclerosis (MS) treatment clears the three regulatory hurdles of safety, quality and efficacy, only to fall at the fourth: cost-effectiveness. This has led to concerns about the validity of the measures typically used to quantify treatment effects in cost-effectiveness analyses and in 2012, in the United Kingdom, the National Institute for Health and Care Excellence called for an improvement in the cost-effectiveness framework for assessing MS treatments.
OBJECTIVE AND METHODS OBJECTIVE
This review describes what is meant by cost-effectiveness in health/social care funding decision-making, and usual practice for assessing treatment benefits.
RESULTS RESULTS
We detail the use of the quality-adjusted life-year (QALY) in resource allocation decisions, and set out limitations of this approach in the context of MS.
CONCLUSION CONCLUSIONS
We conclude by highlighting methodological and policy developments which should aid addressing these limitations.

Identifiants

pubmed: 32880511
doi: 10.1177/1352458520954172
pmc: PMC8894952
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

346-351

Subventions

Organisme : Department of Health
Pays : United Kingdom

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Auteurs

Annie Hawton (A)

Health Economics Group, University of Exeter Medical School, University of Exeter, Exeter, UK/NIHR Applied Research Collaboration (ARC) South West Peninsula, University of Exeter Medical School, University of Exeter, Exeter, UK.

Elizabeth Goodwin (E)

Health Economics Group, University of Exeter Medical School, University of Exeter, Exeter, UK.

Kate Boddy (K)

NIHR Applied Research Collaboration (ARC) South West Peninsula, University of Exeter Medical School, University of Exeter, Exeter, UK.

Jennifer Freeman (J)

School of Health Professions, Faculty of Health, University of Plymouth, Plymouth, UK.

Sarah Thomas (S)

Faculty of Health and Social Sciences, Bournemouth University, Bournemouth, UK.

Jeremy Chataway (J)

Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK/National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, London, UK.

Colin Green (C)

Health Economics Group, University of Exeter Medical School, University of Exeter, Exeter, UK/Collaboration (ARC) South West Peninsula, University of Exeter Medical School, University of Exeter, Exeter, UK.

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Classifications MeSH