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Assessment of technical errors and validation processes in economic models submitted by the company for NICE technology appraisals.
Radeva, Demi; Hopkin, Gareth; Mossialos, Elias; Borrill, John; Osipenko, Leeza; Naci, Huseyin.
Afiliação
  • Radeva D; Department of Health Policy, London School of Economics and Political Science, London, UK.
  • Hopkin G; United Health Group, Eden Prairie, Minnesota, USA.
  • Mossialos E; Department of Health Policy, London School of Economics and Political Science, London, UK.
  • Borrill J; Institute of Health Economics, Edmonton, Alberta, Canada.
  • Osipenko L; Department of Health Policy, London School of Economics and Political Science, London, UK.
  • Naci H; Bristol-Myers Squibb, Uxbridge, London, UK.
Article em En | MEDLINE | ID: mdl-32618536
ABSTRACT

BACKGROUND:

Economic models play a central role in the decision-making process of the National Institute for Health and Care Excellence (NICE). Inadequate validation methods allow for errors to be included in economic models. These errors may alter the final recommendations and have a significant impact on outcomes for stakeholders.

OBJECTIVE:

To describe the patterns of technical errors found in NICE submissions and to provide an insight into the validation exercises carried out by the companies prior to submission.

METHODS:

All forty-one single technology appraisals (STAs) completed in 2017 by NICE were reviewed and all were on medicines. The frequency of errors and information on their type, magnitude, and impact was extracted from publicly available NICE documentation along with the details of model validation methods used.

RESULTS:

Two STAs (5 percent) had no reported errors, nineteen (46 percent) had between one and four errors, sixteen (39 percent) had between five and nine errors, and four (10 percent) had more than ten errors. The most common errors were transcription errors (29 percent), logic errors (29 percent), and computational errors (25 percent). All STAs went through at least one type of validation. Moreover, errors that were notable enough were reported in the final appraisal document (FAD) in eight (20 percent) of the STAs assessed but each of these eight STAs received positive recommendations.

CONCLUSIONS:

Technical errors are common in the economic models submitted to NICE. Some errors were considered important enough to be reported in the FAD. Improvements are needed in the model development process to ensure technical errors are kept to a minimum.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Health_technology_assessment / Prognostic_studies Idioma: En Revista: Int J Technol Assess Health Care Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Health_technology_assessment / Prognostic_studies Idioma: En Revista: Int J Technol Assess Health Care Ano de publicação: 2020 Tipo de documento: Article