Verification of Decision-Analytic Models for Health Economic Evaluations: An Overview.

Decision-analytic models for cost-effectiveness analysis are developed in a variety of software packages where the accuracy of the computer code is seldom verified. Although modeling guidelines recommend using state-of-the-art quality assurance and control methods for software engineering to verify...

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Publicado en:PharmacoEconomics Vol. 35; no. 7; pp. 673 - 684
Autores principales: Dasbach, Erik, Elbasha, Elamin, Dasbach, Erik J, Elbasha, Elamin H
Formato: review Journal Article
Publicado: Springer Nature Jul2017
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Verification of Decision-Analytic Models for Health Economic Evaluations: An Overview.
      aug:
        au:
          Dasbach, Erik
          Elbasha, Elamin
          Dasbach, Erik J
          Elbasha, Elamin H
        affil: Merck & Co. Inc., Kenilworth, NJ, USA
      sug:
        subj:
          Decision Support Techniques
          Models, Statistical
          Economics, Pharmaceutical
          Software
          Cost Benefit Analysis
          Quality Assessment
          Ferrans and Powers Quality of Life Index
          Questionnaires
      ab: Decision-analytic models for cost-effectiveness analysis are developed in a variety of software packages where the accuracy of the computer code is seldom verified. Although modeling guidelines recommend using state-of-the-art quality assurance and control methods for software engineering to verify models, the fields of pharmacoeconomics and health technology assessment (HTA) have yet to establish and adopt guidance on how to verify health and economic models. The objective of this paper is to introduce to our field the variety of methods the software engineering field uses to verify that software performs as expected. We identify how many of these methods can be incorporated in the development process of decision-analytic models in order to reduce errors and increase transparency. Given the breadth of methods used in software engineering, we recommend a more in-depth initiative to be undertaken (e.g., by an ISPOR-SMDM Task Force) to define the best practices for model verification in our field and to accelerate adoption. Establishing a general guidance for verifying models will benefit the pharmacoeconomics and HTA communities by increasing accuracy of computer programming, transparency, accessibility, sharing, understandability, and trust of models.
      pubtype: Academic Journal
      doctype:
        review
        Journal Article
      ougenre: Article
    language: English
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