Literature DB >> 28669122

Validation of a DICE Simulation Against a Discrete Event Simulation Implemented Entirely in Code.

Jörgen Möller1, Sarah Davis2, Matt Stevenson2, J Jaime Caro3,4,5.   

Abstract

BACKGROUND: Modeling is an essential tool for health technology assessment, and various techniques for conceptualizing and implementing such models have been described. Recently, a new method has been proposed-the discretely integrated condition event or DICE simulation-that enables frequently employed approaches to be specified using a common, simple structure that can be entirely contained and executed within widely available spreadsheet software. To assess if a DICE simulation provides equivalent results to an existing discrete event simulation, a comparison was undertaken.
METHODS: A model of osteoporosis and its management programmed entirely in Visual Basic for Applications and made public by the National Institute for Health and Care Excellence (NICE) Decision Support Unit was downloaded and used to guide construction of its DICE version in Microsoft Excel®. The DICE model was then run using the same inputs and settings, and the results were compared.
RESULTS: The DICE version produced results that are nearly identical to the original ones, with differences that would not affect the decision direction of the incremental cost-effectiveness ratios (<1% discrepancy), despite the stochastic nature of the models. LIMITATION: The main limitation of the simple DICE version is its slow execution speed.
CONCLUSIONS: DICE simulation did not alter the results and, thus, should provide a valid way to design and implement decision-analytic models without requiring specialized software or custom programming. Additional efforts need to be made to speed up execution.

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Mesh:

Year:  2017        PMID: 28669122     DOI: 10.1007/s40273-017-0534-0

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


  10 in total

1.  Disease-simulation models and health care decisions.

Authors:  J J Caro
Journal:  CMAJ       Date:  2000-04-04       Impact factor: 8.262

2.  The impact of ignoring population heterogeneity when Markov models are used in cost-effectiveness analysis.

Authors:  Gregory S Zaric
Journal:  Med Decis Making       Date:  2003 Sep-Oct       Impact factor: 2.583

3.  A taxonomy of model structures for economic evaluation of health technologies.

Authors:  Alan Brennan; Stephen E Chick; Ruth Davies
Journal:  Health Econ       Date:  2006-12       Impact factor: 3.046

Review 4.  Modelling methods for pharmacoeconomics and health technology assessment: an overview and guide.

Authors:  James E Stahl
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

5.  Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1.

Authors:  J Jaime Caro; Andrew H Briggs; Uwe Siebert; Karen M Kuntz
Journal:  Value Health       Date:  2012 Sep-Oct       Impact factor: 5.725

6.  State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--3.

Authors:  Uwe Siebert; Oguzhan Alagoz; Ahmed M Bayoumi; Beate Jahn; Douglas K Owens; David J Cohen; Karen M Kuntz
Journal:  Value Health       Date:  2012 Sep-Oct       Impact factor: 5.725

7.  Interpreting and comparing risks in the presence of competing events.

Authors:  Martin Wolkewitz; Ben S Cooper; Marc J M Bonten; Adrian G Barnett; Martin Schumacher
Journal:  BMJ       Date:  2014-08-21

8.  Discretely Integrated Condition Event (DICE) Simulation for Pharmacoeconomics.

Authors:  J Jaime Caro
Journal:  Pharmacoeconomics       Date:  2016-07       Impact factor: 4.981

9.  Probabilistic analysis and computationally expensive models: Necessary and required?

Authors:  Susan Griffin; Karl Claxton; Neil Hawkins; Mark Sculpher
Journal:  Value Health       Date:  2006 Jul-Aug       Impact factor: 5.725

Review 10.  Health economic modelling of treatment sequences for rheumatoid arthritis: a systematic review.

Authors:  Jonathan Tosh; Matt Stevenson; Ron Akehurst
Journal:  Curr Rheumatol Rep       Date:  2014-10       Impact factor: 4.592

  10 in total
  3 in total

1.  Smoking Cessation: A Comparison of Two Model Structures.

Authors:  Becky Pennington; Alex Filby; Lesley Owen; Matthew Taylor
Journal:  Pharmacoeconomics       Date:  2018-09       Impact factor: 4.981

2.  TECH-VER: A Verification Checklist to Reduce Errors in Models and Improve Their Credibility.

Authors:  Nasuh C Büyükkaramikli; Maureen P M H Rutten-van Mölken; Johan L Severens; Maiwenn Al
Journal:  Pharmacoeconomics       Date:  2019-11       Impact factor: 4.981

3.  Economic evaluation of betibeglogene autotemcel (Beti-cel) gene addition therapy in transfusion-dependent β-thalassemia.

Authors:  Anuraag R Kansal; Odette S Reifsnider; Sarah B Brand; Neil Hawkins; Anna Coughlan; Shujun Li; Lael Cragin; Clark Paramore; Andrew C Dietz; J Jaime Caro
Journal:  J Mark Access Health Policy       Date:  2021-06-07
  3 in total

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