Transparency in Decision Modelling: What, Why, Who and How?
Transparency in decision modelling is an evolving concept. Recently, discussion has moved from reporting standards to open-source implementation of decision analytic models. However, in the debate about the supposed advantages and disadvantages of greater transparency, there is a lack of definition. The purpose of this article is not to present a case for or against transparency, but rather to provide a more nuanced understanding of what transparency means in the context of decision modelling and how it could be addressed. To this end, we review and summarise the discourse to date, drawing on our collective experience. We outline a taxonomy of the different manifestations of transparency, including reporting standards, reference models, collaboration, model registration, peer review and open-source modelling. Further, we map out the role and incentives for the various stakeholders, including industry, research organisations, publishers and decision makers. We outline the anticipated advantages and disadvantages of greater transparency with respect to each manifestation, as well as the perceived barriers and facilitators to greater transparency. These are considered with respect to the different stakeholders and with reference to issues including intellectual property, legality, standards, quality assurance, code integrity, health technology assessment processes, incentives, funding, software, access and deployment options, data protection and stakeholder engagement. For each manifestation of transparency, we discuss the ‘what’, ‘why’, ‘who’ and ‘how’. Specifically, their meaning, why the community might (or might not) wish to embrace them, whose engagement as stakeholders is required and how relevant objectives might be realised. We identify current initiatives aimed to improve transparency to exemplify efforts in current practice and for the future.
SE kindly acknowledges his colleagues at Collaborations Pharmaceuticals.
All authors were involved in the conception and planning of the manuscript, wrote sections, edited and commented on drafts and approved the submitted version. CS organised and led the write-up and contributed to the writing of all sections. RA wrote parts of Sects. 1–5. SB wrote parts of Sects. 4 and 5. PC wrote parts of Sects. 2. SE wrote parts of Sects. 2, 4 and 5. AH wrote parts of Sects. 2–5. NH wrote parts of Sects. 1, 3 and 4. SL wrote parts of Sects. 2–5. DM wrote parts of Sects. 1, 3 and 5. MS wrote parts of Sects. 2–5. WS wrote parts of Sects. 1–5. EW wrote parts of Sects. 1–4. TW wrote parts of Sects. 2–5.
Compliance with Ethical Standards
No specific funding was received to support the preparation of this manuscript. CS is an employee of the Office of Health Economics, a registered charity, research organisation and consultancy, which receives funding from a variety of sources including the Association of the British Pharmaceutical Industry and the National Institute for Health Research (NIHR). CS has received honoraria from the NIHR in relation to peer review activities. CS has received travel support from Duke University for attendance at a meeting related to the content of this manuscript. SB receives salary support from the University of British Columbia, Vancouver Coastal Health and the British Columbia Academic Health Science Network. He previously chaired CADTH’s Health Technology Expert Review Panel and provides consultancy advice to CADTH, for which he received honoraria and travel support. All of his decision model project work is supported through public sources, primarily the Canadian Institutes for Health Research (CIHR) and the BC Ministry of Health. PC has received payment for workshops run alongside Mt Hood conferences. SE is CEO and Owner of Collaborations Pharmaceuticals, Inc. SE has received a grant from the National Institutes for Health to build machine learning models and software. DM is employed by the University of Calgary, with a salary funded by Arthur J.E. Child Chair in Rheumatology and Canada Research Chair in Health Systems and Services Research. DM’s research is funded through multiple funding organisations including the CIHR, Arthritis Society, CRA and AAC in peer-reviewed funding competitions, none of which relate to this work. DM has received reimbursement for travel from Illumina and Janssen for attendance and presentation at scientific meetings not related to this work. RA, AH, NH, SL, MS, WS, and EW declare that they have no conflicts of interest. TW is a Co-Editor of PharmacoEconomics, but was not involved in the peer review nor any editorial decisions for this paper.
SE acknowledges funding from NIH/ NIGMS R43GM122196, R44GM122196-02A1.
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