Ranking Decision-Making Criteria for Early Adoption of Innovative Surgical Technologies.


Journal

JAMA network open
ISSN: 2574-3805
Titre abrégé: JAMA Netw Open
Pays: United States
ID NLM: 101729235

Informations de publication

Date de publication:
01 Nov 2023
Historique:
medline: 27 11 2023
pubmed: 17 11 2023
entrez: 16 11 2023
Statut: epublish

Résumé

There is no decision-making framework in the early-adoption stage of novel surgical technologies, putting the quality of health care and resource allocation of the health care system at risk. To investigate relevant weighted criteria that decision-makers may use to make an informed decision for the early adoption of innovative surgical technologies. This multi-institutional decision analytical modeling study used a mixed-methods multicriteria decision analysis (MCDA) and had 2 phases. First, a panel of 12 experts validated decision criteria in the literature and identified additional criteria. Second, 33 Canadian experts prioritized the main criteria (domains) using the composition pairwise-comparison weight-elicitation method (analytical hierarchy process model) and ranked their subcriteria using the direct-ranking elicitation method (Likert scale). Data were analyzed, and response consistency was estimated using the consistency ratio. Analysis of variance was used to assess for significant differences between expert responses. The MCDA was conducted at McGill University between 2021 and 2023. Data were collected nationally by inviting experts in Canada. Criteria domain weights and subcriteria rankings. Priority vectors, which are priority scores analyzed and prioritized from expert responses, were used to rank criteria domains and subcriteria for decision-making on adopting new innovative surgical technologies. A total of 45 experts (33 male [73.3%] and 12 female [26.7%]) were invited with different levels of education (22 experts with MD or equivalent, 13 experts with master's degree, and 12 experts with PhD degree) and years of experience (4 experts with <10, 12 experts with 11-20, 18 experts with 21-30, and 11 experts with >30 years). Surgeon experts (23 individuals) were from all surgical disciplines, and nonsurgeon experts (22 individuals) were administrative officers in surgical device procurement, health technology assessment experts, and hospital directors. A total of 7 domains and 44 subcriteria were identified. The MCDA model found that clinical outcomes had the highest priority vector, at 0.429, followed by patients and public relevance (0.135). Hospital-specific criteria (priority vector, 0.099), technology-specific criteria (priority vector, 0.092), and physician-specific criteria (priority vector, 0.087) were the next most highly ranked. The lowest priority vectors were for economic criteria, at 0.083, and finally policies and procedures, at 0.075. There was consensus in the responses (consistency ratio = 0.006), and there were no statistically significant differences between expert responses. This study weighted priority criteria domains in importance and established ranked subcriteria for decision-making of early adoption of surgical technologies. Putting these criteria into a framework may help surgeons and decision-makers make informed decisions for the early adoption of new surgical technologies.

Identifiants

pubmed: 37971741
pii: 2811940
doi: 10.1001/jamanetworkopen.2023.43703
pmc: PMC10654796
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2343703

Références

ANZ J Surg. 2013 Jun;83(6):422-8
pubmed: 23638720
Surg Innov. 2021 Aug;28(4):401-402
pubmed: 34281433
Int J Technol Assess Health Care. 1997 Spring;13(2):133-43
pubmed: 9194350
J Endourol. 2017 Sep;31(9):886-892
pubmed: 28699357
Int J Technol Assess Health Care. 2010 Jul;26(3):341-7
pubmed: 20584365
J Public Econ. 2009 Apr 1;93(3-4):541-548
pubmed: 20454467
Med Devices (Auckl). 2014 Jun 13;7:205-9
pubmed: 24966699
Int J Technol Assess Health Care. 2019 Jan;35(3):204-211
pubmed: 31017075
J Am Coll Radiol. 2019 Feb;16(2):208-210
pubmed: 30389329
J Health Econ. 2013 Jan;32(1):172-80
pubmed: 23202262
Value Health. 2016 Mar-Apr;19(2):125-37
pubmed: 27021745
Br Med Bull. 2007;81-82:51-64
pubmed: 17409119
CMAJ. 2007 Feb 27;176(5):616
pubmed: 17325321
Eur J Health Econ. 2018 Jan;19(1):123-152
pubmed: 28303438
J Biomed Inform. 2016 Feb;59:201-8
pubmed: 26705065
Health Aff (Millwood). 2007 May-Jun;26(3):696-703
pubmed: 17485746
Health Econ. 2017 Feb;26 Suppl 1:5-12
pubmed: 28139084
Surg Endosc. 2013 Jul;27(7):2253-7
pubmed: 23660720
Int J Technol Assess Health Care. 2000 Winter;16(1):282-90
pubmed: 10815373
Int J Technol Assess Health Care. 2023 Jun 19;39(1):e41
pubmed: 37334665

Auteurs

Haitham Shoman (H)

Department of Experimental Surgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
Vanier Scholar, Canadian Institutes of Health Research.

Nisha D Almeida (ND)

Health Technology Assessment Unit, McGill University Health Centre, Montreal, Quebec, Canada.
Division of Clinical Epidemiology, McGill University, Montreal, Quebec, Canada.

Michael Tanzer (M)

Division of Orthopaedic Surgery, McGill University, Montreal, Quebec, Canada.

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