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Currently submitted to: JMIR Human Factors

Date Submitted: Mar 3, 2026
Open Peer Review Period: Mar 16, 2026 - May 11, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Towards a Multi-Criteria Decision-Making Framework: Assessing Suitability of Human Reliability Analysis Methods for Surgery

  • Mo Cong; 
  • Xueyang Liu; 
  • Weidong Liu; 
  • Jiayuan He; 
  • Juan Lin; 
  • Jianqiao Liu

ABSTRACT

Background:

Human reliability analysis (HRA) is regarded as an indispensable step in significantly enhancing the quality and safety of surgery. Nevertheless, HRA techniques are severely constrained and no formal HRA method for surgery has been published.

Objective:

This study established a multicriteria decision-making framework to support the selection of HRA techniques in the surgical sector.

Methods:

The framework integrates triangular fuzzy numbers, CRITIC, and VIKOR methods to quantitatively address complex decision problems with conflicting criteria and uncertainty of subjective judgments in the assessment process.

Results:

results of the case study suggest that the preferred option is METHOD 0, followed by SPAR-H, SLIM, and THERP. The case study suggests that in actual medical risk assessment, a more practical choice is to use SPAR-H to identify critical surgical tasks which may be potential significant risks, then conduct an in-depth analysis using THERP’s detailed event tree.

Conclusions:

The This study lays the groundwork for a practical framework to assist surgery safety managers in selecting appropriate HRA techniques.


 Citation

Please cite as:

Cong M, Liu X, Liu W, He J, Lin J, Liu J

Towards a Multi-Criteria Decision-Making Framework: Assessing Suitability of Human Reliability Analysis Methods for Surgery

JMIR Preprints. 03/03/2026:94583

DOI: 10.2196/preprints.94583

URL: https://preprints.jmir.org/preprint/94583

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