# Expert Views on Criteria for Evaluation of Human Factors Methods: Qualitative Interview Study

## TL;DR

Experts identified criteria for evaluating human factors methods in health IT projects to improve safety and effectiveness.

## Contribution

A novel framework for evaluating human factors methods in real-world health IT projects was proposed.

## Key findings

- Five main criteria and 28 subcriteria for evaluating human factors methods were identified.
- Experts emphasized effectiveness, efficiency, ease of use, acceptability, and impact on solutions.
- The framework aims to help organizations optimize human factors methods application.

## Abstract

Human factors (HF), or ergonomics, which explores the interaction between humans and systems, has been used to support design in safety-critical industries such as aviation, transportation, nuclear power, and manufacturing. HF methods have the potential to support the safe design of health IT; however, the evaluation of HF methods to determine their effectiveness and feasibility in this context has been limited.

The aim of this study was to identify criteria for evaluating HF methods when applied to real-world projects and to use these to propose a framework for method evaluation.

The study design was qualitative and descriptive and involved semistructured interviews with HF experts working across health and nonhealth industries in academic and/or practitioner roles. HF experts held a relevant degree (eg, ergonomics and HF engineering) and were actively using their HF expertise. Results were thematically analyzed.

A total of 21 participants took part, and interviews lasted, on average, 52 (range 39‐103) minutes. Participants mentioned that they did not routinely evaluate methods; however, when asked how they would evaluate methods, they outlined a range of criteria to support method evaluation. Overall, 5 criteria and 28 subcriteria were identified. High-level criteria included effectiveness, efficiency, ease of use and acceptability, and impact on the solution.

Results from this study were used to propose a framework for evaluating HF methods used in real-world health IT projects. The framework should provide organizations with valuable information on how to optimize the application and outcomes of HF methods and build HF capability within organizations, particularly where this capability may be lacking.