top of page
  • Writer's pictureHFUX Research | Medical HF

Best Practices for Use-Related Risk Analysis Through Collaboration of Human Factors and Clinical


Integrating human factors and its user-centered approach and corresponding Human Factors Engineering (HFE) process into risk management of medical devices has been an ongoing challenge for Human Factors (HF) practitioners and their partners for decades.

The introduction of the European MDR in 2017 placed emphasis on the importance of use-related risk within the clinical evaluation and introduced clinical teams to new challenges as well. This poster provides best practices for early integration of an iterative use-related risk analysis process and how to do so using a collaborative approach between HF teams and clinical teams.


Phase 1: Discovery and Concept

  • Conduct early exploratory research to identify use-related issues in the field. Ensure data collected includes hazardous use scenarios with respect to current products on market addressing your intended use concept.

  • Use clinical resources, e.g., literature, patient groups etc. to plan field research with respect to use-related risk perception and safety aspects.

  • Leverage a systematic, task-based analysis approach to identify potential hazardous situations and design opportunities.

Phase 2: Formulation and Planning

  • Draft an initial framework of the device task analysis and identify potential use problems, (e.g., use errors, close calls, and use difficulties) related to all tasks.

  • Include use-related risks, usability, clinical, and risk management requirements sections in HFE plan, clinical evaluation plan, and risk management plan.

Phase 3: Design and Development

  • Utilize formative human factors usability studies to assess early prototypes understand their actual use in both positive and negative use scenarios with respect to use(r) preferences, acceptance, performance, as well as potential use-related risks.

  • Document observed and/or reported use errors and difficulties and subject them to analysis equivalent to that performed for use(r) preferences, acceptance, and/or performance.

  • Simulate real-world settings in clinical studies, when feasible and appropriate, to evaluate the efficacy of your early design concepts.

Phase 4: Validation and Product Launch

  • Collaborate between HFE, clinical evaluation, and risk management teams; provide input into each other’s evaluation and validation plans.

  • Align goals of human factors and clinical evaluation studies with respective requirements, e.g., identify opportunities for hybrid data collection studies.

  • Conduct hybrid data collection studies when possible, addressing evaluation and validation of clinical and usability requirements, including use-related risks. Aim to capture typically elusive data points, e.g., use-related risk mitigations addressed by “knowledge tasks”.

  • Simulate real-world settings in clinical studies when feasible and appropriate for validation of final designs.

  • When appropriate, use a staggered approach for device design validation, employing simulated-use data combined with real-world data.

  • Exercise the same degree of scrutiny in the design of regional adaptations and their respective "information for safety" as in device master record (DMR).

Phase 5: Market Introduction and Post-Market Surveillance

  • Coordinate and synchronize Post-Market Clinical Follow-up and post-market surveillance activities within product development (incl. HFE), clinical evaluation, and regulatory teams to enhance the integration of (post-market) feedback into subsequent generations of (your) devices.

FDA human factors engineering use-related risk analysis best practices for medical device development


The best practices outlined above can help to resolve current practical challenges when combining risk-based and user-centered design thinking into medical device product development by applying a collaborative approach between HF teams and clinical teams.

This approach can potentially facilitate the collection of hybrid data for a parallel HF evaluation and clinical evaluation and result in more robust data collection, optimized residual risk and benefit-risk analyses, facilitation of comprehensive development documentation, and strengthening of HF and clinical evaluation processes and reporting.


Heidi M. Mehrzad, HFUX Research, LLC

Thomas Stüdeli, Hoffmann-La Roche Ltd.

Helene Quie, Qmed Consulting A/S

You can find and read our paper here.

27 views0 comments


bottom of page