# Genomics workforce views on automating genomic reanalysis: trust, equity and governance

## TL;DR

This study explores how healthcare professionals view the automation of genomic reanalysis, highlighting concerns about trust, transparency, and governance.

## Contribution

The paper provides new insights into the ethical and practical challenges faced by clinical staff regarding automated genomic reanalysis.

## Key findings

- Participants supported automation but emphasized the need for transparency and human oversight.
- Legal and moral obligations to return results were a major concern among participants.
- A centralized system with national governance was proposed to ensure equitable implementation.

## Abstract

Automation of genomic data reanalysis can increase diagnostic rates in a timely and cost-effective manner. However, implementing automated reanalysis brings with it both ethical and practical challenges. We sought to explore how clinical and laboratory staff view these challenges as part of a broader study piloting automated genomic reanalysis. Focus groups were conducted with 21 genetics health professionals recruited from a previous survey and purposively sampled from clinical genetics diagnostics services and laboratories. Participants were supportive of automating reanalysis but discussed trust and accuracy, and emphasized the need for transparency, updated phenotypic information and human checking in an automated model. Legal versus moral obligation to return results when patients are unable to be recontacted was extensively discussed. Participants held concerns about a potential legal obligation to return results arising as reanalysis becomes routine and potential for impacts on workflow. A centralized system with national governance was proposed to ensure development and implementation of an equitable service and facilitate communication between patients and genetics services. However, this may be limited by existing infrastructure and the public’s perception of government services. In conclusion, participants in this study supported automated reanalysis, however issues regarding transparency, trust and accuracy will need to be systematically addressed to support implementation.

The online version contains supplementary material available at 10.1007/s00439-026-02824-7.