Mixed-method evaluation of ambient voice technology: phase 1

Clinical documentation consumes a substantial proportion of health professionals’ working time, contributing to workload pressures, staff burnout and inefficiencies in patient care. In response, health systems are increasingly looking to digital tools that can improve productivity while maintaining care quality. Ambient voice technology (AVT) uses conversational AI to capture and structure clinical encounters in real time, with the potential to reduce administrative burden, support more timely records and improve communication between clinicians and patients.

Adoption of AVT is accelerating across health care and particularly in primary care and acute care settings. But existing evidence is fragmented, often industry-led, or limited to evaluations of individual products. This comes at a time when regulatory and procurement frameworks for digital health technologies are rapidly evolving. NICE, the MHRA and the NHS have introduced guidance covering safety, interoperability and information governance, but these frameworks require robust, independent evidence on real-world use and impact to support informed decision-making.

This publication presents the Phase 1 findings from an independent evaluation of ambient voice technology in the NHS in England. Phase 1 establishes the evidence base and evaluation foundations for subsequent research, including a synthesis of existing evidence, a taxonomy of AVT systems, mapping of current adoption and procurement models across NHS settings, and the development of logic models and data strategies to support robust assessment of impact in Phase 2.

Resources and findings from phase 1

Read the slide deck report

Taxonomy of characteristics of AVT tools in health care