{
  "abstract": "Background UK ambulance services face record demand, resourcing challenges and rising clinical documentation burden. Ambient voice technology (AVT) coupled with generative AI offers a potential solution by automatically transcribing consultations and drafting clinical notes. Our aim was to test AVT in a complex and undifferentiated pre-hospital context.Methods A within–subject pre–post evaluation of ambient voice technology was undertaken with clinicians in two operational pathways (remote telephone triage in the Clinical Hub (‘Hear and Treat’) and on-scene care provided by paramedics (‘Face-to-Face’) in a large metropolitan ambulance trust. Data collected included assessment duration; number of patients handled per hour or shift; documentation quality; on-scene, handover and combined incident ‘job cycle’ times; clinician experience and cognitive load (NASA-TX).Results 656 Hear and Treat cases were managed with AVT. Compared with baseline, AVT shortened assessments by two minutes (15 vs 17 minutes) and increased throughput by 15% (2.3 vs 2.0 patients/hour) without compromising documentation quality. In Face-to-Face care (n=344 AVT contacts) mean on–scene time decreased from 44 to 41 minutes (–6.8%), while median improvement was 15.2% (46 to 39 minutes). Combined on–scene + handover–to–clear time reduced by 2.8 minutes (–4.8%). Across both settings there was a significant reduction in clinician cognitive load, improvement in clinician experience and perceived benefits to patients.Conclusion This evaluation demonstrated an increase in remote telephone triage throughput and a reduction in on-scene care times with AVT. Scaling such improvements would translate into real-world operational gains that, if implemented nationally, would ease pressures on ambulance services whilst improving patient care. AVT demonstrably frees clinical time across remote ambulance workflows, aligning with national ambitions to ‘bulldoze bureaucracy’ and speed-up care. Strategic scaleup with robust governance could release capacity equivalent to thousands of additional patient contacts each day and improve outcomes for some of the most unwell patients.Acknowledgements for Funding or Support The evaluation was supported by NHS England (London) Frontline Digitisation and Great Ormond Street Hospital DRIVE unit; the AVT platform (Tortus AI) was supplied free of charge. London Ambulance Service NHS Trust technical and clinical project resourcing was provided for pilot implementation.",
  "authors": [
    {
      "affiliations": [
        "London Ambulance Service, UK"
      ],
      "name": "David Davis"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Jo Wray"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Geralyn Oldham"
    },
    {
      "affiliations": [
        "London Ambulance Service, UK"
      ],
      "name": "Daniel Elkeles"
    },
    {
      "affiliations": [
        "London Ambulance Service, UK"
      ],
      "name": "Timothy Borham"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Paul Gough"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Maya Tomlinson"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Nick James"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Alastair Hill"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Eleanor Sullivan"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Stephen Mathew"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Robert Robinson"
    },
    {
      "affiliations": [
        "Tortus, UK"
      ],
      "name": "Jasmine Balloch"
    },
    {
      "affiliations": [
        "Tortus, UK"
      ],
      "name": "Dom Pimenta"
    },
    {
      "affiliations": [
        "London Ambulance Service, UK"
      ],
      "name": "Sarah Kirk"
    },
    {
      "affiliations": [
        "London Ambulance Service, UK"
      ],
      "name": "Anna Booth"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Andrew Taylor"
    },
    {
      "affiliations": [
        "Great Ormond Street Hospital for Children NHS Foundation Trust, UK"
      ],
      "name": "Shankar Sridharan"
    }
  ],
  "title": "100 ‘What witchcraft is this?’: Paramedics report gains in productivity, well-being, and patient flow from piloting ambient voice technology in an NHS Ambulance Service",
  "uid": "e4606a92-8047-5db8-b96e-65c039c14672"
}