A novel digital platform for ‘smart’ maternity triage at the onset of labour to help clinicians prevent fetal brain injury during childbirth – translation of research source code into commercial-grade software

Health problem: Each year in the UK, over 1100 term, healthy babies sustain permanent brain damage due to lack of oxygen during labour and delivery1 (1.15 million globally)2. Half of these injruies are preventable with better monitoring of fetal wellbeing and more individualised labour management1–4. The NHS paid £3.5bn in 2022/23 for maternity-related negligence claims3. Most payouts relate to shortcomings in fetal monitoring and labour management3-7. Fetal health in labour is monitored with cardiotocography (CTG), which displays uterine contractions and fetal heart rate continuously8,9, producing long complex graphs. Clinicians interpret the CTG visually to identify signs of oxygen deprivation and expedite delivery if necessary (e.g. Caesarean section). But CTG patterns are difficult to interpret and confounding with multiple risk factors is not well understood4,8-10. Many tragic outcomes stem from our inability to: (1) reliably triage high-risk cases needing extra clinical attention in labour; (2) consider the individual combination of multiple maternal/fetal clinical risk factors when interpreting the CTG; (3) effectively communicate the risks within clinical teams and with parents1,11-15. Our solution: To address these problems, we have developed the Fit4Labour tool for smart triage at the maternity ward. It combines 20-60 minutes of CTG recording from the onset of labour with clinical data about mother and pregnancy, to provide individualised risk score. Its data-driven methodoloty already uses data from 100,000 births and is designed to support clinical decision-making and avoid the worst outcomes. Fit4Labour is a Tier C Digital Health Technology16 and only takes data inputs already available at the hospital. Risk factors included alongside the CTG include gestational age, maternal age, maternal co-morbidities and temperature, parity, and presence of thick meconium. Fit4Labour is valid for pregnancies of 36 weeks or more and CTGs taken within five hours before or after labour onset. Progress to date: Curated, processed and analysed multicentre datasets with size and detail unprecedented worldwide. Developed and tested the source code for analysis of the CTG, using Matlab (a research programming platform). Developed Fit4Labour, ensuring optimal accuracy on the datasets (patent filed, publication in preparation). Built a fully functional mobile App that works in real-time at the hospital, taking required data directly from the hospital infrastructure and calculating the risk-score using the Matlab codes. Conducted a feasibility study at the hospital with 63 labouring women. Conducted usability sessions with midwives and doctors, co-developing the App s interface and functionality, achieving excellent usability scores. Conducted early health economic modelling17; qualitative research of the needs/requirements of clinicians18 and families19; barriers to adoption and market research. These showed significant value to the NHS and acceptability by clinicians and patients. Parent, Patient and Public Involvement (PPPI): Our research and this proposal are supported by a dedicated PPPI panel, comprising members with diverse experience, led by two PPPI co-leads (https://www.wrh.ox.ac.uk/research/oxfordlabourmonitoringgroup/parent-patient-public-involvement) Relevance to programme scope: Fit4Labour aims to help clinicians prevent brain injury to the baby, developing de-novo during childbirth, which is directly aligned with the scope of this FAST call. Alex from the i4i FAST team confirmed eligibility by email on 26th Sept 24.