Health tech provider C2-Ai has formally launched a new ‘observatory’ system to help hospitals gain a better understanding of risks, outcomes and safety within maternity and neonatal services.
Announced at the annual NHS ConfedExpo, the new system will equip hospitals and frontline teams with a detailed picture of individual health trajectories for women, and the performance of maternity units.
Known as the ‘Maternity & Neonatal Observatory’, the system is based on a highly regarded AI-backed risk methodology already used in the NHS, and in top hospitals around the world, to measure safety and performance, highlight hidden risks in healthcare, and safely manage waiting lists.
By shining new light on outcomes for mothers and babies, it will help healthcare providers to proactively identify and address areas of concern early within maternity services, before they escalate or become systemic problems.
Frontline clinical teams will also be better informed about specific risks and care requirements for individual women, including any specialised support needed to ensure favourable outcomes.
Dr Mark Ratnarajah, a practising NHS paediatrician and UK managing director for C2-Ai, said: “Maternity services have come under close scrutiny in the public eye. By working closely with partners in the NHS, we will provide capabilities that can alert healthcare providers to challenges at the earliest of stages. And they will have new analysis to help them to demonstrate quality to regulators, maternity incentive schemes, and the outside world.
“Insights needed to achieve this can often be buried within data held in disparate places. We can now decode that complex clinical data, and unearth intelligence needed to support a learning environment. In addition to current evaluations of compliance with processes, services will have a new means to help them understand, interrogate, and enhance outcomes on an almost continuous basis.”
Early adopters within the NHS are expected soon, with maternity teams in trusts across several regions having already provided positive feedback on the observatory’s capabilities.
The system works by calculating and comparing in-detail observed outcomes for women and babies, in relation to expected outcomes for those individuals. Tailored for the acuity level of each maternity and neonatal service, the observatory uses AI and machine learning algorithms, widely proven in the NHS and internationally, to assess a total of 47 clinical factors. It takes into account case-mix adjusted maternal and neonatal clinical outcomes, impacts from social determinants of health such as ethnicity and deprivation, and comorbidities.
Maternity services are then able to visualise in granular detail where they may need to focus attention. The same system then allows providers to track if policy changes and quality improvement measures put in place have led to improvements.
Healthcare providers will be better equipped to identify patterns – for example the prevalence of sudden or unexpected increases in complications. Th