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Improving Maternity Safety through novel AI enabled analytics/Maternity Observatory

Improve maternity care and safety through the creation of a regional maternity observatory to allow sharing of enhanced insights to proactively identify outlier units and share learning from best practices.

  • Proposal
  • 2020

Meet the team

Also:

  • Members of the regional maternity leadership team and relevant stakeholders. Details TBC
  • C2Ai team

What is the positive change that has emerged through new collaborations or partnerships during Covid-19 that your project is going to embed?

Even prior to the COVID 19 Pandemic, the recent inquiries on maternity services have highlighted the need for early  intervention and support for maternity units that are failing to meet national clinical standards. COVID 19 has exacerbated some of the issues.

The Covid Pandemic catalysed the development of a regional Maternity Safety Cell including regional maternity leaders, the relevant AHSNs, Local Maternity System leaders, Strategical Clinical Network Professionals and the creation of a regional maternity observatory will further enhance the effectiveness of these new collaborations and provide a vehicle for regional learning and dissemination of good practice.

The clinical leaders  within the South East are exploring use of  hospital coded data and utilising novel AI enabled analytics tools to create a regional ‘Maternity Observatory’ in order to benchmark clinical outcomes. For example, in one maternity unit the use of risk adjusted benchmarking resulted in demonstrable improvements in reducing the stillbirth rate.

What does your project aim to achieve?

We aim to generate systems and processes that help improve maternity care and patient safety.  We plan to embed learning through the creation of  a regional maternity observatory to allow sharing of enhanced insights to proactively identify outlier units and share learning from best practices in order to reduce unwanted variance in clinical practice across the region and improve health outcomes with a specific focus on health inequalities.

How will the project be delivered?

The project will be overseen by Prof Minesh Khashu, who has experience of regional and national roles in neonatology and maternity. The regional team will include all regional relevant stakeholders and maternity leaders.

The regional team will be supported by C2-Ai (C2-Ai.com), a leading health analytics provider that has supported the CQC and Keogh reviews, to undertake the analysis and insights reporting.  C2-Ai will be responsible for information security and that data governance requirements are complied with.

The regional clinical team will meet to discuss the findings of the data insights in the form of a quarterly report and have influence on future insights and KPI development as the basis for national benchmarking and a national maternity unit observatory.

As part of the analysis, an economic evaluation (Harris unit clinical cost efficiency analysis) will be undertaken to look at the direct cost impact of clinical quality and improvement and ROI.

How is your project going to share learning?

This will be the first-time risk adjusted methodology has been applied to maternity services across an entire region. The benefit of doing so will allow the set-up of regional and national speciality specific benchmarks to set the standards for maternity services and allow like for like comparison among maternity units. In so doing, we will facilitate early identification of outlier units and allow root cause analysis and early remedial action to take place in a timely manner.

The shared learning from quality improvement projects where need has been identified and improvements generated, will be disseminated across all the units in the region and made available to Q  members to benefit from the learning and best practices. We also aim to publish our work in international peer reviewed journals and share our learning at conferences and relevant events.

How you can contribute

  • 1. Any suggestions for improvement based on similar work done in a different speciality/field.
  • 2. Collaborate with us and get involved in this work.
  • 3. Share any relevant insights.

Plan timeline

21 Sep 2020 please see GANTT chart uploaded above