NeoEPOCH: Neonatal Electronic health record data for Point Of Care Health research and continuous incremental improvement in neonatal care

1 in 11 UK babies are born prematurely; many of these need neonatal care that involves medical decisions about every part of a baby's care (like how best to support breathing). Many babies who require neonatal care have medical and neurological problems that affect them throughout their lives; these may be influenced by decisions made during their neonatal stay.

The ideal way to work out which clinical decision (i.e. which type of breathing support to use) is the best is a randomised trial. Here each baby has an equal chance of being given each decision (type of breathing support) and this is chosen by chance, like tossing a coin. By including lots of babies we can work out which decision (type of breathing support) works best. Unfortunately randomised trials are very expensive and burdensome because it is time-consuming to collect all the information. As a result, only a small number of neonatal clinical decisions have been tested in randomised trials and so most decisions are only educated guesses.

I want to make randomised clinical trials cheaper and easier so all day-to-day neonatal decisions can be based on the best research - randomised clinical trials. I plan to do this is by getting rid of the most expensive part, data collection. At the moment this is done by paying a researcher to check each baby's medical notes. I want to get all the information straight from a baby's electronic health record (EHR), a computerised version of the medical notes. Since 2007 all UK neonatal units have used one EHR system. Information from this EHR, on all babies admitted for neonatal care (with names and other identifying information removed), is held in the National Neonatal Research Database (NNRD). The NNRD is already used for other purposes, I want to use it for randomised trials to make them much cheaper and easier. These can be called Point-of-Care Trials (PoCT).

There are a number of problems to solve. Firstly, information in the EHR may not be completely accurate. We will deal with this by
1. Looking at other EHR systems to work out the best way to measure and report the accuracy of the neonatal EHR
2. Looking to see how other people have made EHR data more accurate
3. Using these techniques and measuring to see if they work using a cluster randomised controlled trial; this is like a larger randomised clinical trial but instead of each baby having an equal chance of getting one decision or another, each neonatal unit will have an equal chance of having one technique or another

We think that if parents are more involved in their baby's EHR data it will be more accurate. We will test this by asking parents to help us to help them use their baby's EHR data. Then we will try this out in the same cluster randomised trial to see if it makes EHR more accurate. We think that taking these steps will make the EHR accurate enough for PoCT, but we will also work out mathematically how to use EHR data even if it is not completely accurate.

Secondly, we want to make sure that PoCT will ask the right research questions in the right ways. We will do this by
1. Asking interested groups (doctors, nurses, parents, patients, etc.) what they think the most important "outcomes" for PoCT are. An "outcome" is a result of a trial, like whether a baby needs oxygen at home
2. Asking the same groups what the most important clinical decisions (like how to support a baby's breathing or what milk to start feeding with) are to test in PoCT

Thirdly, we want to show that we can carry out a PoCT using the neonatal EHR. To do this we will run a small PoCT over 20 neonatal units and one year. We will measure how accurate it is and whether it is easier and cheaper.

Finally we want to make sure that knowledge from PoCT can be quickly and effectively communicated across the NHS to improve the way babies are looked after so we will learn from the successes and mistakes of another health system that already does this.

Aims

1. Demonstrate feasibility, efficacy and efficiency of neonatal point-of-care trials (PoCT) using Electronic Health Record (EHR) data held by the National Neonatal Research Database (NNRD)
2. Develop a platform to leverage PoCT to improve neonatal care

Objectives and methods

Measure neonatal EHR data quality
- Methods: internal/external validation
Synthesise evidence for improving EHR data
- Methods: systematic review, meta-analysis
Develop parent-centred EHR data; test it alongside interventions identified from systematic review to see if it improves data quality
- Methods: Focus group, cluster randomised trial
Develop a core outcome set for neonatal PoCT
- Method: Delphi consensus process
Predict the influence of variable data quality on PoCT
- Method: Statistical modelling
Complete a pilot PoCT
- Method: A multi-centre, superiority, randomised point of care trial (WHEAT)
Map and prioritise neonatal treatment uncertainties
- Method: Delphi consensus process
Develop best practice for implementing PoCT results
- Methods: qualitative interviews with leaders/stakeholders

Scientific opportunities:

NeoEPOCH will reduce waste in neonatal research by testing multiple uncertainties in large pragmatic trials, identifying research questions of importance and disseminating trial results. NeoEPOCH aims to increase research participation by making parent and public participation central and will develop into an open platform for POCT. By facilitating collaborative, efficient, national trials NeoEPOCH will increase the attraction of UK neonatal services to multinational and commercial research funders.

Medical opportunities:

NeoEPOCH meets to need to improve neonatal clinical care by rapidly reducing treatment uncertainties, thus making it truly evidence based. By building a research platform around parent involvement NeoEPOCH aims to improve participation in research and build public trust in electronic health record data.

This fellowship will benefit the following groups:

1. Patients
- Greater Electronic Health Record (EHR) data quality will: a) improve patient care by reducing errors and improving communication; b) facilitate bench-marking between units reducing variation and inequalities in care; c) improve national audit programmes in identifying and disseminating best practice.
- In the medium-term, the large pragmatic point-of-care trials (PoCT) will improve the neonatal evidence base, impacting and improving health: conditions with long-term health effects (i.e. necrotising enterocolitis) are influenced by day-to-day clinical decisions (i.e. choice of milk feed); PoCT will allow these to be rigorously tested.
- NeoEPOCH will involve ex-preterm children in throughout to ensure that future research is responsive and relevant to patients.

2. Parents and the wider public
- By developing an intervention that places parents at the centre of their baby's EHR data we hope to empower parents to improve their baby's data quality.
- This regular provision of information to parents has been demonstrated to improve confidence in, and satisfaction with, neonatal units.
- NeoEPOCH will embed parent and public involvement in neonatal research at multiple levels. This is primarily to improve the quality of the research, but will also make research accountable, relevant and responsive, increasing accountability and trust in neonatal research and EHR data.
- We plan to demonstrate tangible benefits from the careful academic use of EHR data, and hope to improve public perceptions of "big health data" following recent negative publicity (care.data).
- Reducing the cost and burden of research aims to increase the number of neonatal units that participate in clinical trials. This should benefit patient care; research activity is associated with better clinical outcomes.

3. Neonatal health professionals
- The main medium term impact will be reduced uncertainty in clinical decision-making following large clinically driven PoCT.
- Health professionals will benefit from a research infrastructure that aligns research questions with clinical need.

4. Industry
- Integration of the neonatal EHR in research will benefit Clevermed, the commercial provider of the EHR platform (BadgerNet).
- The PoCT model, developed in collaboration with Clevermed, is readily scalable to other healthcare settings and other EHR platforms.
- Increasing the number of UK neonatal units participating in clinical trials will make the NHS more attractive for children's research, adding to the globally recognised excellence of the NIHR Children's Research Network (most global first recruits of any research network in 2012-13).
- The large trials that NeoEPOCH aims to facilitate are ideally suited for testing medical devices (such as ventilation strategies) or nutritional supplements (human milk fortifier) attracting commercial research and development into the NHS and the UK.

5. Policy makers within national government
- Exploring processes and experiences of other organisations implementing a "learning healthcare system" will inform and guide the development of such reorganisations in the UK.

6. Charities
- Involving Bliss and other charities will help them achieve their objectives, placing parents and patients at the heart neonatal research.
- In the medium to long-term, this will make neonatal research more responsive to charity priorities and provide them with tangible achievements, impacting their fund-raising capabilities.

7. The fellow and research staff
- Training, experience and recognition stemming from this fellowship will help me develop into a neonatal academic leader.
- The fellowship intends to train a research statistician to become an independent researcher and help to develop a National Neonatal Clinical Improvement Unit.