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

NeoEPOCH：新生儿电子健康记录数据，用于护理点健康研究和新生儿护理的持续增量改进

• 批准号: MR/N008405/1
• 负责人: Chris Gale
• 金额: $ 129.96万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FN008405%2F1
• 关键词: NeoEPOCH; Neonatal; Electronic; health; record

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 by1. 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 accurate3. 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 anotherWe 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 by1. 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 home2. 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 PoCTThirdly, 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.

英国每11个婴儿中就有一个是早产的；其中许多婴儿需要新生儿护理，涉及到婴儿护理的每一个部分的医疗决定(比如如何最好地支持呼吸)。许多需要新生儿护理的婴儿都有影响他们一生的医疗和神经问题；这些问题可能会受到他们在新生儿逗留期间所做决定的影响。确定哪种临床决策(即使用哪种呼吸支持)是最好的理想方法是随机试验。在这里，每个婴儿都有平等的机会得到每一个决定(呼吸支持的类型)，这是随机选择的，就像扔硬币一样。通过纳入大量的婴儿，我们可以确定哪种呼吸支持效果最好。不幸的是，随机试验非常昂贵和繁重，因为收集所有信息都很耗时。因此，只有一小部分新生儿的临床决定在随机试验中进行了测试，因此大多数决定只是有根据的猜测。我想让随机临床试验更便宜、更容易，这样所有日常新生儿的决定都可以基于最好的研究--随机临床试验。我计划通过去掉最昂贵的部分，数据收集来做到这一点。目前，这是通过付钱给研究人员检查每个婴儿的医疗记录来完成的。我想直接从婴儿的电子健康记录(EHR)中获得所有信息，EHR是医疗记录的计算机版本。自2007年以来，所有英国新生儿病房都使用了一个电子健康记录系统。国家新生儿研究数据库(NNRD)保存着来自该EHR的关于所有入院接受新生儿护理的婴儿的信息(删除了姓名和其他识别信息)。NNRD已经被用于其他目的，我想将其用于随机试验，以使它们更便宜、更容易。这些可以被称为关注点试验(PoCT)。有许多问题需要解决。首先，电子病历中的信息可能并不完全准确。我们将在1之前处理这个问题。看看其他电子健康记录系统，找出衡量和报告新生儿电子健康记录准确性的最佳方法2。看看其他人是如何使电子健康记录数据更准确的3。使用这些技术，并使用整群随机对照试验进行测量，以确定它们是否有效；这就像一个更大的随机临床试验，但每个新生儿单元将有同样的机会获得一种或另一种技术，而不是每个婴儿都有平等的机会做出一项或另一项决定。我们认为，如果父母更多地参与婴儿的EHR数据，就会更准确。我们将通过请求父母帮助我们帮助他们使用婴儿的EHR数据来测试这一点。然后，我们将在同一组随机试验中尝试这一点，看看它是否会使EHR更准确。我们认为，采取这些步骤将使EHR足够准确地用于PoCT，但我们也将从数学上解决如何使用EHR数据，即使它不完全准确。第二，我们希望确保POCT将以正确的方式提出正确的研究问题。我们将在1号之前完成这项工作。询问感兴趣的团体(医生、护士、家长、病人等)他们认为POCT最重要的“结果”是什么。“结果”是一项试验的结果，比如婴儿在家中是否需要氧气。问同样的小组，在PoCT中测试最重要的临床决策是什么(比如如何支持婴儿的呼吸或用什么牛奶喂养)。第三，我们想要展示我们可以使用新生儿EHR进行PoCT。为了做到这一点，我们将在20个新生儿单元和一年内运行一个小型PoCT。我们将衡量它的准确性，以及它是否更容易和更便宜。最后，我们希望确保PoCT的知识可以在NHS中快速有效地传播，以改善照顾婴儿的方式，这样我们将从另一个已经做到这一点的医疗系统的成功和错误中吸取教训。

项目成果

Study protocol: optimising newborn nutrition during and after neonatal therapeutic hypothermia in the United Kingdom: observational study of routinely collected data using propensity matching.

• DOI: 10.1136/bmjopen-2018-026739
• 发表时间: 2018-10-23
• 期刊: BMJ open
• 影响因子: 2.9
• 作者: Battersby C;Longford N;Patel M;Selby E;Ojha S;Dorling J;Gale C
• 通讯作者: Gale C

COVID-19 in children: what did we learn from the first wave?

• DOI: 10.1016/j.paed.2020.09.005
• 发表时间: 2020-12
• 期刊: Paediatrics and child health
• 影响因子: 1.9
• 作者: Bogiatzopoulou A;Mayberry H;Hawcutt DB;Whittaker E;Munro A;Roland D;Simba J;Gale C;Felsenstein S;Abrams E;Jones CB;Lewins I;Rodriguez-Martinez CR;Fernandes RM;Stilwell PA;Swann O;Bhopal S;Sinha I;Harwood R
• 通讯作者: Harwood R

Kernicterus in neonates from ethnic minorities in the UK.

英国少数民族新生儿的核黄疸。

• DOI: 10.1136/archdischild-2022-324642
• 发表时间: 2023
• 期刊: Archives of disease in childhood. Fetal and neonatal edition
• 作者: Baskaran D