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NHS turns to AI to solve its ‘missed appointments’ problem

2023-02-27
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An NHS Trust is bringing in artificial intelligence (AI) software to predict potentially missed appointments and offer back-up bookings. But whether the software is accurate enough to help the health service cut waiting times remains to be proven, an expert told Tech Monitor.

NHA AI software on a laptop
Artificial intelligence is the NHS’ saviour for missed appointments. (Photo by Shutterstock)

The software, which has been developed by Deep Medical, will use algorithms and anonymised data to break down potential reasons why a patient might not attend an appointment. It will use a range of external insights such as the predicted weather, traffic and patients’ jobs. Based on the data, the appointment will be rearranged for the most convenient time for patients.

The NHS says that Deep Medical’s software will back-up bookings to ensure no clinical time is lost.

The system also implements intelligent back-up bookings to ensure no clinical time is lost, maximising efficiency.

It is being trialled by Mid and South Essex NHS Foundation Trust, which supports 1.2 million people. Its rate of ‘did not attend’ (DNA) appointments averages 8%. The national average is 6.7%.

New NHS AI push could save it billions

In January 2023, NHS England launched its drive to reduce an estimated 7.8 million missed hospital appointments per year, which equals a £1.2bn cost to the health service. Of the 122 million appointments booked in 2021/22, around 6.4% were missed – around 650,000 a month.

Missed appointments contribute to longer waiting lists. In January 2023, NHS England said that around four in five people are on an NHS waiting list for an outpatient appointment. Over three in five outpatient appointments are follow-ups.

According to NHS England, when at full scale the AI software could free up an additional 80,000-100,000 patients to be seen each year at Mid and South Essex. An additional five NHS Trusts are set to be tested this year. Tech Monitor contacted NHS England to confirm which trusts would be testing the software.

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Amanda Pritchard, NHS chief executive, said that the pilot shows that the f NHS is at the “forefront of innovation,” using the latest technologies to ensure patients have the best possible experience.

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“The system will help ensure patients receive ‘smart’ appointments, that are convenient and fit into people’s increasingly busy lives,” she said. “It is a win-win for patients and the NHS alike.” Pritchard added that smart appointments will help free up doctors to treat more patients, save taxpayers’ money as well as help to reduce waiting times.”

Bringing in AI isn’t about people ‘forgetting appointments’

Wider use of the technology could save the health service “hundreds of millions of pounds every year” according to Steve Barclay, health and social care secretary. Barclay said it would also “boost our efforts to cut waiting lists so patients can get the care they need more quickly.”

However, according to Deep Medical’s co-founder Dr Benyamin Deldar, the appointment of the AI software isn’t about people forgetting an appointment – it’s about challenging health inequalities.

“Whilst working on the frontline over Covid, I felt the impact of the pandemic on our services,” he explained. “We’ve created a system that can better identify and offer support for patients, whilst importantly tackling the NHS waiting list.”

Deldar is a member of the NHS Clinical Entrepreneur Programme (NHS CEP) – a development programme aimed at equipping NHS staff to develop commercial skills, knowledge and experience to help them digitally transform healthcare without leaving the national health service.

“Being a part of the NHS CEP has given me the framework and skills to scale innovations with purpose,” he said.

AI might predict missed appointments, but it can also get it wrong

This isn’t the first time technology has been used to solve the ‘missed appointments’ challenge. In 2019, University College Hospital, London, created an algorithm using records from 22,000 MRI scan appointments as part of a broader programme around machine learning in the NHS.

The algorithm identified 90% of patients who turned out to be a no-show. “On average we estimate this could save £2-3 per appointment,” Parashkev Nachev, UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery at UCLH, told the Guardian.

However, it also incorrectly flagged around 50% of patients who did attend their appointments as a risk of not doing so.

Sam Smith, who leads policy at independent organisation medConfidential, told Tech Monitor that while data could help with DNAs, hospitals will still require sufficient infrastructure to be able to communicate with their patients.

“We look forward to reproducibility to show if this AI is any more useful than astrology,” he said.

Read more: NHS brings in extra scrutiny for data platform due to Palantir concerns

Topics in this article : NHS England

参考译文
英国国民医疗服务体系求助人工智能来解决“错过预约”的问题
英国国家医疗服务体系信托基金正在引入人工智能软件,以预测可能错过的预约,并提供备用预约。但一位专家告诉《科技观察报》(Tech Monitor),该软件是否足够准确,能够帮助医疗服务机构缩短候诊时间,还有待证实。该软件由Deep Medical开发,将使用算法和匿名数据来分析患者可能不赴约的潜在原因。它将使用一系列外部信息,如预测天气、交通和病人的工作。根据数据,重新安排患者最方便的时间。NHS表示,Deep Medical的软件将备份预约,以确保不浪费临床时间。该系统还实现了智能备份预约,以确保没有临床时间的损失,最大限度地提高效率。目前,埃塞克斯中南部国民保健服务基金会正在进行试验,该基金会为120万人提供服务。它的“未参加”(DNA预约)率平均为8%。全国平均水平为6.7%。2023年1月,英格兰国民医疗服务体系启动了一项旨在减少每年约780万次错过医院预约的行动,这相当于卫生服务的12亿英镑成本。在2021/22年度预约的1.22亿次预约中,约6.4%被错过,每月约65万次。错过约会会导致等候名单变长。2023年1月,英国国民医疗服务体系表示,大约五分之四的人在国民医疗服务体系的门诊预约等候名单上。超过五分之三的门诊预约是随访。据英国国民医疗服务体系(NHS)称,当人工智能软件全面投入使用时,埃塞克斯中部和南部每年可以多收治8万至10万名患者。另外5个NHS信托基金将在今年接受测试。Tech Monitor联系了英国国家医疗服务体系,确认哪些信托机构将测试该软件。英国国民医疗服务体系首席执行官阿曼达·普里查德(Amanda Pritchard)表示,该试点表明,英国国民医疗服务体系处于“创新的前沿”,利用最新技术确保患者获得尽可能好的体验。她说:“该系统将有助于确保患者接受‘智能’预约,方便并适应人们日益繁忙的生活。”“这对患者和NHS都是双赢的。”普里查德补充说,智能预约将有助于腾出医生来治疗更多的病人,节省纳税人的钱,并有助于减少等待时间。英国卫生和社会保障大臣史蒂夫•巴克莱表示,更广泛地使用这项技术可以为医疗服务“每年节省数亿英镑”。巴克莱表示,这也将“促进我们减少等候名单的努力,以便患者能够更快地获得所需的治疗。”然而,Deep Medical的联合创始人本雅明·德尔达尔博士表示,预约人工智能软件并不是让人们忘记预约,而是为了挑战健康不平等。他解释说:“在抗击新冠疫情的第一线工作时,我感受到了疫情对我们服务的影响。”“我们已经创建了一个系统,可以更好地识别和为患者提供支持,同时重要的是解决NHS的等候名单。”Deldar是NHS临床企业家计划(NHS CEP)的成员,该发展计划旨在为NHS员工提供商业技能、知识和经验,帮助他们在不离开国家卫生服务的情况下实现医疗保健数字化转型。他说:“作为NHS CEP的一部分,我获得了有目的地扩大创新的框架和技能。”这并不是技术第一次被用来解决“错过约会”的挑战。2019年,伦敦大学学院医院使用2.2万次核磁共振扫描预约的记录创建了一种算法,这是NHS围绕机器学习的更广泛项目的一部分。 该算法识别出了90%的未来就诊的病人。伦敦大学学院皇后广场神经病学研究所和伦敦大学lh国立神经病学和神经外科医院的帕拉什科夫·纳乔夫告诉《卫报》:“平均来说,我们估计每次预约可以节省2-3英镑。”然而,它也错误地将大约50%的患者标记为没有赴约的风险。独立组织medConfidential的政策主管山姆·史密斯(Sam Smith)告诉Tech Monitor,虽然数据可以帮助处理dna,但医院仍然需要足够的基础设施来与患者沟通。他说:“我们期待重现性,以证明这种人工智能是否比占星术更有用。”
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