Automated, intelligent oral contraception prescribing via telemedicine - using AI to improve patient health outcomes and streamline time-intensive assessment processes, exacerbated by COVID-19

通过远程医疗自动、智能地开具口服避孕药 - 使用人工智能改善患者健康结果并简化因 COVID-19 而加剧的耗时评估流程

• 批准号: 86077
• 金额: $ 41.44万
• 依托单位: UNIQ HEALTH LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=86077
• 关键词: Automated; intelligent; oral; contraception; prescribing

Covid 19 has validated and compounded the need for improved efficiencies (identified within the NHS Long Term plan) via the urgent introduction of automation and the utilisation of Telemedicine where feasible to reduce strain on resources, especially with the prospect of a second wave/future spikes on the horizon.The ongoing impact of Covid-19 meant over 45% of non-urgent appointments were either cancelled or postponed, leaving GP's with significant backlogs. Contraception and prescription of Oral Contraceptives (OC) is the second most common reason to visit a GP (UK), accounting for more than 20m appointments/annum, equivalent to 13,900 days and is classed as "non-urgent."This has been further compounded by the closure of 54% of Sexual Health Clinics, often utilised by young females for contraceptive consultations, leaving many unsupported.Intelligent, automated technology, as identified in the NHS Long-Term/NIHR post-Covid strategies, can help in this regard in particular when combined with recently curated large female health datasets on hormonal profiles. Reducing demand on GP clinics whilst improving the prescribing process by ensuring optimum available medication is prescribed first time (52% of users suffer side-effects on the first prescribed medication, on average resulting in 2 further consultations to manage adverse side-effects and determine optimum medication).Building upon our CE-Marked hormonal health platform and prototype TRL5 patient stratification algorithms, we intend to develop and trail (alongside NHS partner CNWL NHS Trust) a new Telemedicine platform for female contraceptive treatments that will;* Automate the consultation and triage process* Intelligently/accurately select the optimum available OC via patient stratification (utilising advanced algorithms) that considers a woman's unique hormone profile* Ongoing remote outreach and monitoring by our digital support hub-\> earlier detection of side-effects, mitigation through counselling/coaching /medication changes where warranted.**Impact**The project addresses both a long-term inefficiency in the current prescribing method, as well as addresses the immediate impact of COVID-19 on GPs/Primary Care. The technology will explicitly;1. Remove the need for a GP in 70% of all cases via remote triage: saving ~9730 GP-days/annum.2. Improve the triage process for remaining 30% of complex cases via our CE-Marked knowledge base for GPs.3. Improve the accuracy of medication prescription through AI-assisted patient stratification, reducing re-consultations by ~60%.4. Enable remote prescribing via our partners Pharmacy2U&Mayberry\_Pharmacy5. Help reduce the ~£1.9Bn cost to the NHS of hormonal medication related side-effects(NHS:2019)6. Improve patient care and proactive management through digital outreach and interaction.7. Can be rolled out nationally, at scale, quickly.

Covid-19 已经验证并加剧了提高效率的需求（在 NHS 长期计划中确定），即通过紧急引入自动化和在可行的情况下使用远程医疗来减少资源压力，特别是在第二波/未来高峰即将出现的情况下。Covid-19 的持续影响意味着超过 45% 的非紧急预约被取消或推迟，这给全科医生留下了巨大的负担。 积压。避孕和口服避孕药 (OC) 处方是去看全科医生的第二大常见原因（英国），每年有超过 2000 万次预约，相当于 13,900 天，被归类为“非紧急”。54% 的性健康诊所关闭，这进一步加剧了这一情况，这些诊所经常被年轻女性用来进行避孕咨询，导致许多诊所得不到支持。 NHS 长期/NIHR 后新冠战略中确定的自动化技术可以在这方面提供帮助，特别是与最近整理的有关荷尔蒙概况的大型女性健康数据集相结合时。通过确保首次开具最佳可用药物，减少对全科医生诊所的需求，同时改进处方流程（52% 的用户在第一次开处方药物时出现副作用，平均需要 2 次进一步咨询来管理不良副作用并确定最佳药物）。基于我们的 CE 标志激素健康平台和原型 TRL5 患者分层算法，我们打算开发和 Trail（与 NHS 合作伙伴 CNWL NHS Trust 一起）为女性避孕治疗提供了一个新的远程医疗平台，该平台将：* 自动化咨询和分诊过程* 通过患者分层（利用先进算法）智能/准确地选择最佳的可用 OC，考虑女性独特的激素特征* 通过我们的数字支持中心进行持续的远程外展和监控 -\> 及早检测副作用， 在必要时通过咨询/指导/药物改变来缓解。**影响**该项目既解决了当前处方方法的长期低效问题，又解决了 COVID-19 对全科医生/初级保健的直接影响。该技术将明确；1．通过远程分诊，70% 的病例不再需要全科医生：每年节省约 9730 个全科医生天。2。通过我们的全科医生 CE 标志知识库改进剩余 30% 复杂病例的分诊流程。3。通过AI辅助患者分层，提高用药处方的准确性，减少约60%的复诊次数。4.通过我们的合作伙伴 Pharmacy2U&Mayberry\_Pharmacy5 启用远程处方。帮助减少 NHS 因激素药物相关副作用而花费约 19 亿英镑的费用 (NHS:2019)6。通过数字化推广和互动改善患者护理和主动管理。7.可以在全国范围内快速推广。