A rapid mixed-methods evaluation of remote home monitoring models during the COVID-19 pandemic in England.

Naomi J Fulop, Holly Walton, Nadia Crellin, Theo Georghiou, Lauren Herlitz, Ian Litchfield, Efthalia Massou, Chris Sherlaw-Johnson, Manbinder Sidhu, Sonila M Tomini, Cecilia Vindrola-Padros, Jo Ellins, Stephen Morris, Pei Li Ng
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Patients monitored blood oxygen saturation and other readings (e.g. temperature) at home and were escalated as necessary.</p><p><strong>Objective: </strong>To evaluate effectiveness, costs, implementation, and staff and patient experiences (including disparities and mode) of COVID-19 remote home monitoring services in England during the COVID-19 pandemic (waves 1 and 2).</p><p><strong>Methods: </strong>A rapid mixed-methods evaluation, conducted in two phases. Phase 1 (July-August 2020) comprised a rapid systematic review, implementation and economic analysis study (in eight sites). Phase 2 (January-June 2021) comprised a large-scale, multisite, mixed-methods study of effectiveness, costs, implementation and patient/staff experience, using national data sets, surveys (28 sites) and interviews (17 sites).</p><p><strong>Results: </strong><i>Phase 1</i> Findings from the review and empirical study indicated that these services have been implemented worldwide and vary substantially. 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Abstract

Background: Remote home monitoring services were developed and implemented for patients with COVID-19 during the pandemic. Patients monitored blood oxygen saturation and other readings (e.g. temperature) at home and were escalated as necessary.

Objective: To evaluate effectiveness, costs, implementation, and staff and patient experiences (including disparities and mode) of COVID-19 remote home monitoring services in England during the COVID-19 pandemic (waves 1 and 2).

Methods: A rapid mixed-methods evaluation, conducted in two phases. Phase 1 (July-August 2020) comprised a rapid systematic review, implementation and economic analysis study (in eight sites). Phase 2 (January-June 2021) comprised a large-scale, multisite, mixed-methods study of effectiveness, costs, implementation and patient/staff experience, using national data sets, surveys (28 sites) and interviews (17 sites).

Results: Phase 1 Findings from the review and empirical study indicated that these services have been implemented worldwide and vary substantially. Empirical findings highlighted that communication, appropriate information and multiple modes of monitoring facilitated implementation; barriers included unclear referral processes, workforce availability and lack of administrative support. Phase 2 We received surveys from 292 staff (39% response rate) and 1069 patients/carers (18% response rate). We conducted interviews with 58 staff, 62 patients/carers and 5 national leads. Despite national roll-out, enrolment to services was lower than expected (average enrolment across 37 clinical commissioning groups judged to have completed data was 8.7%). There was large variability in implementation of services, influenced by patient (e.g. local population needs), workforce (e.g. workload), organisational (e.g. collaboration) and resource (e.g. software) factors. We found that for every 10% increase in enrolment to the programme, mortality was reduced by 2% (95% confidence interval: 4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1.8% (-1.2% to 4.9%). None of these results are statistically significant. We found slightly longer hospital lengths of stay associated with virtual ward services (adjusted incidence rate ratio 1.05, 95% confidence interval 1.01 to 1.09), and no statistically significant impact on subsequent COVID-19 readmissions (adjusted odds ratio 0.95, 95% confidence interval 0.89 to 1.02). Low patient enrolment rates and incomplete data may have affected chances of detecting possible impact. The mean running cost per patient varied for different types of service and mode; and was driven by the number and grade of staff. Staff, patients and carers generally reported positive experiences of services. Services were easy to deliver but staff needed additional training. Staff knowledge/confidence, NHS resources/workload, dynamics between multidisciplinary team members and patients' engagement with the service (e.g. using the oximeter to record and submit readings) influenced delivery. Patients and carers felt services and human contact received reassured them and were easy to engage with. Engagement was conditional on patient, support, resource and service factors. Many sites designed services to suit the needs of their local population. Despite adaptations, disparities were reported across some patient groups. For example, older adults and patients from ethnic minorities reported more difficulties engaging with the service. Tech-enabled models helped to manage large patient groups but did not completely replace phone calls.

Limitations: Limitations included data completeness, inability to link data on service use to outcomes at a patient level, low survey response rates and under-representation of some patient groups.

Future work: Further research should consider the long-term impact and cost-effectiveness of these services and the appropriateness of different models for different groups of patients.

Conclusions: We were not able to find quantitative evidence that COVID-19 remote home monitoring services have been effective. However, low enrolment rates, incomplete data and varied implementation reduced our chances of detecting any impact that may have existed. While services were viewed positively by staff and patients, barriers to implementation, delivery and engagement should be considered.

Study registration: This study is registered with the ISRCTN (14962466).

Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (RSET: 16/138/17; BRACE: 16/138/31) and NHSEI and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. 13. See the NIHR Journals Library website for further project information. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health and Care Research or the Department of Health and Social Care.

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新冠肺炎大流行期间英格兰远程家庭监测模型的快速混合方法评估。
背景:在大流行期间,为新冠肺炎患者开发并实施了远程家庭监测服务。患者在家中监测血氧饱和度和其他读数(如温度),并在必要时进行升级。目的:评估新冠肺炎大流行期间(第1波和第2波)新冠肺炎远程家庭监测服务在英格兰的有效性、成本、实施以及工作人员和患者体验(包括差异和模式)。方法:分两个阶段进行快速混合方法评估。第一阶段(2020年7月至8月)包括快速系统审查、实施和经济分析研究(在八个地点)。第二阶段(2021年1月至6月)包括使用国家数据集、调查(28个地点)和访谈(17个地点)对有效性、成本、实施和患者/工作人员体验进行的大规模、多地点、混合方法研究。结果:第一阶段的审查和实证研究结果表明,这些服务已在全球范围内实施,差异很大。经验调查结果强调,沟通、适当信息和多种监测模式有助于执行;障碍包括转介程序不明确、劳动力可用性以及缺乏行政支持。第2阶段我们收到了292名工作人员(39%的回复率)和1069名患者/护理人员(18%的回复率。我们采访了58名工作人员、62名患者/护理人员和5名国家负责人。尽管在全国范围内开展了服务,但服务的注册率低于预期(37个临床调试组的平均注册率被判断为已完成数据,为8.7%)。受患者(如当地人口需求)、劳动力(如工作量)、组织(如协作)和资源(如软件)因素的影响,服务的实施存在很大差异。我们发现,该项目的注册人数每增加10%,死亡率就会降低2%(95%置信区间:从4%降低到1%增加),入院人数会增加3%(-1%-7%),住院死亡率会下降3%(-8%-3%),住院时间会增加1.8%(-1.2%到4.9%)。这些结果都没有统计学意义。我们发现,与虚拟病房服务相关的住院时间略长(调整后的发病率比率为1.05、95%置信区间为1.01至1.09),对随后的新冠肺炎再入院没有统计学上的显著影响(调整后的比值比为0.95,95%置信区间为0.89至1.02)。低患者登记率和不完整的数据可能影响了检测可能影响的机会。每位患者的平均运行成本因不同类型的服务和模式而异;并受到工作人员数量和级别的推动。工作人员、患者和护理人员普遍报告了积极的服务体验。服务很容易提供,但工作人员需要额外的培训。工作人员的知识/信心、NHS资源/工作量、多学科团队成员之间的动态以及患者对服务的参与(例如使用血氧计记录和提交读数)影响了交付。患者和护理人员觉得所得到的服务和人际接触让他们放心,而且很容易参与。参与取决于患者、支持、资源和服务因素。许多网站设计服务以满足当地居民的需求。尽管有适应,但据报道,一些患者群体之间存在差异。例如,老年人和少数民族患者报告说,在参与服务方面遇到了更多困难。技术支持的模型有助于管理大型患者群体,但并没有完全取代电话。局限性:局限性包括数据完整性、无法将服务使用数据与患者层面的结果联系起来、调查响应率低以及一些患者群体的代表性不足。未来的工作:进一步的研究应该考虑这些服务的长期影响和成本效益,以及不同模式对不同患者群体的适用性。结论:我们无法找到新冠肺炎远程家庭监测服务有效的定量证据。然而,低入学率、不完整的数据和多样化的实施减少了我们发现任何可能存在的影响的机会。虽然工作人员和患者对服务持积极态度,但应考虑到实施、提供和参与方面的障碍。研究注册:本研究在ISRCTN(14962466)注册。资助:该项目由国家卫生与护理研究所(NIHR)卫生与社会护理提供研究计划(RSET:16/138/17;BRACE:16/138/31)和NHSEI资助,并将在《卫生与社会保健提供研究》上全文发表;第11卷第13期。有关更多项目信息,请访问NIHR期刊图书馆网站。 本出版物中表达的观点是作者的观点,不一定是国家卫生和护理研究所或卫生和社会护理部的观点。
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