Department of Applied Health Research, University College London, UK.
Research and Policy, Nuffield Trust, London, UK.
Health Soc Care Deliv Res. 2023 Jul;11(13):1-151. doi: 10.3310/FVQW4410.
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.
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).
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).
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. 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 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.
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.
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.
This study is registered with the ISRCTN (14962466).
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 ; 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.
在大流行期间，为 COVID-19 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（例如体温），并在必要时进行升级。
评估英格兰在 COVID-19 大流行（第 1 波和第 2 波）期间 COVID-19 远程家庭监测服务的有效性、成本、实施情况以及工作人员和患者的体验（包括差异和模式）。
一项快速混合方法评估，分两个阶段进行。第 1 阶段（2020 年 7 月至 8 月）包括快速系统评价、实施和经济分析研究（在 8 个地点进行）。第 2 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、实施情况以及患者/工作人员的经验进行大规模、多地点、混合方法研究。
审查和实证研究的结果表明，这些服务已在全球范围内实施，并存在很大差异。实证研究结果表明，沟通、适当的信息和多种监测模式有助于实施；障碍包括转诊流程不明确、劳动力可用性和缺乏行政支持。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）的调查。我们对 58 名工作人员、62 名患者/护理人员和 5 名国家负责人进行了访谈。尽管进行了全国推广，但服务的注册人数低于预期（在被认为已完成数据的 37 个临床委员会评估组中，平均注册人数为 8.7%）。服务的实施存在很大差异，受患者（例如当地人口需求）、劳动力（例如工作量）、组织（例如协作）和资源（例如软件）因素的影响。我们发现，每增加 10%的入组人数，死亡率降低 2%（95%置信区间：死亡率降低 4%至增加 1%），入院人数增加 3%（-1%至 7%），住院死亡率下降 3%（-8%至 3%），住院时间增加 1.8%（-1.2%至 4.9%）。这些结果均无统计学意义。我们发现虚拟病房服务的住院时间稍长（调整后的发病率比为 1.05，95%置信区间为 1.01 至 1.09），并且对随后的 COVID-19 再入院没有统计学上的影响（调整后的优势比为 0.95，95%置信区间为 0.89 至 1.02）。低患者入组率和不完整的数据可能影响了可能存在的影响的检测机会。不同类型的服务和模式的每位患者的平均运行成本各不相同；并由员工数量和职级驱动。工作人员、患者和护理人员普遍对服务的体验表示满意。服务易于交付，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程度（例如，使用血氧计记录和提交读数）都会影响服务的交付。患者和护理人员感到服务和人际接触使他们感到安心，并很容易参与其中。参与的条件取决于患者、支持、资源和服务因素。许多站点根据当地人口的需求设计了服务。尽管进行了调整，但一些患者群体仍存在差异。例如，老年人和少数族裔患者报告说，他们在参与服务方面遇到了更多困难。支持技术的模型有助于管理大量的患者群体，但不能完全替代电话。
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、调查回复率低以及一些患者群体代表性不足。
进一步的研究应考虑这些服务的长期影响和成本效益，以及不同模型对不同患者群体的适宜性。
我们没有发现定量证据表明 COVID-19 远程家庭监测服务具有有效性。然而，低入组率、不完整的数据以及实施情况的差异降低了我们检测可能存在的任何影响的机会。尽管工作人员和患者对服务的看法积极，但应考虑到实施、交付和参与方面的障碍。
本研究在 ISRCTN 注册（14962466）。
该项目由英国国家卫生与保健优化研究所（NIHR）健康和社会保健交付研究计划（RSET：16/138/17；BRACE：16/138/31）和 NHSEI 资助，并将在《健康服务研究杂志》上全文发表；第 11 卷，第 13 期。请访问 NIHR 期刊图书馆网站以获取更多项目信息。本出版物中表达的观点是作者的观点，不一定代表国家卫生研究院或英国卫生部和社会关怀部的观点。
