Adopting technology-enabled remote monitoring in the NHS: generating evidence that is fit for purpose

Co-authored by Stephanie Stockwell, Senior Analyst, RAND

Using technology to support remote patient monitoring has become a central part of discussions about the future of NHS care delivery. This involves the use of digital technologies to collect, transmit, and sometimes analyse patient data outside conventional clinical settings in ways that support ongoing care and clinical decision making over time. This could include patients on virtual wards submitting observations through apps or telephone-supported systems, or people with heart failure transmitting physiological data from home to clinical teams.

The attraction for the NHS is obvious. Technology-enabled remote monitoring promises earlier intervention, more proactive chronic disease management, care closer to home, better patient experience, potentially reduced pressure on overstretched services and more. There is significant policy and operational momentum behind it. But there is also a persistent problem. Many remote monitoring initiatives show promise in pilot form and then struggle to scale, spread or sustain in routine practice.

So the question increasingly facing the NHS is not simply: does remote monitoring work? But what kind of evidence helps us decide where, when, for whom and under what conditions it should be adopted?

In this blog we argue that evidence for technology-enabled remote monitoring needs to move beyond narrow assessments of technical performance or short-term outcomes. While these are important, adoption decisions in the NHS are rarely determined by technology alone. Many evaluations of remote monitoring have historically focused mainly on whether technologies ‘work’ under controlled conditions, while paying less attention to how they function in ‘real-world’ NHS settings. And yet adoption depends on how technologies interact with clinical workflows, workforce capacity, organisational priorities, patient capabilities, data infrastructures and models of care.

Generating evidence to support real world decision making about remote monitoring

Technology-enabled remote monitoring is fundamentally a socio-technical intervention (i.e. involving people, relationships and culture as well as machines, software and processes) and the way we generate and use evidence needs to reflect that. The challenge for evidence generation is therefore not simply establishing efficacy (i.e. the ability of a specific tech-enabled monitoring intervention to produce a beneficial effect under highly controlled conditions). It is generating evidence that supports real-world decision making. What we might think of as ‘traditional evaluation models’ are often poorly aligned with the realities of digital innovation in healthcare. Randomised controlled trials remain important for questions of safety and effectiveness, but they are often too slow and too fixed to keep pace with rapidly evolving technologies and service models. By the time findings emerge, the technology, the implementation context, and even the policy landscape have changed.

NHS organisations often need evidence within months not years. This is one reason why rapid evaluation approaches have become increasingly important. Rapid evaluation is an intensive, team-based approach designed to deliver actionable findings on programs or innovations quickly. It is about producing responsive, relevant, methodologically robust, and actionable evidence within useful timescales. Typically, this involves mixed-methods approaches delivered over weeks or months rather than years.

Using rapid evaluation to support adoption in the NHS

The National Institute for Health Research now funds five dedicated rapid evaluation centres, including the DECIDE Centre, a partnership across University of Oxford and RAND Europe, that focuses specifically on technology-enabled remote monitoring. For DECIDE, one important principle is treating remote monitoring not simply as a technology product, but as a service model. The relevant unit of analysis is the wider pathway of care into which monitoring is introduced. That means evaluations need to examine, not only devices or platforms, but also patient selection, escalation pathways, staffing, clinical governance, workflow integration and adaptation over time. This approach is reflected in the NASSS framework — Non-adoption, Abandonment, Scale-up, Spread and Sustainability — which was developed by the Oxford end of our team. It highlights that implementation success depends not only on the technology, but also on organisational readiness, the adopters involved, wider system factors, and the ability to adapt over time.

A focus on real-world adoption and spread, creates a strong case for mixed-methods evaluation of tech-enabled remote monitoring. Quantitative data are essential: admissions, readmissions, service utilisation, costs, mortality, patient-reported outcomes. But on their own, these findings rarely explain why implementation succeeds in one setting and struggles in another.

Qualitative methods are equally important for understanding the organisational and human dimensions of implementation. Examples come from rapid qualitative evaluations of home monitoring services that we’ve conducted in DECIDE - for COPD, heart failure and blood pressure monitoring. Using interviews with industry, policy, clinicians, managers and patients – combined with observation of real time use of remote patient monitoring and the work involved in designing, adopting and supporting it - these evaluations have all showed that success depends heavily on organisational integration rather than on the monitoring technologies alone. In some settings, clinicians described monitoring dashboards generating large volumes of alerts without sufficient workforce capacity to respond effectively. Elsewhere, uncertainty emerged around responsibility for escalation decisions between primary, community and secondary care teams – and across NHS and private providers. Patients and carers often valued reassurance and continuity, but some also found monitoring burdensome or anxiety-provoking.

Importantly, these tech-enabled services for COPD, heart failure and blood pressure monitoring were constantly evolving. Eligibility criteria, escalation thresholds, staffing arrangements and workflows changed in response to operational pressures. Rapid qualitative evaluation allowed those dynamics to be captured in real time, supporting adaptation and service improvement during implementation rather than years afterwards.

Quantitative and mixed-methods rapid evaluations are equally important. One example is evaluation of COVID-19 Oximetry@home pathways, which combined analysis of routine operational data with qualitative implementation research. This was undertaken by BRACE and RSET – two of the other rapid teams funded by NIHR - who explored outcomes such as admissions, escalation rates, mortality, and healthcare utilisation. But the mixed-methods design was critical because outcome data alone could not explain substantial variation between sites. Some services achieved strong engagement and effective escalation processes, while others struggled with fragmented workflows, low uptake, or difficulties integrating data into existing systems. Organisational readiness, staffing capacity, digital infrastructure, and local leadership all appeared to shape outcomes significantly.  An important lesson was that context is not secondary to implementation; it is central to it.

Implications: generating evidence that’s fit for purpose for the NHS

This all has important implications for how evidence should be generated in the NHS. First, evaluation needs to be embedded into implementation from the outset, not added retrospectively once services are established. Second, evidence needs to extend beyond narrow activity metrics to include workforce impact, patient experience, organisational consequences, equity, and sustainability. Third, remote monitoring should be evaluated as part of wider socio-technical systems rather than as isolated technologies. Fourth, evidence generation approaches need to match the pace and complexity of digital innovation itself. That means combining methodological rigour with approaches capable of producing timely and operationally relevant findings. Finally, evidence generation isn’t sufficient. While independence and rigour are essential to evaluation, - rapid or otherwise – relevance, responsiveness and relationships are also critical in ensuring translation of evidence into decision making into policy and practice, and equitable and improved care for patients.

Technology-enabled remote monitoring is unlikely to transform the NHS through technology alone. Its future depends on whether health systems can redesign pathways, develop sustainable workforce models, strengthen infrastructure and generate - and act on - evidence that genuinely supports informed adoption decisions in complex real-world settings. Rapid, socio-technical approaches to evaluation are important, and increasingly essential, for moving technology-enabled remote monitoring from promise to everyday practice across the NHS.