Tech to save time: how the NHS can realise the benefits

Introduction

In recent years, increasing emphasis has been placed on the potential for technology to improve care and free up time for NHS staff. This has been a key focus of several health plans and reviews, including the 2019 NHS Long Term Plan, the productivity plan set out in the 2024 Spring Budget, the NHS Long Term Workforce Plan, the Darzi report and most recently the government’s planned shift from ‘analogue to digital’. However, the NHS has often encountered scenarios where technologies that appeared promising on paper fell short in practice. In particular, the failure of technology to increase productivity or free up time has been described in economic studies as the ‘productivity paradox’ and is well-documented in health care. Without more detailed attention on what is required to support digital transformation, the government’s proposed shift from analogue to digital risks remaining an ambition rather than a reality.

Over the last year, the Health Foundation has explored the potential of technology to save NHS staff time, examining which technologies offer the biggest time-saving opportunities and how clinicians would use time freed up by technology. In this new analysis, we investigate the challenges of using tech to free up time, including the reasons technology can have no or negative impact on staff time, and provide recommendations to better realise the benefits of health care technologies. Our findings challenge the assumption that the procurement of technology will automatically lead to benefits such as freeing up staff time. We argue that programmes must include a greater focus on implementation and optimisation to realise the benefits of technology.

What does the evidence tell us about the impact of different technologies on staff time?

The promise of technology to save time and resources in the NHS is compelling, especially for a system grappling with limited funding and an ever-growing demand for services. Yet introducing technologies into health care systems is often far from simple, and realising their benefits far from guaranteed. To explore this, we commissioned a rapid review of the evidence base on the impact of technology on staff time in health care, sampling 467 studies from between 2010 and 2023 that looked at whether a particular technology saved staff time (see Box 1). 

Figure 1 shows the proportion of the 467 studies analysed that found a positive impact on staff time versus no or negative impact for different categories of technology. (Though some of these categories, such as ‘telemedicine’, are quite broad, the review found that none of the technologies within a specific category were more likely to be associated with a negative impact on staff time than others.) 

A significant finding of this review is that the impact of each of these technologies on staff time is generally mixed (see Figure 1). Every technology, except for tracking/barcode scanning for drugs/tools, has some instances where it has saved staff time and others where it has failed to do so. This highlights that whether a technology generates time savings very much depends on how it is implemented and used – that is, how successfully it is embedded into practice and how effectively workflows and processes are redesigned to take advantage of the new functionalities it offers. 

For example, electronic health records could save staff time by centralising clinical information. However, in practice, records are often fragmented across services, wards and platforms and require multiple logins for access, which can negatively impact staff time. Of course, it is also possible a study might show a technology had no impact on staff time for methodological reasons, that is, because relevant data were not collected in a useful way. While some of the studies in this sample did have data collection issues, the review found that none failed to show a positive impact on staff time solely for data collection reasons; in all cases, other ‘real-world’ factors related to implementation and usage meant the technologies in question did not save staff time.

It should be noted that just because a technology had a negative impact or no impact on staff time does not imply it was unsuccessful overall. Technology might have a negative impact on staff time but still, for example, improve clinical outcomes, promote patient safety or enhance patient and/or staff experience. And these factors may ultimately have knock-on benefits for staff time and resource use. For example, robotic-assisted surgery may initially cost staff time as they undertake training, ensure it is properly integrated into practice and maintain the technology. But over time, increased surgical quality could shorten recovery time, reduce length of stay and reduce readmissions. Indeed, for a technology deployed primarily to improve care quality, having no impact on staff time could be viewed as a success (and would imply an increase in productivity). So whether or not a technology is judged as successful overall will depend on the range of reasons for introducing it. Nevertheless, for all studies included in this review, the impact on staff time was an outcome of interest.

Among different types of technology, there was considerable variation in the proportion of studies that found time savings – suggesting that some technologies may have more complex implementation challenges than others in relation to saving staff time. For example, while 85% of the 27 studies of computerised decision support showed time savings, only 52% of the 31 studies of robotic surgery showed time savings. As this review sampled a relatively small number of studies (467), the specific percentages shown in Figure 1 cannot be used to make broad generalisations about particular technologies. However, with a larger sample of studies, the type of data displayed here could be a useful metric of implementation complexity for different technologies. It is not hard to imagine, for example, that barcode scanning technologies may be less complex and less context-sensitive in their use than, say, surgical robots.

Why some technologies have no or negative impact on staff time

The review analysed in detail 144 studies where a technology was implemented with either no impact or a negative impact on staff time (including some with a mixed impact but conclusions of no or a negative impact overall). The most common reasons technologies had no or negative impact on staff time are listed in Figure 2. By far and away the two most common reasons were ‘staff needed to spend more time doing usual tasks’ and ‘staff needed to do extra tasks’, with each factor present in over half of the studies in question. As highlighted earlier, although several of the studies had data collection issues, the review showed that in no single study was this the only reason no impact on staff time was found. 

The reasons reported in Figure 2 highlight three important issues that can prevent technology from having a positive impact on staff time.

Workflow and task efficiency

Technology has the potential to increase the burden of time on staff through its impact on workflow – either due to a lack of proper integration or by lengthening existing tasks or adding new ones. Depending on the goal of a specific technology, this increased time may not ultimately be undesirable in terms of quality or safety. For example, in the case of robotic-assisted surgery, the increased burden on staff time related to training and maintenance may be justified in terms of increased surgery quality. However, in several studies included in the review, technology increased the time it took staff to do a task such as typing notes into an electronic form rather than writing them by hand. In others, a negative impact on staff time was due to the technology adding an extra step, such as printing 3D models to help plan surgery. Case study 1 highlights a UK study that found the use of technology created new work for staff. This can also happen when previous approaches are not retired or technologies are not integrated effectively into workflows, causing the duplication of activities. For example, a study on nurse workload highlighted how the large diversity of electronic systems used within and across care organisations and the lack of linkage between them results in the duplication of documentation activities for nurses, increasing workload. 

In relation to workflow, it should be noted that a limitation of many studies included in this review was a simplistic approach to recording time that would not have identified where time was saved and reused within a single task or episode of care. For example, if time saved in the taking of notes was then used to have a longer discussion with a patient, this may not have been recorded as a time saving, as consultation length remained the same. 

Studies may also not have picked up where time was saved for a different member of staff – something that has implications for multidisciplinary teams. For instance, a technology may not have saved time for a receptionist within a patient’s care episode but could have saved time for a GP, or vice versa. In other cases, time savings for one member of staff may have come at the expense of another. Further research is required to examine how time savings from the use of technology may accrue and be distributed across teams, providing a clearer picture of how efficiencies are shared and identifying potential areas for improved workflow integration. This could help ensure technologies have a positive impact on whole teams without inadvertently overburdening specific individuals.

Usability and skills 

The review found there were often challenges in using new technologies due to a lack of support to identify and resolve issues, or a lack of training to support staff in their effective use. As a result, many technologies were not effectively embedded into clinical practice. For example, in some studies, electronic health records systems were seen as challenging to navigate and not user-friendly, requiring significant training and often additional time to use effectively. One study examining nursing documentation and its relationship with perceived workload found that electronic health records had too many mandatory sections or headings not relevant to the patient that required navigation, costing nurses time. A lack of adequate training and support also often made it harder to use the technology efficiently. 

In case study 1, staff were left unable to troubleshoot issues, negatively impacting their capacity. Case study 2 highlights an example where staff were provided with training to resolve issues and were able to communicate easily with the technology provider, which minimised frustration and any additional burden on staff time. 

Issues with usability and skills may delay the effective use of a technology, as staff require time to overcome the initial learning curve. It is worth flagging here another potential limitation of the review: studies in the sample were often conducted shortly after implementation, without follow-up to assess whether the impacts of the technology shifted after processes were more familiar and embedded, potentially limiting insight into their long-term effectiveness. 

Buy-in and wider organisational context

Another set of factors underpinning why technologies had no or a negative impact on staff time related to the context in which they were implemented, including leadership, clinician and patient buy-in, and infrastructure and resourcing. This observation is in line with previous research suggesting that the impact of technology on staff time likely depends on the type of staff and patients using it and the organisational culture and context surrounding implementation. For example, a study on electronic health record implementation in 20 nursing homes in the US found that the optimal use of electronic health records was strongly linked with organisations having a management strategy that included leadership buy-in and staff empowerment. In particular, 1 in 10 studies that found negative or no impact on staff time identified clinician preferences or lack of buy-in as a factor. This highlights the importance of building consensus and involving staff in the design and implementation of change.

What to consider when using technology to free up staff time

This analysis demonstrates that the benefits of technology will only be realised if it is implemented and used effectively. Through highlighting some of the challenges that can prevent this, it also underscores important factors that contribute towards successful implementation: understanding patient preferences; customising the technology appropriately; training staff and patients in how to use the technology; considering how the technology fits into the workflow; redesigning processes and ways of working; building consensus and buy-in around new ways of working; trialling and honing these new arrangements in practice; and more.

These observations have important implications not only for those leading technology implementation but also for policymakers and system leaders aiming to support the rollout of new technologies and ensure the NHS realises their benefits – such as freeing up staff time. Here, we set out three key recommendations.

1. Successful implementation needs support – so fund the change, not just the tech

Programmes and initiatives aiming to achieve the adoption of technology at scale must widen their focus from procurement to effective implementation and use. Given the work involved in successful technology implementation, this needs to be supported as an integral part of the adoption process. Because many of the challenges involved are related to the specific context in which a technology is being implemented, these will need to be resolved locally, and support to do so directed at those leading implementation on the ground. For example, those adopting technology might need resources and capabilities for user engagement, process redesign, training and clinical backfill, evaluation and quality improvement. In supporting rollout, it is therefore important to fund the change – not just the tech. Often, the resources involved are relatively small but can make the difference between success and failure.

2. Successful implementation requires designing new uses of technology in consultation with staff and patients – avoid a one-size-fits-all approach

By engaging staff and patients as partners in the development, deployment and optimisation of technologies, the NHS can create context-sensitive solutions that are more likely to succeed. Engagement can also play a pivotal role in ensuring patient safety and enhancing the quality of care. In relation to freeing up staff time, many of the challenges highlighted earlier that prevented technologies from having a positive impact on staff time need to involve staff to overcome them, such as the challenges of creating buy-in, workflow redesign, improving usability, skill development and so on. This involvement can also build trust in technologies, as staff will be more confident in using tools they helped develop and deploy. Crucially, this means effective implementation processes require consultation with staff and patients as well as the flexibility to incorporate and respond to their needs and preferences throughout. Programmes focusing on the adoption of technologies will need to allow for locally tailored solutions – a one-size-fits-all blueprint will rarely be the right approach.

3. Realising the benefits can take time – give greater priority to the optimisation of existing technologies

Technologies often promise productivity benefits, yet these are seldom realised immediately. Given that new skills may have to be learned and new ways of working evolved, a significant lag is common between the introduction of new a technology and demonstrable results. For example, in a recent Health Foundation survey clinical staff named electronic health records as one of the technologies most likely to deliver time savings over the next 5 years and expressed frustration that they are not yet being used effectively or to their full potential. This has some important implications. First, technology programmes must be based on realistic timescales, with a distinction between the acquisition and initial embedding of a technology and the productive use of it. Second, and perhaps more optimistically, there will be a range of technologies already in place in the NHS that are not yet being used to their full productive potential. A greater focus on optimising these could generate near-term productivity gains. For example, as more than 90% of NHS trusts now have electronic health records, attention can shift towards realising their longer term potential, such as through adding wider datasets or integrating machine learning to enable risk prediction or decision support. Other recently introduced uses of technology such as video consultations, virtual wards and AI image analysis will likely also offer gains from further optimisation. 

Conclusion: How can we realise the potential for technology to release time to care?

With the NHS experiencing unprecedented levels of demand, high bed occupancy and long treatment backlogs, there is a real urgency to realise the benefits of technology in order to improve productivity. As highlighted in The Strategy Unit's recent report, Digital Downsides, ‘a hunger for solutions within resource-starved services creates ideal conditions for digital enthusiasm’. But it is important this enthusiasm comes with a dose of realism about the challenges involved, particularly with regard to saving staff time. As this analysis has shown, there are many instances where technologies have failed to have a positive impact on staff time due to problems with implementation and use. 

Looking ahead, the NHS 10-Year Health Plan provides an opportunity to improve on many previous technology programmes by challenging the assumption that the procurement of new cutting-edge technologies will automatically unlock staff time and improve patient care. Instead, an approach to supporting the rollout of health technologies should be put in place that better aligns with what we know about the real-world challenges involved in realising their benefits. 

For a complete list of the studies included in the evidence review, please contact Ben Shemesh, Senior Improvement Analyst, The Health Foundation at ben.shemesh@health.org.uk.