The challenges of the COVID-19 pandemic have impacted nursing practice. One major impact has been the change from face-to-face consultations to an increasing number of virtual appointments (Murphy et al, 2021). In addition, in England, it is estimated that the NHS needs to see an additional 500 000 patients a year for the next 4 years to clear the backlog of patients and meet its 18-week standard for attendance of newly referred patients (Gardner et al, 2020). There has been an unprecedented shift towards the use of technology to provide care and information, for example, primary care services frequently offer virtual appointments and remote consultations via telephone, video calls and text messages and e-prescription services (Hutchings, 2020). During the COVID-19 pandemic it was estimated that up to 46% of nurse consultations were delivered remotely, based on data from April 2020 (Murphy et al, 2021).
Internally, healthcare providers introduced software products, such as video conferencing software, to support remote working. The use of such products by a variety of different companies increased by 775% between 2019 and 2020 to enable digital collaboration and communication (Sams, 2020). Video conferencing has been used increasingly by nurses, including for sensitive clinical processes such as facilitating communication between family members and dying relatives during the COVID-19 pandemic (Billingsley, 2020).
There has been a 912% increase in the uptake of the NHS App, introduced in 2019, from 192 676 users in December 2019 to 1 951 640 users in December 2020 (NHS Digital, 2020). The government aim is for 75% of the adult population in England to have an NHS App account by 2024 (House of Commons Health and Social Care Committee, 2023). The NHS App is a digital tool that allows users (who must to be registered with a GP in England) to seek advice, book appointments and review their health records, with the more recent addition of also holding an individual's Covid Pass.
The future of healthcare provision, and therefore nursing practice, is inevitability associated with technology and digitalisation. As such, it is essential for nurses to attain digital competence to adapt to technological advances, especially where they inform safe and effective patient care according to regulatory frameworks.
Digital health: a myriad of terms and technical solutions
Digital health is rooted in electronic health (e-health) and the two concepts are often used interchangeably. In his early work, Eysenbach (2001) defined e-health as an:
‘Emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies.’
There are many potential benefits of e-health according to Eysenbach (2001), including increased efficiency, improved quality of care and empowerment of patients. Improved access to health services and greater information exchange have also been proposed as potential benefits. Nonetheless, these benefits have yet to be fully realised, largely because of digital inequality and poor integration of digital systems in many healthcare systems (World Health Organization (WHO), 2021).
Over the years, a multitude of terms have been used to describe the application of technology in health, including ‘telemedicine’, ‘health information technology (IT)’, ‘e-health’ and ‘m-health’. As the technology evolved with artificial intelligence, big data (data sets that are too large or complex to be dealt with by traditional data-processing application software) and immersive technologies, the term ‘digital health’ emerged.
WHO defined digital health as the adoption of information and communications technology to support health and social care (WHO, 2021). A comprehensive overview of digital health was captured in a recent scoping review by Nazeha et al (2020). The authors analysed digital health definitions and identified three distinct yet convergent uses, including technology used for:
- Monitoring, tracking and providing information about health (such as mobile devices, mobile sensors and wearables (such as a smartwatch), apps and social media)
- Health communication among stakeholders (such as telehealth, telemedicine and virtual consultations); and storing, managing
- Recording and using health data (such as electronic medical records, electronic medication systems and electronic prescribing (e-prescribing)) (Nazeha et al, 2020).
There are many applications of these digital health concepts in nursing practice, as explained in the sections below.
Digital health concepts in nursing practice
Telehealth and telemedicine offer digital solutions to treat patients remotely. Applications include out-of-hours telephone services, videoconferencing case discussions and virtual clinics (Kidd et al, 2010; Gilbert et al, 2020). During the pandemic, telehealth facilitated continuity of care by allowing people to communicate with health providers (Andrews et al, 2020). Evidence indicates that telehealth is affordable, usable, effective and improves care provision (Kruse et al, 2017; Monaghesh and Hajizadeh, 2020). A review by Kruse et al (2017) noted that access to health care can be improved by telehealth modalities and is associated with reductions in the number of missed appointments and improvements in medication adherence. Nevertheless, it is important to note that studies in this review highlighted variations in the patient-reported benefits depending on the age of patients. Patients who are older are less likely to report the same benefits as younger patients (Kruse et al, 2017).
The electronic health record (EHR), sometimes called the electronic patient record (EPR), is another example of a digital health concept applied in nursing practice. These systems store information about the care received by individuals who access NHS services (Jacob, 2020). The EHR/EPR system can also collate data from different healthcare organisations, which generates big data that can be used to train artificial intelligence programmes and conduct research to improve the quality and efficiency of care. Steps toward achieving this have already been made in the healthcare systems of Israel and China (Britnell, 2019). In the UK, the Greater Manchester Care Record (Health Innovation Manchester, 2023) combines patient data from local health and social care providers to allow professionals to meet patients' needs more effectively. The use of EHRs often results in benefits including improvements in the quality and efficiency of care at a national scale, particularly in relation to public health for disease surveillance (Kruse et al, 2018).
However, accessibility and usability (ease of use, access, intuitive processes, design) remain a challenge with EHR systems. A large study by Bloom et al (2021) indicated a lack of usability (ease of use of a product to perform its intended purpose) in many EHR systems, and that more simplicity is necessary. Notably, Bloom et al (2021) reported that none of the 15 emergency department EHR systems they evaluated met the standard of usability considered acceptable. This, arguably, highlights a need for greater involvement of clinical staff, including nurses, during the development, implementation and evaluation of these products.
E-prescribing systems enable healthcare providers to send prescriptions digitally to a dispenser (such as a hospital pharmacy department). A recent review on the effectiveness of e-prescribing for improving the safety of medicines administration highlighted the potential benefits of these systems (Gates et al, 2021), such as significantly reduced rates of medication errors. However, the authors also reported that there is still insufficient evidence indicating how effective these systems are for preventing serious harm to patients. Contrary to the Gates et al (2021) study, increases in medication-related harms were reported in a study by Slight et al (2019) when e-prescribing systems were used – specifically dose and medicine reconciliation errors. This highlights the potential for e-iatrogenesis (patient harm caused by the application of health technology) when these systems are used.
Moreover, an earlier study by Davies et al (2017), investigating the impact of e-prescribing systems on staff perceptions of safety in a hospital in England, reported a reduction in perceived safety when using the system. The authors concluded that poor implementation strategies and poor staff competence may have been responsible for the poor perceptions of e-prescribing technology. Recent studies (Mohsin-Shaikh et al, 2014; Lee et al, 2015) reported increased safety and communication among health professionals. However, these studies also reported that log-in times prolong medicines administration processes and put pressure on nurses' time.
The evidence indicates that e-prescribing has the potential to prevent medication errors when used correctly. However, without adequate digital skills' development for nurses and a well-considered implementation plan, the benefits of this technology may be diminished. Nurses should carefully consider their current and potential future use of digital systems and reflect on personal and development needs in relation to the use of digital systems to support nursing processes. This will lead to potential service improvements as they could pursue improving the safety of these systems.
Mobile health (m-health) is expected to lead to a ‘mobile health revolution’ given that smartphones are accessible, portable, and, increasingly, more affordable (Lucivero and Jongsma, 2018). M-health has been adopted across clinical practice and includes wearables, apps and messaging systems to offer wellbeing programmes and tools for patients with long-term conditions to self-manage their illness. M-health is expected to play a key role in the prevention, monitoring and management of health conditions and has shown huge potential in many clinical contexts, particularly in cases where camera technology is useful. For example, the SkinVision app was demonstrably able to detect skin cancers using camera technology, although more evaluations of this technology are required before it could replace expert clinician judgement (Freeman et al, 2020). Studies have also demonstrated the ability of mobile apps to assist in the assessment and documentation of wounds (Shamloul et al, 2019), an area of clinical practice that is currently predominantly provided by nurses in the UK (Guest et al, 2020).
M-health applications are purported to increase access to health information and monitoring and provide better access to services and management of long-term conditions (Marcolino et al, 2018). For example, text messages contributed to better self-management of diabetes in two studies where participants were sent reminders about aspects of their daily diabetes care. Participants reported that daily reminders helped them to comply with treatment regimens, check their feet for wounds and attend arranged appointments (Dick et al, 2011; Shetty et al, 2011).
Apps can also link with wearable sensors that connect to the internet, to transmit and analyse data. These can then present the user (wearers) with graphs and statistics that can be used to monitor health indicators or change behaviour. The use of wearable sensors has increased rapidly during the COVID-19 pandemic for the purpose of remote monitoring of patients to identify deteriorating patients rapidly without requiring long inpatient stays and observation by trained nurses (Seshadri et al, 2020).
Despite the expected benefits, the technology might not reach those without adequate health and digital literacy and who face language barriers, thereby excluding certain groups (such as those on low incomes and elderly people) (NHS Digital, 2021). New approaches to nursing assessment are needed, which consider the digital capability of patients and what this may mean for their ability to access or engage with opportunities offered by digital systems such as m-health.
Extended reality (XR) (sometimes known as cross reality) is an umbrella term for technologies that alter reality using digital elements and includes augmented reality, virtual reality and mixed reality. Augmented reality superimposes computer-generated sensory information on to a user's experience of real-world locations, and so can enhance those locations with contextual information (including video, audio, animated 3D graphics and real-time social networking) (Eckert et al, 2019). Its applications can be found in medical training in laparoscopy, surgery, and medical visualisation (Barsom et al, 2016) and evidence of its use in nursing education and clinical settings is starting to emerge (Wüller et al, 2019).
The dissemination of augmented reality technology and applications has been limited by technical constraints and limited sensing of the surrounding environment (Eckert et al, 2019). However, recent technical developments such as machine learning are set to significantly change the potential usefulness, acceptability and accessibility of augmented reality.
Mixed reality technology is similar to augmented reality, but rather than the digital elements being used as a layer over reality, they can interact with physical elements, therefore providing a greater degree of interactivity.
Virtual reality is an immersive environment where computeraided stimuli create the illusion of being somewhere else (Pottle, 2019). Virtual reality can be displayed with a variety of tools, including computer or mobile device screens, and virtual reality rooms of head-mounted displays (such as Google Cardboard). Virtual reality, in contrast to augmented reality, creates a new world (the user is immersed in a virtual world). Virtual reality has been used more widely in health care, especially in education (Gelmini et al, 2021; Woon et al, 2021). A systematic review of virtual reality in nursing education indicated that it could improve student knowledge (Woon et al, 2021). Furthermore, virtual reality has been used for various applications in clinical situations such as in effectively reducing pain during procedures (such as phlebotomy), dental appointments, dressing changes or therapeutic interventions, by providing a digital distraction during the procedure (Snoswell and Snoswell, 2019). The evidence was collected for both paediatric and adult populations in multiple settings (hospital, clinic, and home).
Artificial intelligence
Artificial intelligence (AI) combines different approaches (such as machine learning) where the software replicates tasks (functions) performed using human intelligence. The application of AI ranges from expert systems to natural language processing (NLP) (Bohr and Memarzadeh, 2020). Expert systems emulate decision-making processes made by humans using automated processes. They are designed to make complex decisions through exploring knowledge (data) and making decisions using rules (if/then/else). In a healthcare setting, responses to abnormal physiological parameters can be responded to more efficiently using expert systems. For example, ‘if ’ the blood glucose level is within ‘X’ range then ‘Y’ dose of insulin should be administered via the automated administration pump. Systems such as this already exist for diabetic patients and have gained wide acceptance in diabetes care (Umpierrez and Klonoff, 2018).
AI is constantly developing and its use is becoming more widespread, and it is predicted to change nursing practice. At a basic level, AI can be used to replace time-consuming tasks (such as bed management and stock supply) to allow nurses to spend more time with patients (Ronquillo et al, 2021). It can also facilitate visualisation of trends, based on existing data, that can support immediate care and long-term management (Ronquillo et al, 2021). For example, mobile applications have been developed using AI that can measure wounds, identify wound-bed tissue types and calculate a wound-bed preparation score, allowing more accurate monitoring of the healing process (Zoppo et al, 2020). Advanced versions of robots using AI are now available that appear more emotionally responsive. Researchers are testing robots to perform nursing functions, including ambulation support, vital signs measurement, medication administration, and infectious disease protocols (Robert, 2019). An early observational study from Japan, where healthcare robots are becoming increasingly prevalent, reported positive improvements in the quality of care received by elderly patients where robots were used to lead exercise regimens and provide interactive dialogue to patients in hospitals and long-term care facilities (Betriana et al, 2022). However, further studies are needed to fully understand the impact of these technologies in clinical practice, ideally using robust research methodologies and using established metrics for quality of care.
Conclusion
Advances in digital technologies have the potential to revolutionise health and social care. This article has provided an overview of these technologies and their relevance to nursing practice. The use of m-health creates unique opportunities to place patients at the centre of a digital system, giving them the ability to participate in the management of their own conditions. Data generated from these new technologies has myriad benefits for both patients and researchers, potentially hastening improvement in approaches to care. Machine learning and AI systems may be able to undertake tasks previously performed by human clinicians and with greater accuracy and, in some cases, identify patterns in data leading to improvements in diagnostics, monitoring and treatment.
For nurses, knowing how digital systems work and the potential problems with their use in healthcare are vital skills that will become even more important as we move towards an increasingly digital healthcare system.
KEY POINTS
- Digital technologies have the potential to revolutionise health and social care
- M-health offers unique opportunities for patients to participate in the management of their conditions, and data generated from these technologies can benefit both patients and researchers
- Augmented reality, virtual reality and mixed reality have applications in medical training, nurse education, and clinical settings
- Artificial intelligence, including expert systems and machine learning, has the potential to undertake tasks previously performed by human clinicians and improve diagnostics, monitoring and treatment
CPD reflective questions
- What steps can you take to improve your digital literacy and ensure you are able to effectively use new technologies in your nursing practice?
- How can you ensure that patients from all backgrounds and levels of digital capability are able to access and benefit from the potential advantages of m-health and other digital technologies?
- In what ways can you incorporate extended reality, artificial intelligence and other digital technologies into your nursing practice to improve patient care and outcomes and what are the potential ethical considerations to be aware of?