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The Topol Review – Highlights Preparing the healthcare workforce to deliver the digital future

Executive summary

As people live longer, but also with more long-term conditions, there is an inexorable increase in the demand for healthcare.

The workforce is also changing: millennials have new expectations and most people seek a good work-life balance through flexible careers. The NHS Long Term Plan identifies the need for more healthcare workers to respond to this increasing demand. Digital healthcare technologies, defined here as genomics, digital medicine, artificial intelligence (AI) and robotics, should not just be seen as increasing costs, but rather as a new means of addressing the big healthcare challenges of the 21st century.

The UK has the potential to become a world leader in these healthcare technologies and this Review anticipates how technological innovation will impact the roles and functions of healthcare staff over the next two decades. Our review of the evidence leads us to suggest that these technologies will not replace healthcare professionals, but will enhance them (‘augment them’), giving them more time to care for patients. Some professions will be more affected than others, but the impact on patient outcomes should in all cases be positive. Patients will be empowered to participate more fully in their own care.

This ground-breaking Review has sought expert opinion from across the UK and overseas. This is the first time that such a wide breadth of expertise has been brought together to anticipate and debate the impact of technological innovation on the NHS workforce.

With patients placed firmly at the centre of our discussions, this report is the culmination of an extensive literature review, interviews, expert meetings and roundtables. We had an overwhelming response to the call for evidence from individuals and organisations, with responses from hundreds of patient representatives, professional groups, industry, education, regulators and national bodies.

Within 20 years, 90% of all jobs in the NHS will require some element of digital skills. Staff will need to be able to navigate a data-rich healthcare environment. All staff will need digital and genomics literacy. This Review is about both the existing and the future workforce. We need to tackle differences in the digital literacy of the current workforce linked to age or place of work.

The next decade presents an opportunity to address data governance and cyber security concerns, agree ethical frameworks and develop NHS staff/organisations to implement genomics and digital technologies in the workplace. The complexity of data governance requirements should not be a reason for inaction. Most importantly, there must be mechanisms in place to ensure advanced technology does not dehumanise care. While automation will improve efficiency, it should not replace human interaction.

"Extraordinary accomplishments, from dissecting and defining DNA to creating such pervasive electronic technologies that immediately and intimately connect most individuals around the world, have unwittingly set up a profound digital disruption in medicine. Until now we did not have the digital infrastructure to even contemplate such a sea change in medicine. And until now the digital revolution has barely intersected the medical world. But the emergence of powerful tools to digitise human beings with full support of such infrastructure creates an unparalleled opportunity to inevitably and forever change the face of how healthcare is delivered."

Dr Eric Topol

This Review proposes three principles to support the deployment of digital healthcare technologies throughout the NHS:

  1. Patients need to be included as partners and informed about health technologies, with a particular focus on vulnerable/marginalised groups to ensure equitable access.
  2. The healthcare workforce needs expertise and guidance to evaluate new technologies, using processes grounded in real-world evidence.
  3. The gift of time: wherever possible the adoption of new technologies should enable staff to gain more time to care, promoting deeper interaction with patients.

Genomics, digital medicine and AI will have a major impact on patient care in the future. A number of emerging technologies, including low-cost sequencing technology, telemedicine, smartphone apps, biosensors for remote diagnosis and monitoring, speech recognition and automated image interpretation, will be particularly important for the healthcare workforce.

What does this mean for patients, carers and the wider community?

In the future, many aspects of care will shift closer to the patient’s home, while more specialised care is centralised into national or regional centres. The NHS has been working towards a less paternalistic relationship between patients and staff for some time, and digital healthcare technologies have the potential to speed up that process, to empower individuals to be more informed about their care, and to allow them to work together with healthcare staff to make treatment decisions.

Genomics has the potential to transform healthcare with more accurate diagnoses of a broader range of diseases with a genetic basis, and to allow patients to know their likelihood of developing one of these diseases. However, there is a need to develop clear frameworks for healthcare staff to use genomic data in a way that safeguards patient confidentiality, and inspires the support and confidence of citizens and the wider community.

Digital medicine is already changing the way people interact with healthcare. Telemedicine services include telephone triage such as 111 and the ability to have video appointments. Smartphone apps help patients self-manage and order repeat prescriptions. Remote monitoring is changing the way care is delivered. Almost 90% of the population regularly use the internet, yet less than a quarter has so far registered for online services with a GP. The health and care system will need to work with patients to co-create applications of digital technologies which meet their needs.

Using AI-based technologies, automated image interpretation in radiology and pathology will lead to faster diagnosis, while speech recognition has the potential to free up more staff time to deliver care. AI will transform patient-generated data into clinically useful information and empower patients to manage their own health or seek appropriate health support. Patient benefit should be the driving force behind AI and robotics design, with new products co-developed with patients from design to implementation.

Advances in healthcare technologies and a greater focus on prevention, health and wellbeing will bring major improvements in patient outcomes. However, it is critical that the healthcare system prepares to adopt any new technologies in a spirit of equality and fairness. A range of social determinants affect health outcomes, and digital health technologies should redress not reinforce inequalities, with particular attention given to vulnerable and marginalised groups.

An evolving health workforce

There is a need to raise awareness of genomics and digital literacy among the health and social care workforce. The latter requires the development of the skills, attitudes and behaviours that individuals require to become digitally competent and confident. The levels of digital literacy, the workforce’s awareness of the required capability, access to training and support, and skills to enable patients and citizens to improve health and wellbeing through technology will all need to be improved, as a fundamental shift in the balance of skills in the workforce takes place over the next two decades. This will present new career opportunities for some of the workforce.

Genomics will become integral to all medical specialties. While some aspects will remain with highly specialised professionals, many will become mainstream and embedded in routine healthcare delivery. The health workforce will play a key role in ensuring that genomic technologies are efficiently, appropriately and equitably deployed, so that individuals can understand how genetics can affect their health.

Digital medicine will require leadership with the capability to direct the agenda, which should include a Board-level member, as well as new senior roles with responsibility for advising boards on digital technologies. The NHS must build skills in data provenance, curation and governance, enhance the understanding of ethical considerations and strengthen the necessary skills to carry out critical appraisal.

Artificial intelligence will be deployed to augment the skills of the NHS workforce. Staff will need to understand fully the issues of data validity and accuracy. Early benefits of AI and robotics will include the automation of mundane repetitive tasks that require little human cognitive power, improved robot-assisted surgery and the optimisation of logistics.

"We have to prepare students for jobs that have not yet been created, technologies that have not yet been invented and problems that we don’t yet know will arise."

NHS organisations should invest in their existing workforce to develop specialist skills, including the assessment and commissioning of genomics and digital technologies. With all new technologies, it is essential to identify future champions early and create networks to enable collaborative learning. Accredited continuous professional development (CPD) and flexible on-going training and career opportunities, including portfolio careers in academia or industry, will be important to deliver change. NHS Boards should also take responsibility for effective knowledge management to support innovation and change.

"We need to equip all staff across the NHS with the right skills to constantly innovate and continuously realise the benefits that technology will provide."

Health service leadership to integrate and adopt new technologies

Technological innovation will increasingly shift the balance of care in the NHS towards more centralised highly specialised care and decentralised less specialist care. This will result in long-term shifts in patterns of need and services. For new digital healthcare technologies to reach their full potential and deliver significantly better patient outcomes without the need to increase resources, the whole health and care system will need to anticipate and plan for the future. As it can take up to 10 years to realise cost savings, investment in IT systems, hardware, software and connectivity, as well as the training of healthcare staff and the public, will have to be planned carefully.

As we shift towards whole genome sequencing, genomics will extend beyond rare diseases and cancers, producing benefits in prevention and management of common later-onset diseases. It is now possible to make corrections to an individual’s DNA that could lead to cures for previously untreatable diseases and deliver targeted therapies. Such an intervention may replace some current palliative therapies in the next 10-20 years, achieving cures and having the potential to reduce the costs of chronic treatments.

There is a need to complete the digitisation and integration of health and care records if the full benefits of digital medicine (earlier diagnosis, personalised care and treatment) are going to be realised for the NHS. An understanding of how data-driven technologies are best deployed to support and improve working practices will be part of workforce development. This will make it easier to commission digital medicine services, for example, telemedicine with the aim of improving ease of access and decreasing non-attendance rates, or remote monitoring with the aim of reducing unplanned hospital admissions.

"Digital technologies have transformed most sectors which affect our daily lives, from communications to transport, banking and entertainment, but not yet healthcare. This is now changing as electronic patient records and online services, as well as wearables, smartphones and apps, are beginning to have a positive impact on the NHS and its workforce."

Advances in mathematics, computing power, cloud computing and algorithm design have accelerated our ability to analyse, interpret and make decisions using artificial intelligence. Uneven NHS data quality, gaps in information governance and lack of expertise remain major barriers to the adoption of these advances. A binding code of conduct and a transparent information governance framework are required to support the analysis of anonymised patient data by industry, as well as guidance to support the evaluation and purchasing of AI products. Capability must be developed within the NHS to identify and understand algorithmic bias and ensure that data does not reflect the bias inherent in social structures, and reinforce structural discrimination and inequalities.

To ensure equity in the adoption of any new technologies, health economy-led mapping of access, use and impact of technology-enabled care will be essential. Patient safety should be at the centre of the integration of new technologies. Health leaders will need to work together with regulators to review the regulation and compliance requirements of new digital technologies, alongside cyber security and data privacy to ensure transparent, resilient, robust and legally enforceable governance policies and practices, and provide evidence-based guarantees of the safety of healthcare technologies. We should learn from other industries and international examples. Training should be commissioned to develop a cadre of specialists in the regulation and assessment of digital technologies.

In order to bridge the skills gap, the NHS will need to collaborate with academia and industry, and attract global technical talent through new apprenticeships and Masters schemes, for example, expanding the NHS Digital Academy, and introducing industry exchange networks to facilitate collaborative working. There is a need to develop a continuous pipeline of robotics engineers, data scientists and other technical specialists, who can then be attracted into the NHS to create the new technological solutions that will improve care and productivity.

Creating a culture of innovation and learning will be critical, by cultivating a reputation for training and support, proactive learning activities, opportunities to learn and reflect away from the workplace, dissemination of lessons from early adoption and sharing examples of best-practice evidence-based initiatives.

Conclusions

This is an exciting time for the NHS to benefit and capitalise on technological advances. However, we must learn from previous change projects. Successful implementation will require investment in people as well as technology. To engage and support the healthcare workforce in a rapidly changing and highly technological workplace, NHS organisations will need to develop a learning environment in which the workforce is given every encouragement to learn continuously. We must better understand the enablers of change and create a culture of innovation, prioritising people, developing an agile and empowered workforce, as well as digitally capable leadership, and effective governance processes to facilitate the introduction of the new technologies, supported by long-term investment.

Recommendations

The Review Board recommends:

The citizen and the patient

  • In a similar way to other public health education initiatives, programmes aimed at engaging and educating the public about genomics and digital healthcare technologies should be developed. (P1)
  • The NHS should work with patient and carer organisations to support appropriate patient education. (P2)
  • Local arrangements should be established to provide needs-based targeted education and support through existing patient support provision, where possible. (HI1)

The Genomics Panel recommends:

The citizen and the patient

  • The NHS, in partnership with relevant regulatory bodies, should establish a clear, robust framework by which healthcare professionals use genomic data, which safeguards patient confidentiality, and inspires the support and confidence of citizens and the wider community. (G1)

Healthcare professionals

  • All healthcare professionals should receive core training in genomic literacy to help them understand the basis, benefits and ethical considerations associated with genomics. (G2)
  • Lifelong training should be available to healthcare professionals with emphasis on continuing support in this rapidly evolving field, including access to dynamic ‘just-in-time’ digital updates and online genomic information resources. (G3)
  • Accredited genomic training for healthcare professionals should be established in key clinical specialities to incorporate genomic testing and genomic counselling into their practice. (G4)
  • Capacity should be built within the NHS Genomic Medicine Service through support for specialist healthcare professionals including genomic counsellors, clinical scientists and specialists in genomic medicine. (G5)

Health system

  • An attractive career pathway should be developed for bioinformaticians, including expansion of Higher Specialist Scientist Training for clinical bioinformaticians. (G6)
  • A framework for genomic leadership should be developed across clinical specialities and primary care settings to encourage and disseminate best-practice and to simplify patient referral systems. (G7)
  • Academic institutions should ensure genomics and data analytics are prominent in undergraduate curricula for healthcare professionals, and that there should be expansion of undergraduate capacity in genomics, bioinformatics and data science. (G8)

The Digital Medicine Panel recommends:

The citizen and the patient

  • NHS online content should be a vital trusted source of health information and be resourced appropriately. (DM1)
  • The NHS should expand research and development programmes, working closely with patients to co-create digital technologies and ensure that emerging technologies meet their needs. (DM2)

Healthcare professionals

  • NHS organisations should invest in their existing workforce to develop specialist digital skills, including the assessment and commissioning of digital technologies, through the Digital Academy, continuous professional development (CPD), sabbaticals and secondments. (DM3)

Health system

  • The NHS, working with regulators, should develop and commission courses to increase the number of specialists in the evaluation and regulation of digital technologies. (DM5)

The Digital Medicine and AI & Robotics Panels recommend:

  • The NHS should create or increase the numbers of clinician, scientist, technologist and knowledge specialist posts with dedicated, accredited time, with the opportunity of working in partnership with academia and/or the health tech industry to design, implement and use digital, AI and robotics technologies. (DM4/AIR5)
"With over 1.2 million staff in England, the NHS is one of the largest employers in the world. It is vital that we empower NHS staff and patients to use emerging digital technologies, including nanosensors and wearables for early disease diagnosis and monitoring.”

Professor Rachel McKendry

The Organisational Development Working Group recommends:

The citizen and the patient

  • NHS organisations must ensure that patients, citizens and staff are involved in the co-design of transformation projects, particularly in identifying how digital healthcare technologies can help to improve both patient experience and staff productivity. (OD1)
  • NHS organisations must ensure that patients, citizens and staff are involved in the co-design of transformation projects, particularly in identifying how digital healthcare technologies can help to improve both patient experience and staff productivity. (OD1)

Healthcare professionals

  • Senior roles should be developed with responsibility to advise on the opportunities offered by digital healthcare technologies and identify local skills gaps. (OD2)
  • Healthcare professionals will need to access training resources and educational programmes in digital healthcare technologies to assess and build their digital readiness. (OD3)

Health system

  • Each organisation should assign Board-level responsibility for the safe and effective adoption of digital healthcare technologies at scale, with a focus on clinical outcomes and on promoting effective and consistent staff engagement. (OD4)
  • NHS Boards should take responsibility for effective knowledge management to enable staff to learn from experience (both successes and failures) and accelerate the adoption of proven innovations. (OD5)
  • The NHS should strengthen systems to disseminate lessons from early adoption and share examples of effective, evidence-based technological change programmes. (OD6)
  • NHS organisations should use validated frameworks to implement technological solutions and ensure staff are trained to use these. (OD7)
  • The NHS should support collaborations between the NHS and industry aimed at improving the skills and talent of healthcare staff. (OD8)
  • The NHS should work with stakeholders across sectors to review the regulation and compliance requirements for new digital healthcare technologies, including the provision of guidance and training on cyber security, data privacy and data anonymisation, learning from the experience of other international healthcare systems. (OD9)
"Educating the current and future NHS workforce is key to enabling the implementation of the revolutionary changes to healthcare practice and delivery that technological advancement will bring for the benefit of patients, carers and citizens."

Technological advances impacting healthcare and the magnitude of disruption

Top 10 digital healthcare technologies and their projected impact on the NHS workforce from 2020 to 2040

"The pace of adoption will depend on factors such as the nature of the technology itself, staff costs including training, initial investment required, public perception, and regulation."

Persona: Eddie the bioinformatician

Eddie in 2013, aged 21:

Eddie is a final-year zoology undergraduate. His dissertation involves studying the phylogenetics of old-world parasites and he has recently learned how to analyse genetic sequences of insects. His housemates are studying medicine and physiotherapy. He feels that working within a team environment in the NHS would suit him. He is interested in genomics and decides to pursue training as a bioinformatician. Eddie is delighted to be accepted for the post-graduate NHS clinical scientist training programme in clinical bioinformatics.

Eddie in 2019, aged 27:

Eddie is now a clinical scientist working as a bioinformatician in a Genomic Laboratory Hub within a large NHS University Hospital Trust. His training programme helped develop a wide array of skills that have enabled him to respond flexibly to the rapidly changing needs of the service. His communication and research skills are major assets for his job.

Eddie is excited by the potential of emerging technologies that allow the detection of molecular disease markers in patients and are affordable enough to be used routinely in clinical practice. He uses his skills in computational genomics and statistical biology to work with colleagues in developing improved bioinformatics tools for identifying complex genetic variants.

He also spends part of his time on the genetic analysis of the data generated from the 100,000 Genomes Project. He is enjoying the opportunity of working at the leading edge of genomics knowledge and finding new genetic diagnoses in patients with rare haematological diseases.

Eddie in 2029, aged 37:

Eddie is now a consultant bioinformatician specialising in haematological cancers. He is an integral member of the team providing a specialist haematology clinical service. His clinical responsibilities include analysing genomic data from live tumour cells for new variants that may require a change in medication or more targeted treatment.

He is a lead member of a research group developing new personalised treatments for rare haematological cancers. His work in evolving new technologies involves collaborating with clinicians, other healthcare scientists and computer scientists to develop tools to improve diagnostic accuracy and yield through better integration of disparate data types.

Eddie also spends time teaching patient groups and primary care physicians in the community, and curating new educational resources for patients, clinicians and healthcare scientists. He has recently applied for the role of NHS Regional Dean for Genomic Education.

Persona: Tom the nurse

Tom in 2009, aged 13:

Tom’s mum is a nurse and he would like to follow in her footsteps. He is interested in maths and science, but worries that his assessment scores will mean that he won’t be able to pursue and progress in a health career. However, he has impressed his teachers and peers with his teamwork, leadership and knowledge in school technology projects. Tom’s hobbies include sci-fi films and playing video games.

Tom in 2019, aged 23:

Tom left school at 18. He had a few other jobs before following his passion for healthcare and trying a career in nursing. Six months ago he joined the NHS as an Apprentice Nurse, undertaking a Level 6 qualification.

Tom likes respiratory nursing, and is developing an interest in exploring how digital healthcare technologies can improve workflow and support patients. He was delighted to be accepted to train at one of the NHS Digital Exemplar sites and to have a Digital Nurse Champion as his mentor.

Tom is excited about discussions of future nursing careers supported by new educational courses and learning resources, which help build skills with health data and technologies across healthcare professions. He has signed up to some of the new genomics and data science development courses.

Tom in 2029, aged 33:

Tom works in primary care. He has recently been appointed as a Consultant in Community Respiratory Care and is a partner in a community health centre, opportunities he would never have considered possible when leaving school.

Tom provides dedicated coaching sessions with newly diagnosed patients with asthma or COPD on how smart inhalers, apps and mobile devices can help them monitor and optimise their health. He co-designs personal health plans which incorporate genomic data, individual physiology and the patient’s desired clinical outcomes.

Tom’s multi-professional team receive patient alerts on clinical deterioration and medication adherence via a safe, AI-augmented remote consultation platform. The team triage patients promptly, nudge health behaviours and recommend new care plans where necessary.

Each month, Tom co-leads a two-hour ‘hackathon’ where a variety of collaborators come together to co-design and co-produce technological solutions for local problems affecting patient care and service need.

Persona: Salma the paramedic

Salma in 2009, aged 38:

Salma is a psychology graduate and worked for various medical charities for 10 years before deciding to pursue a new career. She remained very interested in working in the healthcare field.

Following completion of a two-year Level 3 vocational course, she graduated with a degree in paramedic science and recently qualified as a paramedic. Salma’s training contained very little about how paramedics may benefit from evolving technology throughout their careers.

Salma in 2019, aged 48:

Salma, a senior paramedic, is a team leader in a large city. She is frequently frustrated by the lack of patient information accessible at the scene of an emergency. Furthermore, she would like to be able to provide A&E departments with better real-time information on the patients she is treating, in advance of their arrival at A&E department, in order to streamline the handover and treatment process.

Salma is determined to increase her knowledge and skillset to deploy health technologies at work. She has researched how digital health tools could improve healthcare, but has yet to see significant change or investment in technology that improves her working life. Salma participated in the comprehensive NHS consultation process aiming to capture workforce opinions on their competencies and challenges in adoption of technology.

Salma in 2029, aged 58:

Salma has seen her work transformed by the impact of digital technologies. She is transported in an autonomous ambulance that drives the most efficient route to an emergency, improving response times. On receiving the patient details, Salma gains immediate access to the integrated electronic patient record that is projected onto a digital display, providing information on medical history, allergies and pharmacogenomics profile.

Salma’s smartwatch and smartphone, enabled with mobile vital signs and an ECG reader, and AI-augmented ultrasound scanner, facilitate real-time monitoring and diagnostics. All the data captured are immediately transmitted to the hospital-based team who, with the help of machine learning algorithms providing decision support, can advise, plan and prepare any additional treatment prior to the patient’s arrival.

Salma receives regular education and training updates on innovation in clinical practice hosted within clinical skills hubs, which model how technology and health data can best be used to improve patient care.

Persona: Sarah the doctor

Sarah in 2009, aged 26:

Sarah is a paediatric specialist trainee and loves her work. She has started to use a smartphone in her personal life, but has no access to mobile technology at work and is frustrated by having to rely on outmoded technology, especially fax machines, and time-consuming paper records. Communication with her peers and multi-professional colleagues is disjointed, and has caused patient safety incidents.

Sarah in 2019, aged 36:

Sarah is a paediatric consultant with a specialist interest in metabolic medicine. She has completed a Masters degree in Medical Education and modules of the Genomics Education Programme. Sarah observes that despite schemes like the NHS Clinical Entrepreneur Programme, adoption of innovation in the NHS is variable and slow.

Although hospital-wide electronic prescribing and a new electronic patient record have been introduced, Sarah is still frustrated by needing to use fax machines and bleeps. She wants to use more streamlined, intelligent communication with colleagues and patients, which maximises the amount of time she can spend with patients. However, there are still concerns in her Trust about the data governance and General Data Protection Regulation for social media such as WhatsApp. Sarah is encouraging her Trust Board to be forward-thinking and review some of the NHS Global Digital Exemplars’ initiatives in health information integration.

Sarah in 2029, aged 46:

Sarah is a consultant with a portfolio career that combines clinical work in paediatrics with a national coordinating and oversight role within Genomics England.

Most of her patients have their whole genome sequenced at birth, allowing Sarah a much greater understanding of her patients’ pathology. Sarah’s clinical team now includes bioinformaticians and computer scientists – who bring expertise and learning from their secondments in industry. The whole team benefits from access to integrated, interoperable electronic patient record systems supported by AI technologies. Machine-learning algorithms process the outputs from wearable sensors that remotely monitor metabolic markers to predict patient health trajectories and model personal care plans. As a result, early intervention, followed by personalised treatments, have markedly improved outcomes in conditions such as diabetes. Furthermore, cloud-based educational tools provide accessible ‘just-in-time’ learning resources that enable clinicians, patients and their families to better understand and manage their conditions.

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