Future Medical Workforce Project Annex A: Summary of call for evidence findings on innovation and technology, and review of views from the public and patients
Summary of call for evidence findings on innovation and technology, and review of views from the public and patients
Part 1: Introduction
A call for evidence was launched inviting contributions from Health & Social Care professionals, Academic Institutions, Innovation Networks and Medical Royal Colleges and Faculties to consider innovative approaches, technological and non-technological, that can support the delivery of high-quality, equitable, and future-ready services and realise the vision for Scotland’s population to live longer, healthier and more fulfilling lives and to consider what this means for our future workforce needs.
We invited evidence and insights from individuals, organisations, and partnerships on innovations—both technological and non-technological—that can support the delivery of the Health and Social Care Service Renewal Framework (SRF) 2025–2035 [1]. This call sought to identify scalable, impactful solutions that aligned with the Framework’s five core principles:
Prevention and Early Intervention: prevention of ill health across the continuum of care
Person Centered and Values Based Care: care designed around people rather than the ‘system’ or ‘services’
Community Based Service Delivery: more care in the community rather than in hospital
Population Planning and Equity: planning around population need, rather than along boundaries
Digital Transformation and Artificial Intelligence (AI): using technology to improve services in a safe, ethical and efficient way
Methods
The call for evidence was launched in August 2025. Respondents were requested to provide a brief description of the innovation or evidence and to identify which of the SRF principles the innovation aligned with. As well as the 5 SRF core principles we asked respondents about the impact on the medical workforce. Respondents representing Royal Colleges or Faculties were invited to answer questions around specific areas of interest.
Respondents were asked to answer the following questions based around each area of interest:
Prevention and Early Intervention
How can innovation support early detection and management of long-term conditions?
What new models or tools will support doctors to provide care and improve health outcomes?
What would support a move towards preventative care, and how might prevention-focused workforce differ from our current model?
What new models or tools will support doctors to provide care and improve health outcomes?
What would support a move towards preventative care, and how might prevention-focused workforce differ from our current model?
Person Centred and Value Based Care
What is the role of a medical professional in supporting individuals to manage their own health and care, and how might technology influence this?
What innovations can support services to move towards person-centred care?
Community Based Service Delivery
What approaches have shifted/could successfully shift care from acute settings to communities and what does this mean for our medical workforce?
How will technology/innovation support the shift of care from hospital to community?
How can technology or service redesign improve access to medical care services in rural and island areas?
Population Planning and Equity
How can we improve the use of data and evidence to plan services based on population need?
What innovations address health inequalities and improve access for underserved groups?
Digital Transformation and AI
What digital tools or platforms have improved care co-ordination and outcomes?
How can AI be safely and ethically used to support diagnosis, triage, or resource planning?
What are the barriers and enablers to digital inclusion in health and social care? What skills will our workforce require to support this?
Workforce Enablement/Impact
What innovations support workforce wellbeing, efficiency, and collaboration?
How can training and development be adapted to support new models of care?
How will technology/innovation impact the role of the doctor over the next 20 years?
For Royal Colleges / Expert Advisors Only
In your specialty, how will or could the role of the consultant/general practitioner change in the next 20years?
What will be required to enable that change?
How will AI/digital technology impact the current role/workload of doctors in this specialty?
It was asked that all submissions highlight the achieved or anticipated outcome of the innovation and any considerations regarding scalability or sustainability, providing any supporting data, evaluations or references.
The window for submission was extended to seven weeks to support collation of responses.
Each submission underwent a desktop review to identify overarching themes and examples of innovation, which were then aligned with the appropriate SRF framework category.
Results
There were 30 submissions to the call for evidence. Table 1 shows the number of submissions by category of respondents.
| Category of Respondent | Number of Submissions |
|---|---|
| Professional Organisations | 8 |
| Individual Healthcare Professionals / Academics | 6 |
| Royal Colleges / Faculties | 9 |
| Academic Institutions | 5 |
| Service Representation | 1 |
| Innovation Network | 1 |
| Total | 30 |
Appendix 1 outlines the types of evidence included in each submission to the call for evidence. Each submission contained multiple categories of evidence.
Table 2 illustrates the number of submissions introducing innovations within each area of interest.
| Area of Interest | Number of Submissions |
|---|---|
| Prevention and Early Intervention | 19 |
| Person Centred and Value Based Care | 18 |
| Community-Based Service Delivery | 2 |
| Population Planning and Equity | 17 |
| Digital Transformation and AI | 21 |
| Workforce Enablement and Impact | 12 |
Appendix 2 contains any relevant supporting documentation and references from each submission.
Summary Of Key Themes
The following is a summary of the high-level themes from the call for evidence mapped to each area of interest based on the five core principles of the SRF framework.
Prevention and Early Intervention
Technology can enable prevention of illness with increasing precision. Several submissions called for the adoption of targeted genomic surveillance techniques to improve the early identification of inherited conditions. The use of ‘Big Data’ platforms can inform on population need and support tailored, risk prevention strategies[2]. Technology offers further opportunities through wearable devices and AI tools which enable early detection, remote monitoring and self-management[3].
Strengthening primary care was seen as essential for early detection and preventative support[4]. There was also support for innovative points of access for patients, such as reframing waiting lists as “preparation lists” to offer screening, lifestyle advice, and prehabilitation before treatment[5].
Respondents highlighted the need for doctors to support and enable behavioural change and self-management. Doctors could provide this support virtually with results from remote monitoring being escalated into virtual wards or multi-disciplinary teams. Evidence from one submission showed that embedding physical activity into routine care can reduce hospital admissions and improve wellbeing[6].
Respondents noted that current services are illness focused, noting that if there is to be a shift of focus to prevention this will require not only technological innovation but also organisational, service and social innovation[7]. Furthermore, caution was expressed regarding the mixed evidence available around impact[8]. Risk prediction algorithms (such as those for sepsis or atrial fibrillation) are maturing; however, frontline clinicians often find that such predictions do not translate into actionable changes in the way they provide care[9].
Person Centred and Value Based Care
Innovations will help patients get the information they need to make decisions about their own health. Patients should have access to, and be able to interact with, their personal health records through electronic platforms such as the Digital Front Door. Genomic testing can help facilitate personalised care plans[10]. Explainable AI tools can help enhance understanding and trust by making clinical reasoning transparent. AI-driven triage using natural language processing and computer vision can streamline referrals[11].
Armed with information about their own health and treatment pathways, patients will be empowered to make decisions about their health with their doctor through shared decision-making models[12]. Decision support tools can help guide choices.
Self-management is increasingly possible through wearable devices linked to remote support apps. Doctors can adopt new ways to contact their patients such as online group consultations and webinars which can both improve access and foster peer support.
The adoption of patient reported outcomes measures (questionnaires that gather information directly from a patient about their health or quality of life) can ensure that interventions are targeted towards what is important to the patient.
To realise the benefits of these innovations, interoperable electronic health records and secure digital infrastructure are critical to enabling integrated care across health and social services[13].
Relational continuity remains essential for trust and satisfaction, and coordinated models like Supportive Oncology (a multidisciplinary approach that manages the physical, psychological, and practical impacts of cancer) demonstrate improved outcomes[14][15][16]. These coordinated models are enabled by secure, shared patient data.
Community Based Service Delivery
Expanding hospital-at-home and community health services will shift care closer to home, helping reduce hospital admissions and support early discharge[17]. Embedding multidisciplinary teams and specialists in community settings will enable delivery of high-quality care outside hospital environments. Technology plays a key role in this shift, with telemedicine, portable imaging, wearable biosensors, and remote monitoring tools supporting assessment, treatment, and rehabilitation of the patient in their own home[18][19]. Asynchronous consultations have proven acceptable to patients and offer cost-effective, efficient care.
To make this shift sustainable, investment in the social care workforce is essential, particularly to support transitions from hospital to home and meet the needs of an ageing population.
Reliable connectivity and digital infrastructure are critical, especially in remote and rural communities, yet many systems lack the maturity needed to safely integrate data from remote devices[20].
Without inclusive implementation, digital care risks excluding underserved groups; patients must be supported with access to and training in relevant technologies.
While remote care models offer value, they cannot fully replace face-to-face contact. Hospital-at-home services show promise, but caution was expressed around their economic viability at scale[21].
Population Planning and Equity
A number of submissions emphasised the use of epidemiological and demographic data to ensure that resources are targeted to areas and groups where there is the greatest need[22][23]. AI-generated insights from sources like referral and imaging data can help identify patterns and inequities in access. Multiple submissions highlighted a need to ensure that academics, policy makers and clinicians have access to data to be able to generate real-time, policy-relevant evidence.[24]. Furthermore, there was a call to build on Scotland’s leadership in data linkage to integrate health outcomes with social determinants (e.g. employment status) for more targeted interventions.
Inclusive frameworks must actively engage under-represented communities, with assertive outreach in primary care and community hubs to prevent entrenched health inequalities[25][26][27],. Respondents highlighted the opportunity to expand outreach models, such as the Scotland Deep End Project (comprising 100 practices serving the most socio-economically deprived communities) to ensure access and outcomes in deprived areas.
Without adequate support, digital innovation risks excluding underserved groups. To mitigate this, technologies must be co-designed with these communities, placing Public and Patient Involvement and Engagement (the process of research being carried out by or with members of the public) at the centre[28].
Digital Transformation and AI
AI technologies are increasingly being explored in healthcare across Scotland, particularly in diagnostics, triage, and predictive analytics. These tools offer significant potential benefits to both clinicians and patients, including enhanced decision-making, reduced administrative workload, improved access to care, and greater patient empowerment. Examples include transcription systems[29], decision support tools, virtual consultations, and app-based therapies, all of which are seen as aids to clinical efficiency rather than replacements for professional judgement.
Intelligent platforms, such as the Intelligent Liver Function Test (an algorithm-based system which provides automated laboratory investigations and clinical feedback on abnormal liver function test (LFT) results from primary care) are helping to drive patient-centred precision medicine[30],[31]. AI is also being piloted in areas including cancer screening[32],[33],[34], dermatology triage, retinal screening for diabetic retinopathy, and predictive analytics for bed and staffing demand. Tools like Delphi show early promise in combining AI with population data to support disease prediction and clinical decision-making[35].
Despite these opportunities, challenges remain. Past digital implementations have not always delivered expected efficiency gains, sometimes increasing administrative burdens due to outdated infrastructure and fragmented systems. There is a clear need for investment in modern digital infrastructure, national planning for interoperability, integrated patient records, and reliable connectivity.
Ethical considerations are also critical, including bias monitoring, confidentiality, and regulation. Continuous evaluation and transparent reporting of AI tools are essential, alongside careful consideration of their financial and environmental impacts. A Scotland-wide pathway for approvals for Caldicott, information, and data governance, rather than repeating the same process for each board, is essential. Respondents reported that this is currently a major barrier to any digital initiative.
Importantly, the human element in healthcare must not be overlooked. AI cannot replace the therapeutic relationships and nuanced clinical judgement that underpin effective care. To fully realise the benefits of digital innovation, there is an urgent need to improve digital literacy among both healthcare staff and patients.
Workforce Enablement and Impact
To meet the growing demands of complex care and the opportunities presented by digital innovation, Scotland’s medical workforce will require targeted training in digital literacy, AI ethics, and digital health. Education and training must evolve to foster leadership, systems thinking, adaptability, and basic research skills, while also encouraging innovation and entrepreneurial approaches to service development. This shift will need to be reflected in both undergraduate and postgraduate curricula.
The role of the doctor is expected to change, with increasing emphasis on leadership, complex decision-making, care coordination, and strategic service-level responsibilities. While AI and robotic process automation can help reduce administrative and repetitive tasks, freeing up time for clinicians to focus on complex care and human connection, the core responsibilities of clinical judgement and empathy will remain central.
Digital tools also offer opportunities to streamline workloads, improve team coordination, and enhance morale by allowing clinicians to focus on tasks requiring their expertise.
These changes call for strategic workforce planning that includes time for training, leadership development, analytics, and research.
Expanding the clinical informatics workforce, particularly with dual-trained professionals who can bridge clinical and digital domains, will be essential.
Conclusion
The call for evidence highlights a strong consensus that technology and innovation can transform healthcare delivery in Scotland, but success depends on more than digital tools alone. Respondents emphasised the need for integrated approaches combining technological, organisational, and social innovation to shift from illness-focused models to prevention and person-centred care. Digital transformation, including AI and interoperable health records, offers significant potential for precision medicine, improved access, and efficiency, yet requires robust infrastructure, ethical safeguards, and workforce training. Community-based models and inclusive frameworks are essential to ensure equity and avoid digital exclusion. Ultimately, the human element—trust, relational continuity, and clinical judgement—must remain central as Scotland advances toward a digitally enabled, equitable, and sustainable health system.