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Journal articleRajput K, Zuberi S, Elhajj M, et al., 2026,
Mapping Machine Learning-Driven Cybersecurity Solutions in Health Care: Scoping Literature Review.
, J Med Internet Res, Vol: 28BACKGROUND: Health care systems face escalating cyberattacks, including the UK Synnovis ransomware attack, which halted pathology services for 14 weeks; the Ascension Health breach affecting 5.6 million patients; and the Change Healthcare breach costing US $2.5 billion. Conventional cybersecurity measures in health care remain reactive and inadequate against evolving threats. Machine learning (ML) offers adaptive, predictive, real-time cyber defense; yet, there is limited clarity on how ML tools are applied across cybersecurity domains, their real-world effectiveness, and where gaps remain. OBJECTIVE: This study aims to map ML applications in health care cybersecurity against the National Institute of Standards and Technology Cybersecurity Framework version 2.0, summarize ML performance, and identify research gaps and implementation considerations. METHODS: A systematic search of Ovid MEDLINE, Embase, and Scopus was conducted on July 30, 2025, for studies between 2019 and 2025. Eligible studies applied ML-based approaches to organizational-level cybersecurity in health care settings, with outcomes related to data privacy or cybersecurity strengthening. Studies on smart devices, blockchain, or those lacking empirical data were excluded. Title and abstract and full-text screening were conducted independently by 2 (KR and SZ) reviewers following the Arksey and O'Malley framework and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, with discrepancies resolved by consensus. Data were synthesized narratively and mapped against the 6 National Institute of Standards and Technology Cybersecurity Framework version 2.0 functions (Identify, Protect, Detect, Respond, Recover, and Govern). RESULTS: From 10,348 articles identified, 45 studies across 18 countries were included, applying 80 ML models. Most studies addressed "Protect" (n=22, 48.9%), encompassing federated learning, homomorphic encrypti
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Journal articleToparti O, Rajput K, Darzi A, et al., 2026,
Cybersecurity in connected medical devices: a policy agenda for the NHS.
, NPJ Digit Med, Vol: 9Connected Medical Devices (CMD) are redefining care within the NHS but exposing it to bi-directional cyber-physical threats that traverse physical, network and cloud layers. These vulnerabilities blur the boundary between technology and patient safety. This Comment argues that the MHRA should elevate cybersecurity to a clinical-safety mandate, enforcing a unified socio-technical framework with security-by-design, cross-layer risk assessment and continuous post-market vigilance.
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Journal articleFreyer O, Rajput K, Ostermann M, et al., 2026,
Are we heading towards a cybersecurity crisis in health care and are actions needed?
, Lancet Digit Health, Vol: 8 -
ReportGhafur S, Waldock W, Leis M, et al., 2025,
Building the future of UK health data: a blueprint for the health data research service
, Building the Future of UK Health Data: A Blueprint for the Health Data Research Service -
Journal articleBove R, Capezzuto L, West I, et al., 2025,
Simulation of Clinical Visits as a Novel Approach to Evaluate Digital Health in Multiple Sclerosis: Simulation Study.
, JMIR Med Inform, Vol: 13BACKGROUND: Efforts are being made to integrate digital health technologies into clinical care for multiple sclerosis (MS) to improve patient monitoring. Efficiently probing how they might impact clinical care could streamline digital tool development. The Floodlight digital tool, comprising 5 smartphone sensor-based tests, was used to generate health-related data on patient function and symptoms in a clinical simulation. OBJECTIVE: The study had 3 objectives: (1) assess the utility of simulated clinical encounters as a research methodology for exploring the introduction of digital health technologies into clinical practice in MS, (2) confirm the fidelity of the simulated environment and patient cases developed and understand what metrics (eg, workflow, comprehensive evaluation) could be generated, and (3) generate insights into the utility of digitally collected data, including usability, clinical decision contribution, and impact on workflows, in clinical practice. METHODS: A total of 2 patient cases consisting of clinical, radiological, and digital health data were developed with clinician input. US-based neurologists prepared for and conducted 2 simulated teleconsultations each, with an actor briefed on case profiles. Floodlight data were available, via the Floodlight MS™ Health Care Professional Portal, for 1 of the 2 consultations. Participant neurologists completed interviews and surveys assessing the fidelity of the cases presented, user experience and workflow metrics, patient concerns identified, care decisions made, and confidence in making decisions. RESULTS: All 10 neurologists indicated that the simulations were high-fidelity representations of real consultations. Using the Floodlight technology for the first time, median time taken to prepare for and conduct the consultation was ~1.7-2 minutes longer, with slightly greater mental effort reported by participants, compared with not using the tool. The Floodlight MS Health Care Professional Portal
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Journal articleOdunlami WO, Li E, Greenfield G, et al., 2025,
Factors influencing primary care physicians recommending patients to use digital health technologies for self-management: a cross-sectional study across 20 countries
, European Journal of General Practice, Vol: 31, ISSN: 1381-4788BackgroundExpanding access to self-management via Digital Health Technologies may supplement traditional care, mitigating pressures on primary care through self-management. Primary Care Physicians (PCP) can play a critical role in the integration of digital health technologies into patient care, but it is unclear what factors influence PCPs’ recommendation of such technologies.AimsTo identify the factors associated with PCPs recommending digital health technologies to patients for self-management before and during the pandemic.MethodsPCPs across 20 countries completed an online questionnaire between June and September 2020. The outcome was a self-report of recommending patients to at least one of six listed forms of digital health technologies. Univariable logistic regression models were performed to explore factors associated with recommending digital health technologies to patients before and during the pandemic.Results1,592 PCPs were included. Before the pandemic, the odds of recommending digital health technologies for self-management were lower for PCPs not involved in teaching, or practising in Turkey, Australia, Chile, Colombia, France, Italy, Poland, Portugal, Slovenia, and Spain. During the pandemic, PCPs practising in rural settings had higher odds of starting to recommend digital health technologies, as well as those from Brazil, Colombia, and Italy. There was no significant difference in recommending digital health technologies before and during the pandemic.ConclusionsInvolvement in teaching (pre-pandemic) and practising in a rural setting (during the pandemic) positively influenced the recommendation of digital health technologies. Significant variation in recommending digital health technologies was present across countries.
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Journal articleLunova T, Hurndall K-H, Crespo R, et al., 2025,
Impact of the cost-of-living crisis on patient preferences towards virtual consultations
, Journal of Telemedicine and Telecare, Vol: 31, Pages: 1175-1185, ISSN: 1357-633XIntroductionSince 2021, the world has been facing a cost-of-living crisis which has negatively affected population health. Meanwhile, little is known about its impact on patients’ preferences to access care. We aimed to analyse public preference for the modality of consultation (virtual vs face-to-face) before and after the onset of crisis and factors associated with these preferences.MethodsAn online cross-sectional survey was administered to the public in the United Kingdom, Germany, Italy and Sweden. McNemar tests were conducted to analyse pre- and post-crisis differences in preferences; logistic regression was used to examine the demographic factors associated with public preferences.ResultsSince the onset of crisis, the number of people choosing virtual consultations has increased in the United Kingdom (7.0% vs 9.5% P < 0.001), Germany (6.6% vs 8.6%, P < 0.008) and Italy (6.0% vs 9.8%, P < 0.001). Before the crisis, a stronger preference for virtual consultations was observed in people from urban areas (OR 1.28, 95% CI 1.05–1.56), while increasing age was associated with a lower preference for virtual care (OR 0.966, 95% CI 0.961–0.972). Younger people were more likely to switch to virtual care, while change to face-to-face was associated with younger age and lower income (OR 1.34, 95% CI 1.12–1.62). Older adults were less likely to change preference.ConclusionsSince the onset of the cost-of-living crisis, public preference for virtual consultations has increased, particularly in younger population. This contrasts with older adults and people with lower-than-average incomes. The rationale behind patients’ preferences should be investigated to ensure patients can access their preferred modality of care.
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Journal articleGrass E, Pagel C, Crowe S, et al., 2025,
A stochastic optimisation model to support cybersecurity within the UK national health service
, JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, Vol: 76, Pages: 1379-1390, ISSN: 0160-5682 -
Journal articleRajput K, Darzi A, Ghafur S, 2025,
Overlooked and under-reported: the impact of cyberattacks on primary care in the UK National Health Service
, The Lancet Digital Health, Vol: 7, ISSN: 2589-7500 -
ReportRuma B, Jahanara R, Andrew M, et al., 2025,
Thriving Workplaces: How Employers Can Improve Productivity and Change Lives
, Geneva, Publisher: World Economic ForumRising burn-out rates, chronic diseases and shifting work trends underscore the urgent need for workplaces to promote employee well-being. This challenge presents a significant opportunity, not just for improving individual health outcomes but for driving up to $11.7 trillion in global economic value.
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Journal articleDarzi A, Lunova T, Howitt P, 2025,
We need to focus on local solutions for health inequalities
, BMJ: British Medical Journal, Vol: 388, Pages: r55-r55, ISSN: 0959-535X -
Journal articleBahadori S, Buckle P, Soukup Ascensao T, et al., 2025,
Evolving digital health technologies: aligning with and enhancing the National Institute for Health and Care Excellence Evidence Standards Framework
, JMIR mHealth and uHealth, Vol: 13, ISSN: 2291-5222The rapid advancement of artificial intelligence (AI)–driven diagnostics and wearable health technologies is transforming health care delivery by enabling real-time health monitoring and early disease detection. These innovations are catalyzing a shift toward personalized medicine, with interventions tailored to individual patient profiles with unprecedented precision. This paper examines the current National Institute for Health and Care Excellence (NICE) evidence standards framework (ESF) for digital health technologies (DHTs) and evaluates the challenges associated with integrating DHTs into existing health and care systems. A comprehensive review of the NICE ESF guidelines was conducted, alongside an evaluation of their applicability to emerging AI and wearable technologies. Key limitations and barriers were identified, with particular focus on the framework’s responsiveness to technologies that evolve through machine learning and real-world data integration. Our findings indicate that while the NICE ESF provides a structured approach for evaluating DHTs, it lacks the adaptability required for rapidly evolving innovations. The framework does not sufficiently incorporate real-world evidence or support continuous learning models, which are critical for the safe and effective deployment of AI-based diagnostics and wearables. To remain effective and relevant, the NICE ESF should transition to a dynamic, adaptive model co-designed with industry stakeholders. By embedding real-world evidence-based strategies and promoting transparency, efficiency, and collaborative innovation, the updated framework would better facilitate the integration of AI-driven diagnostics and wearables into health care systems, ultimately enhancing patient outcomes and optimizing health care delivery.
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Journal articleCerletti P, Joubert M, Oliver N, et al., 2025,
Evaluating digital health solutions in diabetes and the role of patient-reported outcomes: targeted literature review
, JMIR Diabetes, Vol: 10, ISSN: 2371-4379Background:Digital health solutions (DHS) are technologies with the potential to improve patient outcomes as well as change the way care is delivered. The value of DHS for people with diabetes is not well understood, nor is it clear how to quantify this value.Objective:We aimed to summarize current literature on the use of patient-reported outcome measures (PROMs) in diabetes as well as in selected guidelines for Health Technology Assessment (HTA) of DHS to highlight gaps, needs, and opportunities for the use of PROMs to evaluate DHS.Methods:We searched PubMed and ClinicalTrials.gov to establish which PROMs were most used in diabetes clinical trials and research between 1995 and May 2024. HTA guidelines on DHS evaluation from France, Germany, and the United Kingdom were also assessed to identify PROMs for DHS evaluation in general.Results:A total of 46 diabetes-specific PROMs and 16 nondiabetes-specific PROMs were identified. The most used diabetes-specific PROMs were (1) Diabetes Distress Scale, (2) Problem Areas in Diabetes, (3) Diabetes Empowerment Scale, (4) Diabetes Quality of Life, and (5) Diabetes Treatment Satisfaction Questionnaire. The most used nondiabetes-specific PROMs were Beck Depression Inventory, Sickness Impact Profile, EuroQol 5-Dimension, and Short Form 36-Item Health Survey. In HTA guidelines, the most prominent domain was health-related quality of life, for whose assessment there are well-established measures (Short Form 36-Item Health Survey and EuroQol 5-Dimension).Conclusions:Of the many PROMs used in diabetes care, few are currently used to evaluate DHS, and certain domains of value in diabetes are not mentioned in HTA guidelines. A common, comprehensive DHS-specific HTA framework could facilitate and accelerate the evaluation of DHS.
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Journal articleDaniore P, Hurndall K-H, Zavattaro F, et al., 2025,
Fostering public trust in national health data platforms: key considerations for public involvement activities for England and Switzerland
, DATA & POLICY, Vol: 7 -
ReportLawrance E, Newberry Le Vay J, El Omrani O, et al., 2024,
Global Agenda for Research and Action in Climate Change and Mental Health
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Journal articleGrailey K, Fernandez Crespo R, Howitt P, et al., 2024,
The cost of living crisis – how does it impact the health and life of individuals? A survey exploring perceptions in Italy, Germany, Sweden and the United Kingdom
, BMC Public Health, Vol: 24, ISSN: 1471-2458BackgroundThe Cost of Living Crisis (CoLC), a real term reduction in basic income, risks individuals being unable to afford essentials such as heat, food and clothing. The impact of the CoLC is disproportionate – with different population sub-groups more likely to be negatively affected. The objective of this survey was to evaluate the perceived impact of the CoLC on the life and health of participants across four European countries.MethodsA survey housing two questions to investigate the relationship between the CoLC and its perceived impact on life and health was developed. Four European countries (U.K., Sweden, Italy and Germany) took part via the YouGov platform. Logistic regression models were created for each country and question to evaluate which population characteristics were associated with a negative reported impact of the CoLC.ResultsA total of 8,152 unique individuals responded between 17th March and 30th March 2023. Each country was equally represented. Those aged 36–64 were more likely to report a negative impact of the CoLC on their life and health than younger participants (p < 0.001, p = 0.02 respectively). Across all countries, females were significantly more likely to report a negative impact on their life and health, however, when analysed according to country, in Sweden females were less likely to report a negative impact (p < 0.001). Those in lower income families or who reported poor health in the preceding 12 months were significantly more likely to report a negative impact of the CoLC on their life and health. There was no difference within the participant group on the reported impact of the CoLC based on location (rural vs. urban).ConclusionsWe demonstrate the disproportionate negative impact of the CoLC on both life and health in different population subgroups. Germany and Sweden appeared to be more resilient to the effects of the CoLC, particularly for certain population subgrou
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Journal articleMachleid F, Crespo RF, Flott K, et al., 2024,
Assessing public perceptions of virtual primary care during the COVID-19 pandemic in the UK, Germany, Sweden, and Italy: a topic modeling approach
, Sage Open, Vol: 14, ISSN: 2158-2440The COVID-19 pandemic has driven the transition from face-to-face visits to virtual care delivery. In this study, we explore patients’ perceptions of the benefits and challenges of using virtual primary care technologies during the pandemic, using machine learning approaches. A cross-sectional survey was conducted in August 2020 in Italy, Sweden, Germany, and the UK. Latent Dirichlet Allocation was used to identify themes of two open-ended questions. Comparisons between participant characteristics were made using Wilcoxon rank-sum test. 6,331 participants were included (51.7% female; 42.4% +55 years; 60.5% white ethnicity; 86.6% low literacy). The benefits extracted included: primary care delivery, infection control, reducing contacts, virtual care, timeliness, patient-doctor interaction, convenience, and safety. Participants from Sweden were most likely to mention “primary care delivery” (UK p = .007, IT p = .03, DE p < .001), from the UK “virtual care” (SE p < .001, IT p < .001, DE p < .001) and from Italy “patient-doctor interaction” (UK p < .001, SE p < .001, DE p < .001). The challenges included: diagnostic difficulties, physical examination, digital health risks, technical challenges, virtual care, data security and protection, and lack of personal contact. “Diagnostic difficulties” was most significantly mentioned in Sweden (UK p = .009, IT p < .001, DE p < .001), “virtual care” in the UK (IT p = .02, SE p = .001, DE p < .001), and “data security and protection” in Germany (UK p < .001, IT p = .019, SE p < .001). Our study reinforces the feasibility of using machine learning to explore large q
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ReportGuinto RR, Aruta JJBR, Co GS, et al., 2024,
Connecting Climate Minds climate change and mental health regional research and action agenda: Eastern and South-Eastern Asia
, Eastern and South-Eastern Asia research and action agenda -
Journal articleFranklin BD, Bartel R, Howitt P, 2024,
Avoiding harm through hearing our patients
, BMJ: British Medical Journal, Vol: 384, ISSN: 0959-535X -
Journal articleNeves AL, van Dael J, O'Brien N, et al., 2024,
Use and impact of virtual primary care on quality and safety: The public's perspectives during the COVID-19 pandemic
, Journal of Telemedicine and Telecare, Vol: 30, Pages: 393-401, ISSN: 1357-633XIntroductionWith the onset of Coronavirus disease (COVID-19), primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted the quality and safety of care. We aim to evaluate patient use of virtual primary care models during COVID-19, including change in uptake, perceived impact on the quality and safety of care and willingness of future use.MethodologyAn online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany. McNemar tests were conducted to test pre- and post-pandemic differences in uptake for each technology. One-way analysis of variance was conducted to examine patient experience ratings and perceived impacts on healthcare quality and safety across demographic characteristics.ResultsRespondents (n = 6326) reported an increased use of telephone consultations ( + 6.3%, p < .001), patient-initiated services ( + 1.5%, n = 98, p < 0.001), video consultations ( + 1.4%, p < .001), remote triage ( + 1.3, p < 0.001) and secure messaging systems ( + 0.9%, p = .019). Experience rates using virtual care technologies were higher for men (2.4 ± 1.0 vs. 2.3 ± 0.9, p < .001), those with higher literacy (2.8 ± 1.0 vs. 2.3 ± 0.9, p < .001), and participants from Germany (2.5 ± 0.9, p < .001). Healthcare timeliness and efficiency were the dimensions most often reported as being positively impacted by virtual technologies (60.2%, n = 2793 and 55.7%, n = 2,401, respectively), followed by effectiveness (46.5%, n =
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