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The mHealth field has been reproached for arguing that apps warrant digital exceptionalism given the iterative nature of their design and the prohibitive cost of trials compared with their perceived level of risk.
“Indeed, the mHealth field has been reproached for arguing that apps warrant digital exceptionalism given the iterative nature of their design and the prohibitive cost of trials compared with their perceived level of risk [91].”
From A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review (2019) · cites this paper as [91]
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Kim, D. W., Jang, H. Y., Kim, K. W., Shin, Y., & Park, S. H. (2019) · Korean Journal of Radiology · doi:10.3348/kjr.2019.0025 · Cited by 459 · see citing works
“Our results reveal that most recently published studies reporting the performance of AI algorithms for diagnostic analysis of medical images did not have design features that are recommended for robust validation of the clinical performance of AI algorithms, confirming the worries that premier journals have recently r…”
BackgroundResultDesigning deep learning studies in cancer diagnostics
Kleppe, A., Skrede, O.-J., Raedt, S. D., Liestøl, K., Kerr, D. J., & Danielsen, H. E. (2021) · Nature reviews. Cancer · doi:10.1038/s41568-020-00327-9 · Cited by 318 · see citing works
What should medical students know about artificial intelligence in medicine?
Park, S. H., Do, K.-H., Kim, S., Park, J. H., & Lim, Y.-S. (2019) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2019.16.18 · Cited by 196 · see citing works
Larson, D. B., Harvey, H., Rubin, D. L., Irani, N., Tse, J. R., & Langlotz, C. P. (2021) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2020.09.060 · Cited by 198 · see citing works
Safety of patient-facing digital symptom checkers
Fraser, H., Coiera, E. W., & Wong, D. (2018) · The Lancet · doi:10.1016/s0140-6736(18)32819-8 · Cited by 182 · see citing works
HCI for health and wellbeing: Challenges and opportunities
Blandford, A. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.06.007 · Cited by 152 · see citing works
Evaluating artificial intelligence in medicine: phases of clinical research
Park, Y., Jackson, G. P., Foreman, M. A., Gruen, D., Hu, J., & Das, A. K. (2020) · JAMIA Open · doi:10.1093/jamiaopen/ooaa033 · Cited by 150 · see citing works
Unsworth, H., Dillon, B., Collinson, L., Powell, H., Salmon, M., Oladapo, T., Ayiku, L., Shield, G., Holden, J., Patel, N., et al. (2021) · Digital Health · doi:10.1177/20552076211018617 · Cited by 137 · see citing works
Pham, Q., Graham, G., Carrion, C., Morita, P. P., Seto, E., Stinson, J. N., & Cafazzo, J. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/11941 · Cited by 131 · see citing works
“Indeed, the mHealth field has been reproached for arguing that apps warrant digital exceptionalism given the iterative nature of their design and the prohibitive cost of trials compared with their perceived level of risk [91].”
BackgroundHewitt, S., Sephton, R., & Yeowell, G. (2020) · Journal of Medical Internet Research · doi:10.2196/15617 · Cited by 116 · see citing works
Why does the NHS struggle to adopt eHealth innovations? A review of macro, meso and micro factors
Asthana, S., Jones, R. B., & Sheaff, R. (2019) · BMC Health Services Research · doi:10.1186/s12913-019-4790-x · Cited by 113 · see citing works
“In July 2018, the Lancet published an editorial, calling for a clearer assessment framework in the UK for digital health, “to differentiate efficacious digital products from commercial opportunism” [40].”
BackgroundKim, J., & Heo, W. (2021) · Information Technology and People · doi:10.1108/itp-04-2019-0173 · Cited by 106 · see citing works
Wykes, T., & Schueller, S. M. (2019) · Journal of Medical Internet Research · doi:10.2196/12390 · Cited by 95 · see citing works
“The goal of these principles is to operationalize efforts that can be made by app marketplaces to answer calls for better oversight and backing up products with data and research [3,5,6].”
What is an appropriate level of evidence for a digital health intervention?
Greaves, F., Joshi, I., Campbell, M., Roberts, S., Patel, N., & powell, J. A. (2018) · The Lancet · doi:10.1016/s0140-6736(18)33129-5 · Cited by 92 · see citing works
Health technology assessment frameworks for eHealth: A systematic review
Vis, C., Bührmann, L., Riper, H. M., & Ossebaard, H. C. (2020) · International Journal of Technology Assessment in Health Care · doi:10.1017/s026646232000015x · Cited by 83 · see citing works
“eHealth is debated to diverge from traditional health care due to its technological properties, speed of development, and complexity of implementation in existing routine care, as eHealth often impacts interlocking levels of organizational, staff, and client behaviors, beliefs, and norms (15;16).”
BackgroundWyatt, J. C. (2018) · BMC Medicine · doi:10.1186/s12916-018-1211-7 · Cited by 61 · see citing works
The future of community psychiatry and community mental health services
Rosen, A., Gill, N. S., & Salvador‐Carulla, L. (2020) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000620 · Cited by 91 · see citing works
“Lancet 2018; 392:1495–1497.”
Distinguishing features in the assessment of mHealth apps
Tarricone, R., Petracca, F., Ciani, O., & Cucciniello, M. (2021) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1080/14737167.2021.1891883 · Cited by 62 · see citing works
“Despite many have supported the case for digital excep-tionalism [40], this should not turn into a generalized amendment for mHealth apps, whose future deployment cannot be justified through social enthusiasm, economic circumstances, and political expediency only but should anyway be supported by…”
BackgroundCucciniello, M., Petracca, F., Ciani, O., & Tarricone, R. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00517-1 · Cited by 73 · see citing works
Gansel, X., Mary, M., & van Belkum, A. (2019) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-019-03501-6 · Cited by 53 · see citing works
Stakeholder Perceptions of the Safety and Assurance of Artificial Intelligence in Healthcare
Sujan, M. A., White, S., Habli, I., & Reynolds, N. (2022) · Safety Science · doi:10.1016/j.ssci.2022.105870 · Cited by 58 · see citing works
Wang, X., Xuan, Z., Storella, T. H., & Zhou, X. (2020) · Social Science & Medicine · doi:10.1016/j.socscimed.2020.113035 · Cited by 40 · see citing works
Rapid response to crisis: Health system lessons from the active period of COVID-19
Salvador‐Carulla, L., Rosenberg, S. P., Mendoza, J. A., & Tabatabaei‐Jafari, H. (2020) · Health Policy and Technology · doi:10.1016/j.hlpt.2020.08.011 · Cited by 45 · see citing works
Private Video Consultation Services and the Future of Primary Care
Salisbury, C., Quigley, A., Hex, N., & Aznar, C. (2020) · Journal of Medical Internet Research · doi:10.2196/19415 · Cited by 38 · see citing works
Blockchain in health care: hype, trust, and digital health
Leeming, G., Ainsworth, J. D., & Clifton, D. A. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30948-1 · Cited by 37 · see citing works
Applications of Machine Learning in Bone and Mineral Research
Kong, S. H., & Shin, C. S. (2021) · Endocrinology and Metabolism · doi:10.3803/enm.2021.1111 · Cited by 36 · see citing works
“However, despite the enthusiasm about the use of AI for medicine, the lack of sufficient and appropriate validation of the algorithms has been a concern, and it is called ‘digital exception-alism’ [69,70].”
BackgroundEl-Osta, A. A. R., Webber, I., Alaa, A., Bagkeris, E., Mian, S., Sharabiani, M. T. A., & Majeed, A. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053566 · Cited by 30 · see citing works
Future of Personalized Cardiovascular Medicine
Califf, R. M. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.09.079 · Cited by 35 · see citing works
The Role of Artificial Intelligence in Digital Health
Chang, A. C. (2019) · Health informatics · doi:10.1007/978-3-030-12719-0_7 · Cited by 41 · see citing works
Can Apple and Google continue as health app gatekeepers as well as distributors and developers?
Sadare, O., Melvin, T., Harvey, H., Vollebregt, E., & Gilbert, S. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00754-6 · Cited by 31 · see citing works
Using Health Information Technology to Support Use of Patient-Reported Outcomes in Rheumatology
Gandrup, J., & Yazdany, J. (2019) · Rheumatic Disease Clinics of North America · doi:10.1016/j.rdc.2019.01.007 · Cited by 23 · see citing works
Castro, R., Alves, M. R., de Oliveira, C. C. M., Romero, C., Perazzo, H., Simjanoski, M., Kapciznki, F., Balanzá‐Martínez, V., & Boni, R. B. D. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2021.735624 · Cited by 19 · see citing works
Dewey, M., Bosserdt, M., Dodd, J. D., Thun, S., & Kressel, H. Y. (2019) · Radiology · doi:10.1148/radiol.2019181796 · Cited by 22 · see citing works
Mahmood, U. A., Shrestha, R., Bates, . D. B., Mannelli, L., Corrias, G., Erdi, Y. E., & Kanan, C. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.671015 · Cited by 21 · see citing works
The Role of Artificial Intelligence in Digital Health
Chang, A. C. (2023) · Health informatics · doi:10.1007/978-3-031-33902-8_6 · Cited by 18 · see citing works
Description of an online hospital platform, China
Wu, D., Hesketh, T. M., Shu, H., et al. (2019) · Bulletin of the World Health Organization · doi:10.2471/blt.18.226936 · Cited by 19 · see citing works
The Digital Phenotyping Project: A Psychoanalytical and Network Theory Perspective
Potier, R. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01218 · Cited by 22 · see citing works
“In a recent issue of The Lancet , an editorial was published that questions the reality of digital medicine in its evolutions and promises (Lancet, 2018).”
BackgroundPrinciples for evaluating the clinical implementation of novel digital healthcare devices
Park, S. H., Do, K., Choi, J., Sim, J. S., Yang, D. M., Eo, H., Woo, H., Lee, J. M., Jung, S. E., & Oh, J. H. (2018) · Journal of Korean Medical Association · doi:10.5124/jkma.2018.61.12.765 · Cited by 18 · see citing works
“이러한 디지털 의료 기기들은, 기존의 의약품이나 수술적 치료기기 등에 적용되 는 전통적인 임상검증 방법을 그대로 적용하기 어려울 수 있어 이 과정에서 혼선이 초래되고 있다[5,6].”
InfluentialSmits, M., Ludden, G., Verbeek, P., & van Goor, H. (2022) · Interactive Journal of Medical Research · doi:10.2196/39323 · Cited by 17 · see citing works
Määttä, J. H., Lindell, R., Hayward, N., Martikainen, S., Honkanen, K., Inkala, M., Hirvonen, P., & Martikainen, T. J. (2023) · JMIR Medical Informatics · doi:10.2196/46760 · Cited by 19 · see citing works
Jacobs, F., D’Amico, S., Zazzetti, E., Gaudio, M., Benvenuti, C., Saltalamacchia, G., Gerosa, R., Gentile, D., Lasagna, A., Pedrazzoli, P., et al. (2024) · Digital Health · doi:10.1177/20552076241288821 · Cited by 17 · see citing works
“12,109 Categorization and recognition The world of digital health is vast, and a comprehensive categorization is essential.”
BackgroundHalminen, O., Chen, A., Tenhunen, H., & Lillrank, P. M. (2020) · Health Services Management Research · doi:10.1177/0951484820971447 · Cited by 15 · see citing works
“Therefore, the established standards and processes for evaluating new drugs or devices may fail to keep up with the dynamic nature of digital health development and delivery.(15,16) Especially for the companies, existing summative evaluation models, such as the widely used RE-AIM model,(17) may fail to bring value in…”
BackgroundNjoku, C., Green, S. A., Sathyamoorthy, G., Patel, N., & POTTS, H. W. W. (2023) · Digital Health · doi:10.1177/20552076231173303 · Cited by 14 · see citing works
“In July 2018, The Lancet published an editorial, calling for a clearer assessment framework in the UK for DH, to ‘differentiate efficacious digital products from commercial opportunism’.(39) Overall, it is clear that APs have a major role in connecting and brokering relationships between entrepreneurs, individuals and…”
BackgroundZawati, M. H., & Lang, M. (2024) · Journal of Medical Internet Research · doi:10.2196/50344 · Cited by 13 · see citing works
On Mobile Health, Empowerment, and the Limits of Task Shifting in Healthcare
Gray, J. (2025) · The American Journal of Bioethics · doi:10.1080/15265161.2025.2554771 · Cited by 9 · see citing works
“Systems like DiGA recognize what we have long known, that digital exceptionalism, the practice of exempting digital health devices from scrutiny is dangerous to patients (The Lancet 2018), and not a source of empowerment for them.”
A machine learning method for precise detection of spine bone mineral density
Wang, J., Yang, G., Liu, S., Qiao, R., Cao, Y., Fan, B., Yang, H., & Lyu, F. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.04.059 · Cited by 9 · see citing works
Gonsalves, L., Wangari, W., Schroeder, M., Mwaisaka, J., & Gichangi, P. (2019) · JMIR mhealth and uhealth · doi:10.2196/13005 · Cited by 8 · see citing works
“Most recently, a Lancet editorial cautioned against “digital exceptionalism” and highlighted the risk to patients and the health system if we fail to robustly evaluate digital health interventions [30].”
BackgroundPersonalized Wellness Past and Future
Kanter, M., & Desrosiers, A. (2019) · Nutrition Today · doi:10.1097/nt.0000000000000354 · Cited by 8 · see citing works
Digitally enabled primary care: the emperor’s new clothes?
Atherton, H. (2019) · British Journal of General Practice · doi:10.3399/bjgp19x705125 · Cited by 7 · see citing works
Application progress and potential of digital medicine in pediatric orthopedics
Wang, Y., Fan, M., Zaman, Q., & Zheng, P. (2021) · Digital Medicine · doi:10.4103/digm.digm_11_21 · Cited by 7 · see citing works
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AI Powered SocietyPreprint
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Finance, data and technology initiatives for noncommunicable disease control
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Digital medicine needs to work
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Editorial: Trends in Digital Medicine
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Digital Therapeutics: Scientific, Technological, and Regulatory Challenges
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Smart Start — Designing Powerful Clinical Trials Using Pilot Study Data
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BackgroundHealth, Digital Health and Decision Support: Sisyphus and Pandora
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Validation Study of a Value-Based Digital Health Questionnaire
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Technology exceptionalism in medicine: Is it time to rethink the paradigm?
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On Transforming Competency in Clinical Decision-Making: A Mission Possible?
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- Authors
- Lancet, T.
- Corresponding author
- The Lancet
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 392
- Issue
- 10142
- Pages
- 95
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W4242780009
- Cited by
- 73
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 7 · 2023: 10 · 2022: 7 · 2021: 9 · 2020: 12 · 2019: 16 · 2018: 8
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- digital medicine, NHS App, online appointment booking, repeat prescriptions, health technology adoption, National Health Service, NHS Digital
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