Digital health interventions in dermatology—Mapping technology and study parameters of systematically identified publications
Open accessAbstract
Digital health interventions (DHI) potentially improve the efficiency and effectiveness of dermatological care. Currently, an overview clustering and characterizing the evidence on DHIs is missing. This systematic mapping of the literature aims to analyse published research on DHIs in dermatology to identify trends and gaps in research. For this purpose, a systematic search of the MEDLINE database was conducted in August 2022 to identify original publications on DHIs in dermatology. Data on country, targeted audience, DHI category, indication, outcome parameter and study design were extracted. Out of 12,009 records identified in MEDLINE, 403 studies were included in the final analysis. Studies on DHIs mainly performed in western countries, headed by the United States ( n = 133), Germany ( n = 32) and Spain ( n = 23). Of all identified DHIs, 261 targeted healthcare providers (HCP), 66 clients (e.g. patients, caregivers, healthy individuals) and 67 both clients and HCPs. A majority of DHIs focussed on establishing a diagnosis ( n = 254). Every other study analysed store‐and‐forward teledermatology ( n = 187), followed by artificial intelligence applications for image analysis ( n = 65). The most often analysed DHI category for clients was a support of health behaviour change ( n = 31). Monitoring of clients was targeted by 77 studies. Skin cancer ( n = 148), wounds ( n = 29) and psoriasis ( n = 29) were the most targeted indications by DHIs. Most studies analysed diagnostic performance ( n = 166), fewer studies analysed acceptance ( n = 92) and effectiveness ( n = 98). Usability ( n = 32) and efficiency ( n = 36) were investigated only to a small extent. Studies on DHIs in dermatology have focused on teledermatology and AI applications, with an emphasis on skin cancer diagnosis. Apart from that, a range of DHIs for different user groups, purposes and indications were identified, demonstrating the broad potential for DHIs in dermatology. Further research with a wider set of outcome parameters is needed to fully understand the potential of DHIs and ensure their sustainable implementation into dermatological care.
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Digital health services present numerous opportunities for implementation in chronic urticaria management.
“This situation presents numerous opportunities for the implementation of digital health services in CU management [21, 22].”
From Acceptance and perceived usefulness of digital health services in the management of chronic urticaria: a survey of patients and physicians (2025) · cites this paper as [22]
Cites
Skivington, K., Matthews, L., Simpson, S. A., Craig, P., Baird, J., Blazeby, J. M., Boyd, K. A., Craig, N., French, D. P., McIntosh, E., et al. (2021) · BMJ · doi:10.1136/bmj.n2061 · Cited by 5,808 · see citing works
Basch, E., Deal, A. M., Kris, M. G., Scher, H. I., Hudis, C. A., Sabbatini, P., Rogak, L., Bennett, A. V., Dueck, A. C., Atkinson, T. M., et al. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.63.0830 · Cited by 2,593 · see citing works
Standards of Evidence: Criteria for Efficacy, Effectiveness and Dissemination
Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., Mościcki, E. K., Schinke, S., Valentine, J. C., & Ji, P. (2005) · Prevention Science · doi:10.1007/s11121-005-5553-y · Cited by 1,338 · see citing works
What Is eHealth (3): A Systematic Review of Published Definitions
Oh, H., Jadad, A., Rizo, C., Enkin, M., Powell, J., & Pagliari, C. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e1 · Cited by 1,015 · see citing works
Clinical decision support in the era of artificial intelligence
Shortliffe, E. H., & Sepúlveda, M. J. (2018) · JAMA · doi:10.1001/jama.2018.17163 · Cited by 920 · see citing works
Global Skin Disease Morbidity and Mortality: An Update From the Global Burden of Disease Study 2013
Karimkhani, C., Dellavalle, R. P., Coffeng, L. E., Flohr, C., Hay, R. J., Langan, S. M., Nsoesie, E. O., Ferrari, A. J., Erskine, H. E., Silverberg, J. I., et al. (2017) · JAMA Dermatology · doi:10.1001/jamadermatol.2016.5538 · Cited by 742 · see citing works
Barriers and facilitators to the implementation of eHealth services: systematic literature analysis
Schreiweis, B., Pobiruchin, M., Strotbaum, V., Suleder, J., Wiesner, M., & Bergh, B. (2019) · Journal of Medical Internet Research · doi:10.2196/14197 · Cited by 354 · cited 2× · see citing works
“41– 43 Efficiency, including cost and time efficiency, are a key promise of DHIs 4 and will affect decision-making for adoption on an individual HCP level as well as the healthcare system level.”
BackgroundTechnology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement
Nadal, C., Sas, C., & Doherty, G. (2020) · Journal of Medical Internet Research · doi:10.2196/17256 · Cited by 320 · see citing works
Haggenmüller, S., Maron, R. C., Hekler, A., Utikal, J. S., Barata, C., Barnhill, R. L., Beltraminelli, H., Berking, C., Betz-Stablein, B., Blum, A., et al. (2021) · European Journal of Cancer · doi:10.1016/j.ejca.2021.06.049 · Cited by 267 · see citing works
Teledermatology for the Diagnosis and Management of Skin Cancer: A Systematic Review
Finnane, A., Dallest, K., Janda, M., & Soyer, H. P. (2017) · JAMA Dermatology · doi:10.1001/jamadermatol.2016.4361 · Cited by 257 · see citing works
Philippi, P., Baumeister, H., Apolinário-Hagen, J., Ebert, D. D., Hennemann, S., Kott, L., Lin, J., Messner, E.-M., & Terhorst, Y. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100459 · Cited by 200 · cited 1× · see citing works
“40 Inclusion of the parameter in future research can hence only be endorsed.”
BackgroundArmstrong, A. W., Johnson, M. A., Lin, S., Maverakis, E., Fazel, N., & Liu, F.-T. (2015) · JAMA Dermatology · doi:10.1001/jamadermatol.2014.2299 · Cited by 90 · see citing works
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Hindelang, M., Zink, A., Knitza, J., Darkow, R., Welcker, M., Biedermann, T., May, S., & Muehlensiepen, F. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-13043-7 · Cited by 4 · see citing works
“This situation presents numerous opportunities for the implementation of digital health services in CU management [21, 22].”
- Authors
- Reinders, P., Augustin, M., Kirsten, N., Fleyder, A., & Otten, M.
- Affiliations
- University Medical Center Hamburg-Eppendorf (DE)
- Corresponding author
- Reinders, Patrick
- Venue
- Journal of the European Academy of Dermatology and Venereology
- Publisher
- Wiley
- Published
- 2023-08-16
- Volume
- 37
- Issue
- 12
- Pages
- 2440-2449
- ISSN
- 0926-9959 (ISSN-L)
- 1468-3083
- OpenAlex
- W4385477636
- Cited by
- 19
- References
- 12
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 6
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of the European Academy of Dermatology and Venereology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- Novartis
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Keywords
- digital health interventions, dermatology, teledermatology, store-and-forward telemedicine, artificial intelligence, skin cancer diagnosis, wound care, psoriasis, health behavior change, patient monitoring, diagnostic performance, technology acceptance, usability, research gaps
- MeSH terms
- Artificial Intelligence, Dermatology, Humans, Psoriasis, Skin Neoplasms, Telemedicine
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