Integrating Technology into Urticaria Management: Telemedicine, Remote Monitoring and Patient-Centered Care
Abstract
1. Introduction
2. Burden of Disease and Patient Experience
3. Aim and Scope
4. Methods
5. Results
6. Telemedicine in Urticaria
6.1. Definition and Modalities
6.2. Clinical Applications of Telemedicine in Urticaria
6.3. Use of Social Media
7. Evolution of Telemedicine: Pre-COVID and Post-COVID
8. Telemonitoring of Biologic Therapies
9. Opportunities and Benefits
10. Limitation and Risks
11. Future Directions
12. Discussion
13. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| AI | Artificial intelligence |
| CIndU | Chronic inducible urticaria |
| CMS | Centers for medicare and medical service |
| CRUSE | Chronic urticaria self-evaluation |
| CSU | Chronic spontaneous urticaria |
| CU | Chronic urticaria |
| CU-Q2oL | Chronic urticaria quality of life questionnaire |
| HAE | Hereditary angioedema |
| ICT | Information and communication technologies |
| IT | Information technology |
| MHealth | Mobile health |
| PROs | Patient-reported outcomes |
| saMD | Software as a medical device |
| UAS | Urticaria activity score |
| UCARE | Urticaria centers of reference and excellence |
| UCT | Urticaria control test |
| WHO | World Health Organization |
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| Study (Year) [Ref.] | Country | Study Design | Tool | Clinical Focus | Sample Size | Type of Urticaria | Main Findings | Limitations |
|---|---|---|---|---|---|---|---|---|
| von Kiedrowski et al., (2025) [26] | Germany | Model-based simulation study | Patient journey modeling framework | Impact of educational and digital interventions on management pathway and guideline adherence in CSU | Not applicable (simulations based on secondary data) | Chronic spontaneous urticaria | Disease recognition, reduction in diagnostic/treatment delays, increase in guideline adherence, and improved patient care | Simulation model with assumptions, reliance on secondary data, no prospective patient data, limited generalizability |
| Viegas et al., (2025) [27] | Multinational (UCARE network) | Observational retrospective study | CRUSE® mobile health app (daily monitoring questionnaire) | Identification of predictors of adherence to an mHealth tool for monitoring chronic spontaneous urticaria | 2085 patients | Chronic spontaneous urticaria | Higher adherence associated with older age, male sex, European residence, and monoclonal antibody use | Self-reported diagnosis, potential selection bias of app users, limited clinical data |
| Sousa-Pinto et al., (2025) [31] | Multinational | Observational validation study | Digital visual analogue scales (VAS) in the CRUSE® mobile app | Validation of digital patient-reported outcome measures for monitoring disease activity and impact in CSU | 5938 patients | Chronic spontaneous urticaria | Very high intra-rater reliability (ICC > 0.95), and moderate-high test–retest reliability and responsiveness | App-based real-world data with self-reported disease, potential selection bias of digital tool users, limited clinical verification, observational design |
| Pereverzina et al. (2023) [37] | Russia | Cross-sectional online survey | Patient questionnaires during COVID-19 | Impact of pandemic restrictions on urticaria disease control and healthcare access | 111 patients | Chronic spontaneous urticaria | Reduced access to specialists and treatment interruptions were reported | Small sample size; self-reported outcomes; pandemic-specific context |
| Neisinger et al. (2024) [42] | Multinational (UCARE network) | Observational descriptive study | CRUSE® mobile health application | Digital monitoring and management of chronic spontaneous urticaria | 2540 app users | Chronic spontaneous urticaria | App enabled recording of symptoms, disease activity and treatments; demonstrated feasibility of digital monitoring | Self-reported data; observational design; no clinical outcome comparison |
| Hindelang et al. (2025) [57] | Germany | Prospective pilot study | Telemedicine platforms | Acceptability and utilization of a digital health model for CSU | 24 patients | Chronic spontaneous urticaria | Disease control remained stable while quality of life improved. All physicians found the digital application reliable and timesaving | Small sample size; pilot study |
| Edwards et al. (2026) [63] | United States (Spanish-speaking) | Pilot feasibility study | WhatsApp educational intervention | Digital education for self-management in CSU | 30 patients | Chronic spontaneous urticaria | WhatsApp-based educational program was feasible and well accepted among Spanish-speaking CSU patients | Small pilot sample; short follow-up; no clinical outcome comparison |
| Ali et al. (2024) [75] | Denmark | Cross-sectional observational survey | Patient-taken smartphone photographs | Clinical usefulness of photographs taken by CU patients for dermatologic evaluation | 148 patients | Chronic urticaria | Patient-taken photos can support remote assessment and clinical diagnosis of CU | Observational design, survey-based without longitudinal outcomes, image quality variability |
| Cherrez-Ojeda et al. (2021) [67] | Multinational (UCARE network) | Cross-sectional observational survey | 23-item questionnaire from the UCARE CURICT study assessing patient interest in urticaria monitoring apps | Patient interest and preferences regarding use of mobile apps to monitor chronic urticaria disease activity and control | 1841 patients | Chronic urticaria (CSU and CIndU) | Over half of patients were interested in using apps to monitor disease activity and control; interest was higher in females and those with both types of urticaria versus CSU alone | Self-reported data; hypothetical acceptance |
| Cherrez-Ojeda et al. (2021) [78] | Multinational (UCARE network) | Cross-sectional survey | 23-item questionnaire on Information and communication technologies (ICT) | Interest of CU patients in ICT tools for healthcare | 1841 patients | Chronic urticaria | High interest among patients in using smartphones and digital tools for disease management | Self-reported data, variation in ICT access across regions, potential selection bias of participants at UCARE centers |
| Zysk & Trzeciak (2023) [77] | Poland | Cross-sectional online survey | Online questionnaire for members of Facebook urticaria group | Characterization of chronic urticaria clinical features and self-reported comorbidities in affected patients | 102 respondents | Chronic urticaria | Web-based survey identified disease burden and common comorbidities | Self-reported data; selection bias; predominance of female participants |
| Maurer et al. (2020) [80] | Multinational (UCARE network) | Cross-sectional survey | 23-item questionnaire on Information and communication technologies (ICT) | Usage frequency, quality, and relevance of ICTs for health and chronic urticaria information among patients | 1841 patients | Chronic urticaria | ICT use is extremely high; web browsers and messaging platforms are most frequently used for health and CU-specific information | Self-reported data; cross-sectional design |
| Mondal et al. (2024) [76] | India | Cross-sectional data audit | Facebook, LinkedIn and Twitter analysis | Analysis of patients’ knowledge, attitudes, and practices toward urticaria medication treatment as reflected on social media platforms | 300 posts | Urticaria | Insights into patient perceptions, concerns, and misinformation about treatments, highlighting gaps in patient knowledge and potential targets for education and support interventions online | Indirect data source, potential selection bias, lack of clinical verification, inability to infer clinical outcomes from online discourse |
| Schielein et al. (2021) [79] | Germany | Observational survey | Online questionnaire assessing Internet addiction and healthcare utilization behaviors | Exploration of Internet addiction prevalence and its association with healthcare use | 1686 patients | Psoriasis and chronic urticaria | Internet addiction as comorbidity, patient may exhibit problematic online health information-seeking behaviors, potentially impacting patient-physician interactions and healthcare utilization | Self-reported data, potential selection bias, lack of clinical verification of urticaria diagnoses |
| Kiefer et al. (2025) [74] | Multinational | Cross-sectional patient survey | Disease-specific Facebook group, Online questionnaire | Treatment patterns, patient-reported disease burden, and perceived effectiveness of therapies, QoL assessment | 112 patients | Solar urticaria | Survey identified treatment strategies, data on disease severity, quality of life and highlighted unmet therapeutic needs | Self-reported data, diagnosis not uniformly confirmed, selection bias |
| Ozturk et al., (2021) [40] | Turkey | Cross-sectional survey study | Telemedicine during COVID-19 | Changes in allergy practice and patient management during the COVID-19 pandemic | 183 allergists | Allergic diseases including urticaria | Significant shift toward remote consultations and telemedicine | Pandemic-specific context |
| Choi et al. (2025) [66] | Singapore | Multicenter, randomized controlled, double-blind clinical trial protocol | Digital psychotherapeutic mobile application | Efficacy and process evaluation of a psychotherapeutic app to reduce symptom burden and improve quality of life in patients with chronic inflammatory skin diseases | Unknown | Dermatological diseases including urticaria | Protocol aimed to assess change in Dermatology Life Quality Index and secondary patient-reported outcomes, disease severity, treatment adherence, and implementation engagement; outcomes pending future trial results | Protocol only; results not yet available |
| Mu et al. (2021) [45] | China | Retrospective study | Mobile application–based tele dermatology platform | Tele dermatology service utilization during COVID-19 | 698 patients | Dermatological diseases including urticaria | Tele dermatology ensured continuity of dermatologic care during the pandemic | Small sample size; single-country study; the accuracy of diagnosis was not confirmed clinically; age-standardization was not performed |
| Lee et al. (2021) [51] | Taiwan | Observational descriptive study | Live-interactive tele dermatology program | Feasibility and clinical utility of teledermatology for dermatologic diagnosis and management in underserved rural areas | 426 consultations | Dermatological diseases including urticaria | Teledermatology enabled remote diagnosis and management of multiple skin diseases improving dermatologic care access in rural regions | Single-program experience in Taiwan, lack of group control, heterogeneous dermatologic conditions |
| Chua et al. (2026) [64] | Singapore | Pilot study | MindMySkin app | Digital psychological intervention for dermatologic symptom burden | 27 participants | Dermatological diseases including urticaria | Intervention demonstrated high acceptability and usability for self-management and psychological support | Early-phase study; mixed dermatologic diseases |
| Song et al., (2024) [32] | China | Comparative study using a standardized patient methodology | Telemedicine platforms | Assessment of quality of telemedicine care delivered by public vs. private online platforms | 594 physician-patient interactions by 10 standardized patients | Dermatological diseases including urticaria | Private telemedicine platforms: higher quality in better checklist adherence, more accurate diagnosis, more appropriate prescriptions, more patient-centered communication | Limited clinical scenarios, results specific to Chinese telemedicine platforms, potential lack of generalizability |
| Tool Category | Clinical Application | Evidence Summary | Limitations |
|---|---|---|---|
| Mobile health applications (mHealth) | Remote monitoring of disease activity, symptom tracking, and treatment adherence using validated patient-reported outcome measures (e.g., UAS7, UCT) | Real-world studies demonstrate good feasibility, high patient acceptance, and improved longitudinal monitoring of disease control |
|
| Teleconsultation platforms | Remote clinical follow-up, treatment adjustment, and specialist consultation | Demonstrated clinical utility for follow-up of chronic inflammatory skin diseases, including urticaria |
|
| Secure messaging tools | Rapid patient–physician communication reporting of symptom changes | Improves communication efficiency, continuity of care, and clinical decision-making |
|
| Electronic patient-reported outcome (ePRO) systems | Standardized remote assessment of disease activity and treatment response | Validated tools allow reliable remote disease monitoring and support treatment optimization |
|
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Topa, E.; Cristallo, M.; Rizzi, A.; Lamacchia, D.; Gamberale, S.; Caruso, C.; Rossi, O.; Di Leo, E.; Bova, M.; Nettis, E. Integrating Technology into Urticaria Management: Telemedicine, Remote Monitoring and Patient-Centered Care. Biomedicines 2026, 14, 753. https://doi.org/10.3390/biomedicines14040753
Topa E, Cristallo M, Rizzi A, Lamacchia D, Gamberale S, Caruso C, Rossi O, Di Leo E, Bova M, Nettis E. Integrating Technology into Urticaria Management: Telemedicine, Remote Monitoring and Patient-Centered Care. Biomedicines. 2026; 14(4):753. https://doi.org/10.3390/biomedicines14040753
Chicago/Turabian StyleTopa, Ester, Mattia Cristallo, Angela Rizzi, Donatella Lamacchia, Sara Gamberale, Cristiano Caruso, Oliviero Rossi, Elisabetta Di Leo, Maria Bova, and Eustachio Nettis. 2026. "Integrating Technology into Urticaria Management: Telemedicine, Remote Monitoring and Patient-Centered Care" Biomedicines 14, no. 4: 753. https://doi.org/10.3390/biomedicines14040753
APA StyleTopa, E., Cristallo, M., Rizzi, A., Lamacchia, D., Gamberale, S., Caruso, C., Rossi, O., Di Leo, E., Bova, M., & Nettis, E. (2026). Integrating Technology into Urticaria Management: Telemedicine, Remote Monitoring and Patient-Centered Care. Biomedicines, 14(4), 753. https://doi.org/10.3390/biomedicines14040753

