Evidence map›Paper›PMID 42434370›Full record

ArticleFrontiers in digital health2026

Integration of a tele-dermatology model for Epidermolysis Bullosa improves patient outreach: a before and after observational study.

Aditya Viswanath, Divya Gupta, Manoj Srinivasa, Tim Jose, Silji Jibins, Charles Mendith, Utsav Munnoli, Asha Jubba, Guruduta Baraka, Ravi Hiremagalore

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Aditya ViswanathLeicester Medical School, University of Leicester, Leicester, United Kingdom.
Divya GuptaDepartment of Dermatology, Dr. B R Ambedkar Medical College and Hospital, Bengaluru, India.
Manoj SrinivasaDepartment of Dermatology Sri Madhusudan Sai Institute of Medical Sciences and Research, Chikkaballapur, Karnataka, India.
Tim JoseDepartment of Dermatology Sri Madhusudan Sai Institute of Medical Sciences and Research, Chikkaballapur, Karnataka, India.
Silji JibinsCentre of Human Genetics, Bengaluru, Karnataka, India.
Charles MendithCentre of Human Genetics, Bengaluru, Karnataka, India.
Utsav MunnoliCentre of Human Genetics, Bengaluru, Karnataka, India.
Asha JubbaDermatopathologist, Delhi Dermath Laboratory, New Delhi, India.
Guruduta BarakaDepartment of Human Genetics National, NIMHANS, Bangalore, India.
Ravi HiremagaloreDepartment of Dermatology, University of Alabama, Birmingham, AL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A hub-and-spokes model strengthens care for Epidermolysis Bullosa by combining specialized expertise with community clinics. Genetic and genomic diagnostics power personalized treatment, whilst telemedicine improves access and affordability of patient care. This integrated system delivers equitable and patient-centered care, reducing burden and improving outcomes for individuals with rare genetic diseases. Methods: This was a before-and-after observational study conducted at the Centre for Human Genetics in Bangalore, between January 2020 and August 2025. Patients with confirmed or suspected Epidermolysis Bullosa (EB) were referred, either by spoke-level practitioners or family members, to a teleconsultation with specialized dermatologists. Clinical data, including family history, were securely documented, and a multidisciplinary team was engaged when further intervention was required. Continuity of care was facilitated through a HIPAA-compliant mobile application, enabling families to maintain communication and follow-up. The impact of the program was evaluated by analyzing its geographical reach, patient evaluation, and comparative medical costs before and after implementation. Results: Developing a standardized diagnostic framework and care pathways for the heterogeneous genetic condition Epidermolysis Bullosa (EB) across a large geographic region addressed a critical gap in the healthcare system. Within our program, 271 patients were enrolled, comprising EB simplex ( Conclusion: Patient care for Epidermolysis Bullosa has focused beyond economic benefits; the model demonstrates how technology can enhance equity in healthcare delivery. Telemedicine and genomic technologies bridge critical gaps in specialized care, particularly for complex conditions such as EB across wide geographic regions. A centralized diagnostic and care framework across wide geographic regions allows for statistically significant reductions in direct medical costs.

Indexed as

accessible carecost-analysisdigital healthepidermolysis bullosaglobal healthIndiarare diseasetele-dermatology

Identifiers

PMID42434370
PMCPMC13353098

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.