Benefits and Limitations of Teledermatology in German Correctional Facilities: Cross-Sectional Analysis
Bibliographic record
Abstract
Background: Teledermatology consultations offer the advantage of rapid diagnosis and care. Since 2019, our institute at the University Medical Center Hamburg-Eppendorf has been part of an interdisciplinary team for teledermatology support in German prisons as an alternative to extramural transports of patients. Objective: This study aims to analyze the benefits and limitations of teledermatology for patients with limited access to medical specialties. Methods: We conducted a descriptive cross-sectional analysis of 651 teleconsultations from prisons from February 2020 to April 2023. All cases were performed in a store-and-forward (asynchronous mode) and optional hybrid live (synchronous) consultation for the patient or in-house staff. Results: The main advantage of this case processing was the avoidance of external transport. Of the 651 teleconsultations, 608 (93.4%) could be finalized with telemedical support and 43 (6.6%) required additional workup, including verifications of the type of tumors (n=22, 51%), which needed biopsies, and open cases that were inflammatory (n=11, 26%) or involved infectious skin conditions (n=5, 12%). Digital imaging of the skin lesions improved with the experience of the personnel but remained a challenge, with the photo quality depending on the technical devices or available broadband supply. Conclusions: Hybrid teledermatology consultation represents an effective and resource-saving method of providing specialized care to patients in situations with limited access to medical specialties. The video consultations with experts and exchange of knowledge about the cases presented opened the opportunity to support and train intramural colleagues. One of the main challenges remains the quality of digital imaging and transmission.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".