Comparative effectiveness study of face-to-face and teledermatology workflows for diagnosing skin cancer.


Journal

Journal of the American Academy of Dermatology
ISSN: 1097-6787
Titre abrégé: J Am Acad Dermatol
Pays: United States
ID NLM: 7907132

Informations de publication

Date de publication:
Nov 2019
Historique:
received: 03 07 2018
revised: 11 01 2019
accepted: 19 01 2019
pubmed: 11 2 2019
medline: 31 3 2020
entrez: 11 2 2019
Statut: ppublish

Résumé

The effectiveness and value of teledermatology and face-to-face workflows for diagnosing lesions are not adequately understood. We compared the risks of biopsy and cancer diagnosis among 2 face-to-face workflows (direct referral and roving dermatologist) and 4 teledermatology workflows. Retrospective study of 59,279 primary care patients presenting with a lesion from January through June 2017. One teledermatology workflow achieved high-resolution images with use of a dermatoscope-fitted digital camera, a picture archiving and communication system, and image retrieval to a large computer monitor (in contrast to a smartphone screen). Compared with direct referral, this workflow was associated with a 9% greater probability of cancer detection (95% confidence interval [CI], 2%-16%), a 4% lower probability of biopsy (relative risk, 0.96; 95% CI, 0.93-0.99), and 39% fewer face-to-face visits (relative risk, 0.61; 95% CI, 0.57-0.65). Other workflows were less effective. Differing proficiencies across teledermatology workflows and selection of patients for direct referral could have caused bias. Implementation is critical to the effectiveness of teledermatology.

Sections du résumé

BACKGROUND BACKGROUND
The effectiveness and value of teledermatology and face-to-face workflows for diagnosing lesions are not adequately understood.
OBJECTIVE OBJECTIVE
We compared the risks of biopsy and cancer diagnosis among 2 face-to-face workflows (direct referral and roving dermatologist) and 4 teledermatology workflows.
METHODS METHODS
Retrospective study of 59,279 primary care patients presenting with a lesion from January through June 2017.
RESULTS RESULTS
One teledermatology workflow achieved high-resolution images with use of a dermatoscope-fitted digital camera, a picture archiving and communication system, and image retrieval to a large computer monitor (in contrast to a smartphone screen). Compared with direct referral, this workflow was associated with a 9% greater probability of cancer detection (95% confidence interval [CI], 2%-16%), a 4% lower probability of biopsy (relative risk, 0.96; 95% CI, 0.93-0.99), and 39% fewer face-to-face visits (relative risk, 0.61; 95% CI, 0.57-0.65). Other workflows were less effective.
LIMITATIONS CONCLUSIONS
Differing proficiencies across teledermatology workflows and selection of patients for direct referral could have caused bias.
CONCLUSION CONCLUSIONS
Implementation is critical to the effectiveness of teledermatology.

Identifiants

pubmed: 30738843
pii: S0190-9622(19)30178-1
doi: 10.1016/j.jaad.2019.01.067
pii:
doi:

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1099-1106

Informations de copyright

Copyright © 2019 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Auteurs

Sangeeta S Marwaha (SS)

Dermatology, Kaiser Permanente, Sacramento, California.

Helene Fevrier (H)

Division of Research, Kaiser Permanente, Oakland, California.

Stacey Alexeeff (S)

Division of Research, Kaiser Permanente, Oakland, California.

Eileen Crowley (E)

Dermatology, Kaiser Permanente, Vallejo, California.

Michael Haiman (M)

Dermatology, Kaiser Permanente, Santa Rosa, California.

Ngoc Pham (N)

Dermatology, Kaiser Permanente, Santa Clara, California.

Melanie J Tuerk (MJ)

Dermatology, Kaiser Permanente, Walnut Creek, California.

Danny Wukda (D)

The Permanente Medical Group, Quality and Operations Support, Kaiser Permanente, Oakland, California.

Michael Hartmann (M)

The Permanente Medical Group, Quality and Operations Support, Kaiser Permanente, Oakland, California.

Lisa J Herrinton (LJ)

Division of Research, Kaiser Permanente, Oakland, California. Electronic address: Lisa.Herrinton@kp.org.

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Classifications MeSH