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Partnering with a senior living community to optimise teledermatology via full body skin screening during the COVID-19 pandemic: A pilot programme.
Trinh, Pavin; Yekrang, Kiana; Phung, Michelle; Pugliese, Silvina; Chang, Anne Lynn S; Bailey, Elizabeth E; Ko, Justin M; Sarin, Kavita Y.
Afiliação
  • Trinh P; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Yekrang K; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Phung M; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Pugliese S; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Chang ALS; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Bailey EE; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Ko JM; Department of Dermatology Stanford University School of Medicine Stanford California USA.
  • Sarin KY; Department of Dermatology Stanford University School of Medicine Stanford California USA.
Skin Health Dis ; 2(3): e141, 2022 Sep.
Article em En | MEDLINE | ID: mdl-35941936
ABSTRACT

Background:

Elderly patients in senior communities faced high barriers to care during the COVID-19 pandemic, including increased vulnerability to COVID-19, long quarantines for clinic visits, and difficulties with telemedicine adoption.

Objective:

To pilot a new model of dermatologic care to overcome barriers for senior living communities during the COVID-19 pandemic and assess patient satisfaction.

Methods:

From 16 November 2020 to 9 July 2021, this quality improvement programme combined in-residence full body imaging with real-time outlier lesion identification and virtual teledermatology. Residents from the Sequoias Portola Valley Senior Living Retirement Community (Portola Valley, California) voluntarily enroled in the Stanford Skin Scan Programme. Non-physician clinical staff with a recent negative COVID-19 test travelled on-site to obtain in-residence full body photographs using a mobile app-based system on an iPad called SkinIO that leverages deep learning to analyse patient images and suggest suspicious, outlier lesions for dermoscopic photos. A single dermatologist reviewed photographs with the patient and provided recommendations via a video visit. Objective measures included follow-up course and number of skin cancers detected. Subjective findings were obtained through patient experience surveys.

Results:

Twenty-seven individuals participated, three skin cancers were identified, with 11 individuals scheduled for a follow up in-person visit and four individuals starting home treatment. Overall, 88% of patients were satisfied with the Skin Scan programme, with 77% likely to recommend the programme to others. 92% of patients agreed that the Skin Scan photographs were representative of their skin. In the context of the COVID-19 pandemic, 100% of patients felt the process was safer or comparable to an in-person visit. Despite overall appreciation for the programme, 31% of patients reported that they would prefer to see dermatologist in-person after the pandemic.

Conclusions:

This programme offers a framework for how a hybrid skin scan programme may provide high utility for individuals with barriers to accessing in-person clinics.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article