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Output Type
Speciality
Published
Key findings
- Across the evidence base as a whole there was evidence that teledermatology for secondary care triage of referrals:
- reduces the number of face-to-face secondary care appointments required. Where dermatology specialist triage provided advice or reassurance, published studies reported that in the region of 50% of referrals could be managed in primary care
- facilitates more accurate allocation of referral priority
- reduces waiting time for specialist dermatology input
- reduces time to commencing treatment, and
- offers similar clinical outcomes, quality of life and patient satisfaction as conventional referral.
- The main safety concern is that clinically significant incidental lesions may be missed as a result of fewer in person examinations. Actions to mitigate this risk will be required.
- A de novo cost consequence analysis for NHSScotland estimated that increased uptake of a SAF TD referral triage system would likely lead to a reduction in healthcare resource use, decreased travel requirements and costs for patients, leading to decreased carbon emissions.
What were we asked to look at?
The Scottish Health Technologies Group (SHTG) was asked to evaluate the evidence on clinical effectiveness, safety, and staff and patient experience of store-and-forward teledermatology for triage of primary care referrals to secondary care dermatology services.
Why is this important?
There is a urgent need to identify and fast track referrals relating to potential skin cancers in the context of lengthy wait times for dermatology, which have been exacerbated by the COVID-19 protection measures. Current practice is for the GP to submit a referral and indicate the level of urgency based on their clinical opinion.
Around 12% of primary care consultations concern skin disease and skin problems are the most common reason for a new presentation. Whilst it covers all areas of dermatology, the importance of this topic is directed by the need for patients with skin cancers to access rapid diagnosis and potentially life-saving treatment.
Referred by
The Accelerated National Innovation Adoption (ANIA) collaborative and the Dermatology AI (artificial intelligence) Consortium.