AI in Wound Care: FAQ on Diagnostics, Product Selection, and Documentation
faq
Straight answers to the questions clinicians ask about AI in wound care — what it diagnoses, what it doesn't, and where it fits in the visit.
Dr. Desmond Bell predicts AI adoption will make today's wound care approach look archaic within two years. Clinicians hear that and reasonably ask: what exactly does AI do in a wound visit, and what should I not expect from it? This FAQ answers the common questions.
Does AI diagnose wounds?
No — clinicians diagnose. AI supports differential diagnosis by surfacing patterns in imaging, measurement trends, and prior notes. The clinician still owns the assessment.
Can AI measure a wound accurately without markers or stickers?
Yes. Markerless, point-and-capture imaging estimates length, width, area, and depth from a smartphone image. Details: AI-powered wound imaging.
Does an AI scribe replace the clinician's note?
It drafts the note from the ambient conversation and exam. The clinician reviews, edits, and signs. An AI scribe for wound care is wound-specific — it captures tunneling, undermining, exudate, and periwound findings that generic scribes miss.
Can AI help with product selection?
It can surface healing trajectory data and flag stalled wounds where advanced therapies may be indicated. The decision — and the medical necessity documentation — stays with the clinician.
What about Medicare audits and compliance?
Structured, image-anchored documentation is easier to defend. See how documentation software affects claim denials in WISER.
Where does AI clearly not help yet?
Judgment calls with sparse evidence, atypical wounds outside training data, and any decision requiring hands-on assessment of perfusion or infection.
Read the full Bell interview: Managing Wounds vs. Healing Them.