
FastCare: Clinical Scribe and Wound Measurement at the Point of Care
The Challenge
Clinicians at Gentell FastCare were spending a growing share of their time on manual documentation across fragmented systems. Wound measurement was subjective, so two clinicians assessing the same wound could record different dimensions, and healing could not be tracked consistently over time. The result was less time with patients, inconsistent records, inter-rater variability, compliance gaps, and clinician burnout. Any solution had to fit into the existing care workflow without adding steps or screens.
Our Solution
BeyondScale designed and implemented a mobile-first clinical intelligence platform embedded directly into the point of care. An AI clinical scribe uses domain-tuned NLP to convert clinician-patient conversations into structured, clinically relevant notes in real time, capturing findings, assessments, and care plans automatically.
For wound assessment, computer vision and calibrated image analysis measure length, width, depth, and area from mobile images, producing objective and repeatable results. Voice and image inputs are transformed into standardized, coded, audit-ready data that supports care continuity across shifts and integrates with existing EHR systems.
Highlights
- AI clinical scribe with real-time conversation-to-note conversion
- Domain-tuned NLP for clinical accuracy
- Computer vision wound measurement: length, width, depth, and area from mobile images
- Reduced inter-rater variability with consistent healing tracking
- Standardized, coded clinical data with audit-ready documentation workflows
- EHR-friendly integration approach
- Hands-free, mobile-first workflow embedded in existing care processes
Architecture
FastCare clinical AI
The clinician's phone feeds conversation audio to the scribe and wound photos to the measurement model, and both write coded clinical data that the EHR can take.
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