Inside the healing trajectory: turning visit data into a predictive curve

Most wound records store data. Few of them use it. A healing trajectory turns each visit into a point on a curve — and the shape of that curve tells you which wounds are on track weeks before a clinician would notice by eye.

The inputs

A trajectory is only as good as the signal feeding it. The healing analytics dashboard pulls from:

• Wound surface area from point-and-capture imaging at every visit
• Depth and volume where clinically meaningful
• Tissue composition (granulation, slough, eschar percentages)
• Exudate volume and character
• Perfusion indicators (ABI, TcPO2, toe pressures where available)
• Systemic factors — HbA1c, albumin, offloading adherence

What the curve actually shows

Healing wounds follow a roughly log-linear reduction in surface area. Deviation from that curve — a plateau, or reversal — is the earliest quantitative signal that the current plan isn't working. The trajectory flags this before the four-week LCD threshold that typically forces a plan change.

From trajectory to next best step

A curve alone doesn't change care — the recommendation on top of it does. The trajectory agent pairs the wound's shape with published evidence to suggest concrete next steps: additional vascular workup, culture, offloading escalation, or advancement to a cellular and tissue-based product. Every recommendation cites the underlying rationale.

Why it matters for reimbursement

Advanced therapies require documented failure of conservative care. A trajectory is the cleanest, most defensible way to show that failure — or to show that a wound is progressing and the current plan should continue. It replaces narrative arguments with a measurable curve.

The compounding effect

Each visit adds a point. Each point sharpens the prediction. Across a caseload, the dashboard surfaces which wounds — and which patients — need attention this week, not next month. See it end to end in From Curve to Care.