AI reads. Clinicians decide.

Working hypothesis · not yet measured

Care plans are written in pieces.

A patient with several conditions is seen by several specialists. Each records what should happen next — hold a medication, schedule a procedure, monitor, bridge, cancel — in a different note, written at a different time. The record holds each intention. It does not reconcile them.

Our working hypothesis is that some of these intentions conflict or depend on one another in ways that can be difficult to reconcile across notes written by different clinicians at different times, and that surfacing them with their sources, for a clinician to review, is useful. We have not measured how often this occurs or whether surfacing it helps.

Planned workflow · not validated

A clinician-led workflow.

This is the intended design. It has not been validated or used with real patients.

1. 01

   Read

   Longitudinal documentation written by clinicians across specialties, with its source and timing preserved.

2. 02

   Reconcile

   Stated future intentions are gathered into one view that keeps track of what was known, and when.

3. 03

   Surface

   Candidate conflicts or dependencies are shown with the source passages behind them and the uncertainty around them.

4. 04

   Clinicians decide

   Each finding goes to the clinician accountable for the decision. Their decision is recorded.

   Human decision point

Boundaries. Actline does not diagnose, prescribe, recommend treatment, or change or execute any order. Final clinical authority stays with the responsible treating clinician.

Where we are today.

• Pre-validation. A study using real patient records has yet to begin.
• Synthetic demonstration, separate from the proposed study. The prototype shows authored findings for fictional patients. No model runs in the demonstration.

Proposed study · not started

Proposed evaluation.

We propose a retrospective feasibility study to learn whether available records contain enough context to identify potential conflicts or timing dependencies, and whether clinicians can assess those cases consistently. The study has not started. Any access to patient-level data would require applicable institutional, research, privacy, security, and legal approvals.

Institutional inquiries.

If your organization holds longitudinal, multi-specialty clinician documentation and wants to assess whether a retrospective evaluation is feasible, we would welcome a conversation. A first conversation needs no patient data.

In your message, please include your institution, your role, and your feasibility question.

farooq@actlinehealth.com

Please do not send patient information or medical records.