Healthcare
Clinical coding support
Coders get a ranked list of candidate codes with the supporting text from the record, looked up in the official code sets, for them to accept or change.
Custom app
Healthcare · Automation
Test results follow-up tracking
AI tracking so abnormal test results are acted on
Results the lab has flagged as abnormal are tracked until a clinician acknowledges them and the agreed action happens, with escalation if they stall.
01 today
The problem
Results come back after the patient has left the clinic or ward, sometimes after the requesting doctor has moved on. Abnormal results can sit unacknowledged, and the follow-up that was intended never happens. Missed results are a known cause of harm.
02 the run
What the AI does
- Step 1: Reads results as they are filed, using the lab's own abnormal flags and your rules for what needs action.
- Step 2: Checks that the requesting clinician, or their cover, has acknowledged each flagged result.
- Step 3: Reminds the clinician and escalates to a named deputy if a result stays unacknowledged past your time limit.
- Step 4: Tracks the follow-up the clinician records, such as a repeat test or a call to the patient, until it is done.
- Step 5: Lists open results for each team every day, oldest first.
paused: waiting for a person to approve
03 human in the loop
Where a person approves
Clinicians interpret every result and decide what to do; the tool only uses the lab's flags and your rules and never interprets results itself.
04 after
What changes
Flagged results do not go unseen when people change shifts or rotations, and every intended follow-up has an owner until it is done.
Case studyMaking sure no abnormal result goes unseenThe rollout, what to measure, a worked example and the research behind it.see also
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