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Clinical care and population health
Seeing the readmission coming instead of reading about it after
Clinical and population health teams still assess risk at the point of care, so a patient likely to be readmitted or to deteriorate often isn't flagged until it's already happening. Care gap outreach runs on whoever has time to make the calls.
AI moves the signal earlier. Predictive models score readmission, deterioration, and population health risk from the record you already keep, days ahead of the event. Generative AI drafts the outreach and care gap summaries a care team acts on. Agents keep the gap closure list current as new data arrives. Your clinicians see the risk before it becomes an event, on infrastructure you control.
11 use cases
Chest abnormality detectionChest abnormality detection uses computer vision to flag chest X-rays that may show a heart or lung abnormality, so your radiologists read those first.Clinical evidence synthesisClinical evidence synthesis: AI agents read trial results, safety data and studies, and draft a cited brief of findings and gaps for clinicians to review.Critical care patient deterioration alertsA model that scores changes in a patient's status from monitor and vital-sign data, and alerts the care team on which patients to check first.Hospital capacity simulatorA hospital capacity simulator forecasts census, admissions, and length of stay, then tests surge scenarios so you plan beds and staff before demand arrives.Hospital census forecastingHospital census forecasting predicts how many patients each facility and unit will have in the coming days, so staffing and bed plans are set ahead of demand.Predicting hospital-acquired infectionsA risk model that scores inpatients for infections such as CLABSI from device, procedure and lab data, so infection prevention teams can focus rounds first.Predicting opioid use disorder and overdose riskAI finds patterns in health records linked to opioid use disorder and overdose risk, so your care-management and public-health teams can reach people earlier.Predicting readmissionPredicting readmission scores each inpatient's risk of returning within 30 days of discharge, so care managers focus follow-up on patients who need it most.Prioritizing a cardiology worklist by riskAI clinical decision support estimates each patient's heart disease risk from tests and history, so your cardiology team knows who to review first and why.Public health forecastingTime series models predict flu and respiratory disease activity by region for the coming weeks, so public health teams can plan staff, supplies and outreach.Quality measure and care-gap abstractionAI agents read patient charts against quality measure specifications, assemble the evidence, and flag open care gaps for abstractors to confirm.
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