Solutions

Real-time patient information delivered directly into your workflow

Our AI models predict changes in patients’ care needs, enabling timely and proactive decision-making.

Our predictions are highly accurate and provided through a user-friendly interface, designed for convenient use by busy doctors and nurses.

Signal 1 Discharge Solution

Accelerate discharge planning

We predict which patients have a high probability of being at the end of their acute phase of care and share their status and barriers with relevant staff.

~75%

of patients will be surfaced by our algorithm prior to their actual discharge from hospital.

Based on model performance in a test sample of 1,568 patients from one of our partner hospitals.

Learn how Grand River Hospital has integrated the Signal 1 Discharge Solution into their daily rounds.

Signal 1 Staffing Solution

Improve staffing assignment
We predict which patients are higher-risk and higher-workload, enabling managers to optimally distribute patients across staff.

Receive start-of-shift reports with visibility into patients’ risk levels and nursing tasks to enable smarter staffing and better time management.

Signal 1 Deterioration Solution*

Identify clinical deterioration early
We detect which patients are at high-risk for clinical deterioration and notify care teams in real-time.*Signal 1 Deterioration Solution not yet available for sale. Investigational use only.

30%

of alerts would be on patients who transfer to ICU or die.

60%

of all patients who transfer to ICU or die would be alerted on.

Based on model performance in a test sample of ~4448 patients from St. Michael’s Hospital.

We are commercializing a solution that has been in use at St. Michael’s Hospital since 2020.

16%

improvement in clinicians’ ability to accurately predict patient deterioration1

26%

reduction in in-hospital mortality rate of high-risk patients after deployment2

1 – Verma AA, Pou-Prom C, McCoy LG, Murray J, Nestor B, Bell S, Mourad O, Fralick M, Friedrich J, Ghassemi M, Mamdani M. “Developing and validating a prediction model for death or critical illness in hospitalized adults, an opportunity for human-computer collaboration.” Crit Care Explor. 2023 May 1;5(5):e0897. doi: 10.1097/CCE.0000000000000897. PMID: 37151895; PMCID: PMC10155889.

2 – Based on research from St. Michael’s Hospital, under preparation for publication.

“Machine learning solutions are now part of daily patient care at our hospital, enabling our staff to make better decisions and deliver better patient outcomes.”

– Dr. Amol Verma

Clinician-Scientist, St. Michael’s Hospital Temerty Professor of AI Research and Education in Medicine, University of Toronto

Built on an award-winning AI technology stack designed to deliver accurate and explainable predictions.

10+

years of data

125,000+

patients

200+

clinical features per patient encounter

Use existing data with no extra work

We work with existing data sources and require no manual data entry by your team.

Deployed in as little as 60 days

We easily integrate with existing EMRs, using existing standards such as FHIR protocols, to enable a quick setup.

Delivered through our secure cloud-based platform

Our platform manages all aspects of the AI lifecycle and meets industry standards for privacy and security.

AICPA SOC 2 & HIPPA certification badges

Learn how we can support your hospital

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