Patient
Forecaster, an AI-powered advanced labor management platform, today
announced the launch of its emergency medicine platform, a breakthrough
technology that puts the predictability of scheduling work back in the
hands of administrators of emergency departments and urgent care centers.
The new platform uses machine learning and predictive algorithms to
analyze millions of data points every day across each individual
location. In so doing, Patient Forecaster’s scheduling engine eliminates
the frustrations that administrators normally face due to unforeseen
fluctuations in hourly patient demand. The platform builds accurate
schedule templates that can be used to take instant action via
recommendations, automatic optimization and alerts.
Patient Forecaster combines the strength of historic internal patient
visit data with the external data and tools to produce accurate hourly
predicted patient demands with associated acuity levels, said Jeff
Wadsworth, founder of Patient Forecaster. Its emergence in the market,
he said, has replaced the disjointed or nonexistent systems with a
cohesive and relevant advanced labor management process.
“While many workforce management systems have basic labor trackers, no
one else is using AI to power this depth of accuracy in predicting
patient demand by the hour,” Wadsworth said. “Only our advanced labor
management system provides the highest level of accuracy that allows
administrators to regain control of scheduling in areas such as
patient-to-staff ratios, efficient labor planning and the ability to
determine cost to provide based on patient demands.”
Free demonstrations of Patient Forecaster will be available at the Society
for Academic Emergency Medicine (SAEM) annual meeting in Las Vegas,
May 14-17, 2019. To schedule a demo, contact Nicole Daley, nicole@patientforecaster.com
About Patient Forecaster
Patient Forecaster is an AI-powered advanced labor management platform
that delivers predicted patient demands and staff schedule
recommendations up to 120 days in advance. The platform’s data
aggregation capabilities provide for a cohesive view of predicted
patient demands and acuity levels, allowing for the rapid and accurate
creation of highly efficient schedule templates. By leveraging
machine-learning and employing algorithms for smartly triggered alerts,
emergency department and urgent care administrators use Patient
Forecaster daily for understanding upcoming patient demands and to
develop efficient scheduling templates for nurses, physicians and other
advanced practice providers. Headquartered in Denver, the company serves
hospitals and urgent care centers across the world.
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