NASHVILLE, Tenn. – Intermedix has released a new auto-optimizer capability that delivers valuable scheduling and resource allocation recommendations to emergency department medical directors.
The company, which has made significant investments in its predictive analytics and machine-learning capabilities, announced that the auto-optimizer is an enhancement to its existing Tool for Optimizing Provider Schedules, or TOPS, which is part of the Intermedix data science platform.
As emergency departments continue to face unique challenges and considerable variability in patient volumes on an hourly, weekly and seasonal basis, TOPS utilizes granular data, statistical modeling and user-friendly visuals to provide tailored solutions to medical directors.
Through intuitive dashboards, productivity profiles and data-driven demand models, TOPS can determine the effect various situations have on capacity and patient flow, align provider capacity with patient demand and help determine optimal staffing for each hour throughout the day.
“We created TOPS to take the guesswork out of coverage planning so emergency departments can improve financial operations and ensure overall patient safety and satisfaction,” said Justin Schaper, senior vice president of analytics at Intermedix. “To make TOPS even more user-friendly, we have developed the auto-optimizer so medical directors are quickly presented with the right coverage design that meets their patients' needs.”
Previously, TOPS relied on having medical directors manually align coverage and operational constraints to match historical demand. TOPS would provide them with immediate feedback on appropriateness of coverage, costs and effect of variability. However, optimization to a specific goal was often time consuming for medical directors.
With the addition of the auto-optimizer, TOPS can now look at historical data and input constraints, to make recommendations on the most ideal coverage and resource distribution—without requiring manual iteration. This gives critical time back to medical directors, since the auto-optimizer can now narrow down the best solution, and makes TOPS more efficient and effective for its users.
“One of the main goals with our analytics offerings is to help clients make informed decisions based on accurate and dependable data,” said Joel Portice, CEO of Intermedix. “The auto-optimizer achieves this by crafting coverage designs in a way that is meaningful to medical directors, reaches target goals and is easy to interpret and share.”