Smart Footfall
Predictions
Trend and Anomaly analysis across geographies and hospital-services using Artificial Intelligence. Predicts footfall for specific patient segment using Patent pending technology.
Trend and Anomaly analysis across geographies and hospital-services using Artificial Intelligence. Predicts footfall for specific patient segment using Patent pending technology.
Statistical Machine Learning algorithms to predict seasonal trends across all possible patient segments including demographics, geographies, payer, services, etc.
Detects anomalies in footfall of certain patient segments. Never miss changes in usual trends for some hidden patient demographic segment.
Use patient segmentation for targeted marketing campaigns. Measure ROI on these campaigns to see changes in footfall for specific patient-segment.
Let's say certain changes caused significant drop in patient footfall from a specific demographic in a specialty. This might go unnoticed because overall the footfall might not change significantly in a growing hospital. Can the hospital afford to miss this clue early in the game? With Health-PIE, hospitals would never miss these significant clues. Hospitals can act quickly to fix issues before it is too late. Similarly, some positive clues can also be picked up by this tool to measure ROI and effectiveness of certain promotional events and marketing.
Hospitals are generally aware of overall seasonal trends and understand intuitively how the overall footfall varies through the year. The intuition is good, but it is mostly missing for specific patient-segments. Many hospitals face challenges in planning resources as they are not completely sure on seasonal trends. Hospital Operations Team can now substantiate and enhance their intuition with data from seasonal trends drawn using Health-PIE tools. Hospital teams can clearly check the seasonal and year-on-year trends for specific patient-segments. This helps the hospital plan its resources effectively.