why is perioperative analytics important in healthcare?
For most hospitals, the operating room is a leading revenue generator. But many factors can conspire to negatively affect operation room financial performance from case start delays to lengthy turnover times to inefficient staff scheduling.
Applying perioperative analytics to the streams of data flowing from the operation room can lessen those problems and improve the bottom line.
What is HPA's Periop Analytics?
Periop Analytics™ is populated with case and scheduling data from core systems which is transformed into actionable intelligence that provides robust tracking and trending of facility-wide utilization and performance opportunities. The visualizations can be used to identify root causes, drive operational decisions and enhance profitability through optimizing perioperative department metrics.
first case on-time starts
FCOTS (First Case On-Time Starts) is a view of first cases starting after their scheduled time. Adjust the grace period for start times to understand where and by how much first cases are delayed (across Operation Room/Service Line/Surgeon).
The Case Duration view displays average duration of cases (with and without turnover) and time components of cases (Time from to Incision, Incision to Close, and Close to Out Room). Quickly flip between different duration metrics to explore the distribution of time spent across Operation Rooms/Service Lines/Surgeons.
the block analytics
The Block metrics provide a detailed view of the utilization of scheduled time across the organization block holders. It details key statistics, trends, and utilization of scheduled time by weekday. Explore utilization among block holders to measure the effectiveness of current scheduling.
The Executive Dashboard provides an overview of all key performance areas covered in OR analytics including Volume by Service Line, Primetime Utilization, Case Duration, Turnover Time, and First Case On-Time Starts.
The TOT (Turnover Time) view details distribution of room turnover time between cases. Vary turnover outlier time to fully understand the impact of turnover delays and areas for potential improvement.