How to Optimize Provider Utilization

Workforce management is difficult for any large organization. Healthcare systems are no exception. Caseloads vary from doctor to doctor, and demand for healthcare varies throughout the year.

All of which raises the question, how can a manager know when changes in a doctor’s bookings are something to worry about?

To answer this question, a scheduling platform must collect and report data on appointment bookings down to the provider level.

This data should be accessible to system managers and enable them to easily verify the efficient connection of doctors and patients. Armed with this insight, managers can take action on the most troublesome cases.

To identify these cases, you must be able to forecast the expected number of monthly bookings with modern statistical techniques. In this scenario, we use a fixed-effects panel regression, which controls for time invariant differences between providers. For example, using data from a large national healthcare system, we built a model that accounts for physician/practice characteristics like location, specialty, recent booking history and the monthly variations in appointment bookings.

Together, this constructs a prediction interval for each of the system’s nearly 2000 providers. Using this model, the report flagged 35 providers whose appointment fell below the lowest value of their prediction interval.

At this point, the system sends automated email alerts to the division manager with a summary of the doctors with low bookings. This allows managers to focus on helping the doctors who need to take action rather than sifting through reams of data.

To learn more about how MyHealthDirect is helping healthcare systems improve provider capacity, read our free report, Redefining Patient Access.