Speaker - Matt Seefeld
Revenue cycle organizations are navigating converging challenges: increased patient financial responsibility and unprecedented shortages of qualified billing staff. More than ever, billing departments must make the most of available resources and ensure retention of their most effective people to capitalize on all revenue potential.
Employee compensation models that incorporate financial incentives for top performance have long been recognized as powerful tools for increasing employee effectiveness and building loyalty. However, many organizations are opting for blanket raises because they simply do not have access to the data necessary to identify top performers and understand the drivers behind effective revenue collection. It’s hard enough to find billing staff, but how do you know the staff you have is effective at the work they do?
With employees demanding more pay, better benefits, work from home flexibility and work-life balance, it is imperative that organizations have the ability to monitor and measure work effort of their billing staff and whether that work is yielding the expected result. This information will identify top performers that can be rewarded, as well as low performers that may require more training or may not be a fit. Additionally, the ability to benchmark and compare employee performance helps to incorporate healthy competition and accountability into revenue cycle management.
In this session, Matt Seefeld will demonstrate real world strategies for implementing an incentive-based revenue cycle model. By leveraging effective intelligence solutions, such as workflow automation, task management and data analytics, revenue cycle executives can be equipped with the right data for building compensation models that improve overall staff performance and morale while helping them become more effective at their work.
- Define incentive-based revenue cycle, the various models that exist and its potential to improve collections in today’s healthcare environments.
- Identify how typical revenue cycle challenges associated with patient financial clearance are impacting back-end revenue cycle and increasing potential for bad debt.
- Analyze the data limitations of today’s practice management and EHRs, and how effective intelligence solutions can provide the needed foundation for incentive-based revenue cycle models.
- Identify best practices and lessons learned implementing workflow automation and analytics to support incentive-based revenue cycle.