A framework to measure performance and deliver results
With multiple Key Performance Indicators tracked across various parameters such as dollar value, payers, and time dimensions, revenue cycle processes offer a complex quantitative puzzle. Further, the metrics an A/R process manager uses are very different from the metrics that matter to the CFO. The complexity is enough to delight the statisticians.
1. Most EMR systems are not designed for Analytics
The primary design goals of EMRs are the capture and retrieval of healthcare information and management of the revenue cycle – billing to collections operations. In recent years, EMR software companies are enhancing their analytics and reporting capabilities. While most revenue cycle systems come with multiple reports, the inadequacies of the base-level dashboards get exposed quickly. The one size fits all approach in developing dashboards cannot address the needs of various stakeholders. Revenue cycle leaders must recognize data generating processes and analytics architectures are very different.
2. Implement the analytics solution that fits your organization’s needs
Remember that you chose an analytics solution to help your process managers make more informed choices to improve the process and business outcomes. Document the expectations of your process managers from the revenue cycle system. When choosing an analytics system, assess the ability of the system to address these requirements. The implementation team of your preferred vendor must bring strong RCM functional knowledge, can understand the needs of multiple participants in your revenue cycle chain and align the presentation to address these needs.
3. KPIs: Providing insights across the revenue cycle chain
Revenue cycle processes are a team sport. While individual processes have distinct information needs, CFOs and operational leaders must also be able to get a clear view of the health of the revenue cycle. Most analytics tools can address specific functional needs but are not able to provide an integrated, full-picture view of the revenue cycle.
Defining a metrics-based ecosystem to measure the performance at an individual functional level and a macro level is an important next step. Thankfully, Industry bodies such as HFMA have done some amazing work in that direction.
4. Visualization: The key to making informed decisions
Let’s face it. Sifting through a mountain of data is not how you want to spend your workday. Not only is the exercise time-consuming, but it is also prone to human errors. Data visualization provides the answer. Visualization tools and reports are a key element of any analytics solution worth your money. A well-visualized dashboard can quickly draw the attention of decision-makers to the facts and enable them to make well-informed decisions. Modeling your dashboards on the HFMA MAP Keys is a good way of addressing the needs of functional managers and revenue cycle leaders, and CFOs.
5. Benchmarking and Goal Setting
Once you have visualized the data, you must define process-specific standards for performance. By benchmarking, you get a good understanding of the prevalent performance standards compared to the peers in the industry. Set Goals for specific functional areas such as accounts receivable, patient access, denial management, and other financial and quality parameters.
6. From Analytics to Action.
By combining intelligent workflow systems with analytics, you can auto-create work queues to drive focus on some of the most critical issues in your revenue cycle. This change can reduce the manual effort in creating work queues and improve revenue cycle outcomes significantly.
7. Driving Adoption
Whether you have an analytics tool or utilize in-built reports, the key for transformation is to have a periodic platform for discussion between revenue cycle leaders and the operations team. The discussion will promote consistent usage and interpretation of the data available and help identify transformational initiatives. If your organization is already utilizing an analytics platform, this discussion will also identify better visualization opportunities and create automation workflows.
In Conclusion
Technology and analytics are key enablers of revenue cycle transformation. It’s time for revenue cycle organizations to shift to data-driven decision-making and process automation.