A version of this blog was originally published on April of 2020. We have updated the content to reflect the latest in the healthcare landscape.
As patients return to doctor’s offices and health systems around the country, healthcare organizations find themselves in uncharted waters, with a greater need than ever to make data-driven decisions that drive revenue. Per a report from KLAS, 63% of hospitals found themselves struggling with real-time data analytics.
It should come as no surprise that investments in new analytics tech and training are on the rise. Since 2011, over $39B has been invested in digital health tech, including $7.48B in 2019 alone. It’s estimated that roughly 20% of that has been funneled into the development of technology focused on managing health records and analytics. Furthermore, some models have estimated improving available data collection and analysis tech could save the healthcare industry roughly 25% of its total costs.
The question is, what can you do to unlock that potential within your own organization? There’s a deep well of data that each revenue cycle feeds into, which if properly analyzed, can help organizations operate at their most efficient and effective. Here are the four stages of data analytics workflows that are key to developing those actionable insights.
- A trigger, or the point in your revenue cycle that sets up the call for deeper analysis
- Interpretation of data to determine root causes and identify appropriate next steps
- Intervention to improve specific metrics
- Tracking of said metrics to chart success in achieving desired outcomes
Let’s examine what a successful version of each stage looks like.
1. Trigger
The trigger occurs when you notice something that needs further investigation. With the right analytics tool, you can easily access all of your key performance indicators, financial goals, and more, providing the visibility you need into your rev cycle. When something looks amiss or needs improving, you can drill down to the level that shows what’s really going on.
2. Interpretation
Even a wealth of data amounts to nothing without an efficient way to process and communicate key takeaways. You’ll need to equip your team with access to concise reports, smart visualizations, and relevant historical data in order to get them to the insights that drive action.
3. Intervention
Now is the time to take action. Intervention is ultimately tied directly to your ability to drill down into the data underlying problematic areas of your revenue cycle and clearly communicate takeaways with your team. Success at this stage depends on designing a plan based on your best understanding of underlying issues and the most effective way to address them.
4. Tracking
Your intervention plan is built on KPIs that naturally intertwine with the way you measure success across your revenue cycle. With proper implementation and tracking, running with the analytics cycle can become a simple addition to your everyday workflow. More than delivering on your initial goals, the true power of analytics is the ability to deliver repeat value on your initial investment.
The wrap up
A strong analytics solution does more than deliver a more fully developed picture of your rev cycle performance. It provides actionable business intelligence, cuts down on time between analysis and action, and lessens the strain on your IT department.
Beyond the actionable internal insights it can provide, analytics is also a key tool for helping you benchmark performance in comparison to peers in the industry. And with the right analytics solution, competitive analysis is a simple task, using automation that reviews customizable benchmarks for a tailored review of claim, payment, and denial performance.
Looking for a truly comprehensive analytics solution to help improve performance and enhance your benchmarking capabilities? Learn how Waystar can help you harness the power of your data with Waystar Analytics + Reporting, available separately from the Waystar platform.
