The key to unlocking RCM transformation? Analytics

Today more than ever, successful revenue cycle management is critical to hospitals' survival.

Although hospitals have more clinical and operational information at their disposal than ever before, this data often isn't leveraged to its full capacity. In fact, data analytics has the potential to unlock $50 billion in annual value to the healthcare system by improving payment, revenue cycle and pricing, Pieter Schouten, chief analytics officer of RCM provider Ensemble Health Partners, said during a May 29 webinar sponsored by Ensemble and hosted by Becker's Hospital Review.

"Leveraging analytics in healthcare is promising for a couple reasons. One is we now have data in massive volumes and everybody has invested heavily in IT to collect more and more of it. Also, we know the payoff is there without any doubt," Mr. Schouten said. "But while some results are coming in, a lot of the promise is still out there and is actually proving somewhat elusive to get in the short term."

These challenges include finding the right people and technology to analyze and leverage this data in a way that makes sense for providers. Forty percent of companies, including hospitals, are struggling to find and maintain an analytics team. In addition, there's a large amount of health data left untapped, as healthcare providers throw out 90 percent of the data they generate.

Artificial intelligence and robotic process automation, two of the most talked-about solutions in data analytics, can be used to accurately capture this under- and unused information and transform it into productivity in the revenue cycle.

The four stages of applying analytics to revenue cycle

The four stages of applying data analytics, artificial intelligence and automation in the revenue cycle are data science, predictive modeling, analytics-driven workflow and automation.

"Machines are much better than humans at the heavy-lifting and processing of lots of data without any bias. Machines can quickly process visual information, and machines can also identify associations," Mr. Schouten said.

The first stage of applying analytics to the revenue cycle, data science, involves using data science to improve denial calculations and reporting, vendor inventory reconciliation, vendor invoice analytics and cash reconciliation. The second stage, predictive modeling, includes using tools to gather missing charges and quantities, denials and root causes, and probability to collect. Analytics and workflow, the third stage, includes collection workflow optimization.

One example of how analytics can be applied to the first stage is when providers use data to identify anomalies in contingency-based vendor invoices. Manually reconciling contingency vendors is burdensome and expensive, and can lead to errors, as payment adjustment files are usually viewed as snapshots and vendors don't often reconcile to provider accounts receivables. Issues like these require a fourth stage of analytics application, automation. Automation takes these snapshot data pictures into account, analyzes them in a comprehensive way and gives providers the full picture of the problem so they can implement the best solution.

Where to start when choosing automation to increase cash and reduce cost

If providers are starting from scratch on their analytics journey, there are three steps they should take along the way: an assessment, pilot deployments and implementation.

With more than 200 years of combined leadership experience, Ensemble leaders partner with providers to find solutions that deliver results to their analytic needs across all three stages. Ensemble offers revenue cycle outsourcing solutions aimed at improving denials and underpayments, analytics and workflow optimization, Epic optimization, and management services.

"Ensemble is rooted in being an operator versus a consultant, working with client systems and not forcing technology, sharing the playbook and acting on transparency, aligning incentives and sharing values between client and vendor, and — most importantly — being data-driven in our decision-making," David Hitzel, senior vice president of revenue cycle at Ensemble, said.

More than 3,500 associates over 30 states have partnered with Ensemble to leverage its RCM expertise. One health system with 22 hospitals leveraged Ensemble's invoice analytics solutions and found $2.1 million worth of errors and a monthly error rate of between $100,000 and $200,000.

"To get short-term results like these, we don't boil the ocean. We focus on one specific area and focus on getting results rather than trying to solve some massive problem," Mr. Schouten said.

Learn more about how Ensemble can help your hospital here.

To view the webinar,  click here.

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