Revenue cycle management is becoming increasingly complex as the healthcare landscape evolves and patients become more conscientious of the money spent on healthcare.
In a session at the Becker's Hospital Review 2nd Annual CIO/HIT + Revenue Cycle Conference, July 27 and 28, in Chicago, an expert panel discussed the complexity of revenue cycle processes today and how data analysis can make it easier to manage. The panel included:
• Richard Lyman, vice president of revenue cycle, Chicago-based Advocate Health Care
• Nayan Patel, director of information technology, The Heart Hospital Baylor Plano & Denton (Texas)
• Michele Tsang, director, revenue cycle management at North American Partners in Anesthesia
• Jason Williams, vice president of business analytics at McKesson/RelayHealth
The sea change in analytics in the last five years
According to Mr. Williams, the biggest sea change in healthcare revenue cycle has been the shift to a fact-based culture. Because health systems have invested a lot more in information technology than in the past, the quantity of data is increasing and the quality is getting better. In the past, revenue cycle issues where managed as problems arose. Today, organizations are becoming more proactive and using data and facts to prevent issues before they occur.
"Everyone wants change for the better in their organization," he said. "The facts allow you to see the focus points and discover the pain points. These points may not be what the organization thinks they are."
Mr. Patel agreed with the notion that healthcare revenue cycle management is becoming more data-driven and added that physicians are becoming more and more engaged in hospital operations. They are asking for more data and holding themselves accountable. They want to make sure financial data and clinical information support the decisions they make.
The data-driven revenue cycle culture is made possible due to ever-evolving technological capabilities. One of the most notable analytic technologies of the last five years is the interactive dashboard, said Ms. Tsang. These interactive dashboards allow users to see all the important metrics and key performance measures.
"As revenue cycle directors, we have to look at all the different measures," she said. "You can use the dashboard to see the metrics from the billing point of view. It also allows you to drill into an individual account."
Propensity to pay — how are healthcare systems measuring it?
Mr. Lyman said his organization looks at a patient's soft credit score and consumer history to measure propensity to pay. They then divide patients into four different categories:
Category 1: Patients who pay their bills
Category 2: Patients who need a reminder, such as a phone call, and then will pay
Category 3: Patients who need more reminders, such as calls and letter, and then will eventually pay
Category 4: Patients who are never going to pay
"You have to move on from the category four patients," said Mr. Lyman. "This system has produced a good return-on-investment because your staff doesn't have to call on every account. You don't have to waste time not chasing dollars that you won't get."
Mr. Williams added that while credit score is a good way to help determine propensity to pay, it is important to remember that people may pay for healthcare differently than they pay for other things, like cable or car insurance. Data analytics also helps healthcare organizations measure propensity for a number a different factors — not just pay, but also propensity for readmission, for example.
Preventing common coding and billing issues
Mr. Patel's organization regularly conducts internal reviews. Staff members compare what is coded with what was used in each procedure.
"Procedures and supplies may change, and that isn't always reflected in the final bill," he said. "We have caught a number of errors where supplies are put on the bill that we didn't use. Weekly audits allow us to review each case before it is sent down to patient billing."
Mr. Patel advises preventing billing errors and claims denials rather than managing it. Try and get all your ducks in a row before moving forward with procedures, he said. Collecting data and conducting audits are best practices for managing the revenue cycle effectively.
It is also important to remember that the purpose of collecting and analyzing data isn't just solving problems that occur but also identifying problems.
"Avoid the tyranny of the benchmark," said Mr. Lyman. "Data shouldn't be used only to get answers. Rather it should help you ask better questions. Revenue cycle management is more complex than it used to be and we now have to understand the interplay between the numbers."
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