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Using Data Analytics for Better Financial Outcomes

September 03, 2013

To make the best use of the massive amounts of data being collected by hospitals and health systems, CFOs are turning to powerful analytics tools to find revenue cycle efficiencies and other cost savings.

This article appears in the July/August issue of HealthLeaders magazine.

As healthcare becomes increasingly data-driven, provider organizations find themselves inundated with more information than ever before. Figuring out what to do with all the data may not be easy, but for healthcare finance executives it is a challenge worth tackling because the hospitals and health systems that successfully implement a data analytics program can significantly enhance their economic outcomes and fiscal stability.

The use of data analytics in healthcare is on the rise. Global business consulting firm Frost & Sullivan released a report last year predicting that the adoption of advanced health data analytics in U.S. hospitals would increase from 10% to 50% between 2011 and 2016, a 37.9% compound annual growth rate. Likewise, the February HealthLeaders Media Intelligence Report indicates that 62% of healthcare organizations plan to increase their spending on financial analytics over the next three years; only 3% plan to spend less.

Hospitals in large numbers are being driven to invest in analytics by two factors, says Nancy Fabozzi, connected health principal analyst at Frost & Sullivan, which is headquartered in Mountain View, Calif.

"No. 1 is healthcare reform," she says. "It's the fact that there are going to be more patients coming into the system, and they are going to be a different type of patient in the sense that a lot of these people have not been covered before and may not understand how insurance works. They may not fully understand issues like deductibles and copays."

The second major factor is changing reimbursements, Fabozzi says. "The move away from fee-for-service to value-based payments is a big driver of analytics because it dramatically increases the financial risk … You need to fully understand not just your clinical performance but your operational performance and your financial outcomes. Analytics is at the heart of that."

With these significant threats to revenue on the horizon, hospitals are faced with the need to maximize their data to find efficiencies wherever possible.

Improving collections

The rapid growth in the use of data analytics in healthcare comes as no surprise to Eric Waller, senior vice president and chief marketing officer at Health Management Associates, a healthcare company based in Naples, Fla., operating 71 healthcare organizations across 15 states with $6 billion in annual net revenue.

Waller says when he joined the organization in 2009, he began looking for opportunities to apply analytics and quickly zeroed in on the revenue cycle as the best place to start.   

"Analytics hold enormous potential on the clinical side, but the more immediate opportunities, at least for us, were on the financial side," Waller says.  

"One natural place for us to start was in coding and billing," he says. "Historically, there have just been a lot of people thrown at the problem. Now, we've taken these experts and introduced math and machines, and we've seen significant results. We are making sure we are capturing the information and coding properly and getting the revenue we are due. We've developed sophisticated models to look for outliers in our coding. The machines crunch the data and identify the outliers."

Waller says that through the use of data analytics models, HMA is now preventing about $1 million per month in net revenue leakage.

"In a system of our size, if you make small, incremental improvements, the dollars add up quickly," Waller says. Also, HMA is achieving considerable savings by reducing its reliance on external resources. "We've eliminated a lot of the labor costs from outside firms that would normally have people doing manual sampling of files to look for missed codes. We've eliminated that expense, which was somewhere between $3 million to $5 million per year."

"Think about a room full of people just looking through files to make sure the coding is all correct," he adds. "That's not very scalable. Just throwing more people at the problem isn't the answer … We want to identify any areas where we could potentially underbill and also where we could potentially overbill. It's in everyone's best interest for it to not be over or under, but for it to be accurate. The most efficient way to do that is with computers and data analytics models."

Cleveland-based MetroHealth, a 490-staffed-bed health system with $680 million in annual net patient revenue, also uses data analytics to enhance the revenue cycle. The system developed a tool to identify collections patterns and trends in order to predict what the revenue cycle totals will be at the end of every month.

"We don't want to get to month's end and all of a sudden it's a shock to us, so we developed a tool to focus on revenue projections based on the charges that post on a day-to-day basis for items such as contractual and charity adjustments," says Craig Richmond, MetroHealth's associate CFO.

"This allows us to do a deep dive to see if adjustments are accurate. It could have an impact on month-end results if something is not identified and resolved. We are using data analytics as a proactive measure in order to make sure that things are posted in the system correctly. Wherever you can use data analytics and business intelligence tools to assist you in your operations, it is critical," he adds.

Additionally, MetroHealth has developed what it calls its daily projection flash report, which is distributed to stakeholders on the clinical, operational, and financial sides of the business, Richmond says.

"It's a summary-level document that takes the current activity to date and uses it to project month-end revenue and volumes. It allows us to look at hospital revenue and professional services revenue so we know what our actual numbers are compared to the budget, and we can see where we have a variance. This is another tool that allows us to start evaluating where we might have a potential concern."

While Richmond does have specific details on how much these analytics tools are improving the revenue cycle, he says the big gain is in the health system's ability to be aware of collection trends and to research any outliers in real time, rather than in hindsight.  

"Instead of doing things in a retrospective way where we close the books and take a look at where we fell, the tools we've put in place let us manage the revenue cycle as we are moving through the month. We can be proactive, rather than reactive," he says.

MetroHealth has also implemented an analytics tool designed to capture missing professional charges. When a physician generates a completed note for a hospital patient, the system automatically checks to be sure there are corresponding charges included in the file. If not, the completed note is flagged for further scrutiny.

"It allows us to investigate why there are no corresponding charges when there is a completed note. It lets us take proactive measures to identify the proper charges," Richmond says.  

Through the use of this tool, MetroHealth saw a 5.2% increase in its inpatient professional charges per patient day between 2010 and 2012, he adds.

Estimating patient payments

Four months ago, MetroHealth began using data analytics to determine its patients' liability before performing a procedure.

"We purchased a third-party solution that allows us to estimate the patient's out-of-pocket responsibility," Richmond says. "As individuals are now having a higher cost-sharing portion, it is all about having an informed consumer. We all like to have an idea of what something is going to cost, and understanding the benefits that go along with the insurance you have can be very complex."

The tool uses an algorithm to generate the estimate based on MetroHealth's contracts with payers, its charge description master price for the procedure, the patient's insurance eligibility, and the anticipated service that is to be performed.

Armed with this information, MetroHealth calls patients who are scheduled for an appointment for which there will be a substantial out-of-pocket responsibility to inform them and to offer an opportunity to prepay.

"We have seen some success in securing payments from patients in advance of a procedure," Richmond says, noting that MetroHealth is now collecting about 15% of patient amounts prior to service. "It's a small amount, but it is still a success."  

Balancing staff and patient volumes

Because workforce management is the largest cost center for healthcare providers, it's another key area where organizations can reap financial benefits from the use of data analytics.

HMA targeted its emergency department when it began looking for staffing efficiencies, Waller says.

"We think of the staff as the supply and the number of ER visits as the demand. The better we can match the supply to the demand, the better for everybody. We certainly don't want to be understaffed and not serve our patients the best we can, but we don't want to be overstaffed either. We started by asking the question, 'Is the number and pattern of emergency room visits predictable?' "

With the help of an analytics tool, he looked at four years' worth of data and identified patterns in emergency department usage. "Barring any unforeseen event that would overload the ER, it is predictable by month, by week, by day of the week," he says.

Waller says HMA invested in staff scheduling tools that "allow us to better match supply with demand" based on the available data.

HMA's goal is for a patient in its emergency room to be seen by a medical provider within 29 minutes of arrival, and Waller says there has been significant achievement of that goal where analytics have been implemented.

"We've been able to reach our goal because of our ability to predict demand. We've ended up with happier nurses and happier patients. This has real financial implications because patients will continue to use our hospitals, and we've lowered our labor costs," he says.

Overall, HMA has reduced nurse staff hours in its emergency departments by 3% to 8%, depending on the shift and where analytics are in use; although Waller notes in some cases that staffing has increased during certain times to better reflect patient demand.

"It's been an excellent, excellent investment. Moving the needle a little has resulted in big savings," he says.

Reprint HLR070813-8


This article appears in the July/August issue of HealthLeaders magazine.

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