How hospitals can use data analytics to improve RCM performance: 4 thoughts from Change Healthcare's Marcy Tatsch
As hospitals and health systems look to improve revenue cycle management performance, they can gain a myriad of insights through data analytics.
By using data analytics, an organization can pinpoint the primary causes of claim denials and monitor collection rates, both of which play a crucial role in achieving maximum reimbursement.
Marcy Tatsch, senior vice president and general manager of reimbursement optimization solutions for tech company Change Healthcare, recently provided Becker's Hospital Review with her observations on the importance of data analytics and how it can improve RCM.
Note: Responses have been lightly edited for length and clarity.
Question: How can data and data analysis help an organization's financial performance?
Marcy Tatsch: Healthcare providers can always benefit through the use of data analytics. In an analytics culture, facts must drive decisions. And fact-based, data-driven decisions can improve the healthcare revenue cycle.
There are many examples, but a few that come to mind include:
A 600+ bed hospital system used data to determine that it had a significant amount of denials related to untimely filing of claims. By analyzing the data, the system identified and fixed a flaw in how claims were being submitted by its healthcare information systems. The value of the provider's future write-off savings has been estimated at approximately $2 million.
A smaller facility in the western U.S. was experiencing costly delays in claims. Data revealed problems with physician documentation. Using the data as a guide, the hospital and physicians agreed to a new policy that included a penalty for non-compliance. Within three months, the hospital reduced the number of days between discharge and getting the claim into the claim management system from 26 to 13 days, which helped their cash flow.
And there was a mid-sized hospital that experienced skyrocketing claims errors. They analyzed revenue cycle data to isolate major gaps in the claims transmission process and common errors in claims submitted from its HIS. Over the next three months, they were able to cut the error rate from 20 percent to less than 10 percent.
Q: How is data analytics becoming more important with the shift to value-based care?
MT: A recent national study of 465 hospitals and payers conducted by ORC International and commissioned by McKesson revealed that the rapid pace of change in healthcare payment continues, with hospitals reporting they are now 50 percent along the value continuum, up 4 percent in the past two years.
This fast rise is intensifying system complexity. The majority of providers surveyed are not meeting their goals. Of the metrics in place for measuring value-based success, just 22 percent of hospitals are meeting their goal to reduce administrative cost of care; only 26 percent are meeting goals to lower healthcare costs; just 30 percent are meeting care coordination goals; and 40 percent are meeting goals for improving patient outcomes.
When asked why these failures were occurring, the answers varied, but recurring themes included struggling with metrics, analytics, and data; as well as personnel, organizational and financial factors.
Q: What are the top three challenges physician practices and health systems face in managing finances today?
MT: Ultimately, health systems need to maintain financial viability. Yes, it sounds pretty basic, but "keeping the doors open" is a top-line concern for providers of all sizes. To do this, they need to accelerate reimbursement, remove obstacles to payment, reduce bad debt and take advantage of new technologies to harness data for performance improvements.
Second, managing and preventing claim denials. This is the big obstacle to payment. Today, as many as one in five claims for services already rendered are denied. And although the industry too often views denials as a back-of-the-house, patient-handling problem, studies reveal that 30 to 40 percent of denials are attributed to registration errors. Denials are not limited to the revenue cycle, but cross the clinical realm as well. Denials erode the provider organization's bottom line, resulting in the permanent loss of an estimated 3 percent of net revenue, so they remain a big challenge. While about two-thirds of denials are recoverable, almost all (90 percent) are preventable.
Also, aligning the clinical and financial experience is a top challenge. The patient financial experience can be as important as the clinical one. Let's face it, a poor billing experience can undo all the goodwill of brilliant clinical care — especially when patients are paying a higher portion of their medical costs. So having the right patient access and analytics-driven claims management systems in place — and making sure they are tightly integrated with the EHR/practice management system — goes a long way toward fostering patient satisfaction.
Q: What's the best strategy to pinpoint and address these problems?
MT: Healthcare generates a huge amount of data. Registration data, financial data, claims data. Any good denial prevention/resolution process must be grounded in core analytics — using tools to understand available data to determine where the problems lie. But even with good data we need organizational support. Data should not be used as a weapon. It should be used as informative and interchanging.
While about two-thirds of denials are recoverable, almost all are preventable. So identifying and resolving the root causes of denials has a larger financial benefit than appealing and overturning them. Managing denials begins with using available data to analyze where errors and slowdowns occur, prioritizing those causes, and then addressing them.
Root causes can originate anywhere — from patient access and registration, insufficient documentation and coding/billing errors to payer behavior and utilization/case management. Once the root cause is identified, it must be analyzed to determine which has the greatest impact: whether it's a certain physician, service line, or payer, a certain type of code, or a process in need of redesign in both the clinical and revenue cycle areas. Armed with an analysis, providers can begin to both prevent and manage denials in a more strategic, deliberate manner.
Q: How can providers work more collaboratively with payers on these problems?
MT: What's needed is a more holistic approach to revenue cycle management — one that sets up the entire process for success and minimizes the time -and resource-intensive back-and-forth that can hinder progress. It begins with prior authorization — determining if an authorization is required by the payer — and if it is in place. This remains a needlessly manual process. Accurate registration and eligibility data is needed to pave the way for all downstream revenue cycle processes. Real-time registration quality assurance can go a long way toward ensuring clean claims and accurate, timely reimbursement. If providers have the tools and processes in place to minimize manual touch points and reduce the endless cycle of phone-fax-email-payer portal searching, there will be fewer denials and a lot more harmony.
Q: What are the key performance indicators or other financial benchmarks a practice or hospital should monitor to improve financial performance?
MT: In no particular order, I'd recommend keeping an eye on these metrics:
First, there's payment velocity, which is another way of saying, "How fast are you getting paid?" Accounts receivable days is the industry standard metric, and increases in accounts receivable days usually indicate a process problem, such as how fast claims are getting out the door. Finding the root cause of the slowdown and having easy-to-interpret data to share with stakeholders in problem areas is critical to making timely improvements to keep cash moving.
Then there's claim quality. Something is wrong when denials start to climb. Identifying the root cause early, and having the data to support appeals, can help get the affected processes back on track and the denial rate back in line. Establish alerts for timely filing thresholds to ensure your team doesn't miss filing deadlines.
Reimbursement rate looks at how effectively you are getting paid at contracted rates, and how effectively you are collecting payments from patients. Even the slightest shifts in reimbursement can have seismic impact on the bottom line. And the advent of alternative reimbursements models, such as bundled payments, further complicates the issue.
Also look at quality and productivity metrics. Discharged not final billed shows how long it's taking to get a claim out the door. It's also the most likely KPI to light up early due to improper integration between the clinical and financial systems. That's why it's crucial to establish integration points between the systems.
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