The reasons for the healthcare industry’s shift to value-based care (VBC) are clear and obvious: promoting better care at reduced cost for patients. The reality of its implementation, though, is far more complicated. The move away from fee-for-service (FFS) models has been slower than many in the industry anticipated, but there are signs that momentum is picking up.
Part of the reason for the slow transition is the financial challenges value-based care can create for hospitals. Let’s examine the impact VBC can have on the revenue cycle, and what analytics can do to help.
The shift to a value-based model
The Obama administration oversaw the shift to what it hoped would be a more affordable healthcare system by replacing the FFS model, which stressed quantity of care over quality, with a value-based system. From a national policy perspective, the Affordable Care Act (ACA) reduced spending on Medicare but increased incentive-based payments to hospitals that operated efficiently. The ACA essentially shortened the healthcare industry’s financial leash and told them to behave better.
Similarly, 2015’s MACRA legislation bolstered both the Merit-Based Incentive Payments System (MIPS) and gave bonus payments for participation in Alternative Payment Models (APMs). These national initiatives, combined with like-minded actions on the state level, have incentivized the movement towards value-based healthcare. A 2030 deadline to transition most of Medicare and Medicaid spending to accountable care means that more and more healthcare providers are currently taking action.
The changes have been beneficial for patients but have meant tighter margins for hospitals. This has resulted in revenue cycle issues that must be faced in this new reimbursement landscape.
What are the challenges caused by value-based care?
The new reimbursement structure is complex, and this has had an impact on hospitals’ revenue cycles. For example, decreased Medicare expenditure and a change in employers’ healthcare plans have increased the cost of deductibles in recent years.
The Centers for Medicare and Medicaid Services (CMS) reports that in 2022, out-of-pocket spending grew 6.6% to $471.4 billion, or 11 percent of total national health expenditure. As a result, hospitals have had to change their payment structures to collect more money from patients, who are less reliable when it comes to paying than the government or private insurers are. More financial burden for patients means greater stress for hospital administrators and more cracks for revenue to slip through. This financial leakage has become a serious problem. Incorrect billing information can cost hospitals tens of millions of dollars a year.
A payment structure more reliant on patients is clearly the new norm as hospitals increasingly adopt value-based models and baby boomers move into their late 60s and 70s. To face this issue, health systems would do well to implement analytics tools to handle the ocean of data that is threatening to flood their collection process.
How can analytics help?
From a data perspective, an analytics tool offers health systems a view of their financial situation that is not possible with simple EHR reports. The increasing number of players has resulted in far too much information to process for even the most capable of hospitals.
Revenue cycle analytics can combine reports from across a health system into one dashboard. Analytics can also be employed to boost customer satisfaction in the healthcare process. With patients footing a large portion of the bill, it is paramount that there be correct information and a smooth collection process. An otherwise easy trip to the physician can be completely spoiled by a poor experience at the front desk. Revenue cycle analytics can spot problems along the revenue stream faster than individual reports and allow administrators to dive deep into the data to root out the cause of the issue. Along with data solutions, an analytics tool also offers solutions for people problems within a health system.
The industry-wide shift towards value-based care is a problem for many health systems and data analytics is not a panacea for struggling revenue cycles. But the tool can be effectively used to ease financial analysis for administrators facing an overwhelming number of reports or to spot misidentified patients before problems arise. All of these factors improve a hospital’s revenue cycle in a value-based reimbursement structure that puts increasing pressure on the institution’s bottom line.
To learn more about what Dimensional Insight can do to help you tackle revenue cycle analytics, click here.
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