Does MACRA Signal the Beginning of the End for Medicare Claims Data?

by Jason S. Brinkley, PhD, MA, MS

On the Brink addresses topics related to data, analytics, and visualizations on personal health and public health research. This column explores current practices in the health arena and how both the data and mathematical sciences have an impact. (The opinions and views represented here are the author’s own and do not reflect any group for which the author has an association.)

Jason S. Brinkley, PhD, MA, MS

Jason S. Brinkley, PhD, MA, MS

The new year has seen intense discussion of the future of the Affordable Care Act (ACA), with debate regarding the ins and outs of a potential repeal. With so much focus on the ACA, it seems that less attention is being paid to another large initiative, which has the potential to create greater ripple effects across every sector of health care. The Medicare Access and CHIP Reauthorization Act (MACRA) was signed into law in April 2015 and with it comes a great number of changes in how Medicare will do business. These changes have the potential to impact not only how services are provided but also could affect data collection and reporting, which in turn has a big impact on deciphering what we know about health care costs and the health status of America’s seniors.

First, a little background; original Medicare fee-for-service (FFS) runs very similar to private health insurance in that physicians, hospitals, and others perform services on Medicare beneficiaries and then are reimbursed for those services. Reimbursements are based on claims data that list out which services were provided to the patient. Critics of FFS suggest that this leads to unnecessary testing and inflated costs, that one of the current problems in the health care system is that we aren’t getting value for our dollar. There has been increasing attention towards bending the health care cost curve by shifting the focus to pay for performance; that is, to create a different arrangement where health care provider reimbursement is somehow tied to quality. MACRA is a big step forward in that it forces providers to eventually select one of two avenues of reimbursement (referred to as the Quality Payment System).

The first is the Merit-based Incentive Payment System (MIPS), which will act more like traditional Medicare but with a system of bonuses and penalties based on important factors like quality and costs. The second route is the Advanced Alternative Payment Models (APM), a set of alternative payment structures that some can adopt that provide payment in a different form, which is (in general) not FFS and assumes some financial risk in treating patients. MACRA establishes payment guidelines that offer much greater financial incentives for organizations that follow the APM model. There are several different APM options a provider or group could adopt. Understanding all the aspects of MACRA can be time-consuming, and I would direct the interested reader to the Centers for Medicare and Medicaid Services website or to this American Hospital Association website for a complete and thorough breakdown.

So, long story short: Medicare is changing, with incentives for provider groups to go to an APM, which moves away from the fee-for-service model. While all of this may seem important to providers, it isn’t immediately clear how this impacts public health data, research, or policy. Researchers have increasingly relied on Medicare claims data to understand the US health care system and the general health of America’s seniors. A simple Google Scholar search for ‘Medicare Claims’ for articles in 2015 and 2016 returns over 16,000 articles. JPHMP readers may recall an article by Erdem et al from 2014 that explored publicly available FFS data to show the health status of America’s seniors in terms of number of chronic conditions, hospital admission, costs, and most common conditions. Such summaries provide us an important snapshot of where the country is as a whole and allow us to compare specific areas to national aggregates and help identify potential disparities and preventable over-utilization.

To see how changes in claims data may be important, consider Medicare Advantage, which (since the 1980s) has been an important alternative to original Medicare. As described on the Medicare website, “Medicare pays a fixed amount for your care each month to the companies offering Medicare Advantage Plans.” So a Medicare Advantage plan is obtained from a private insurer, and Medicare pays it to manage that person’s health care. Medicare Advantage can sometimes be an attractive alternative for seniors in that it covers some things that traditional Medicare does not cover (eg, dental or vision) and is usually encouraged for seniors who are in relatively good health. As Brown et al points out, Medicare Advantage providers are not required to turn in individual cost or claims data since private companies negotiate the reimbursements of services with providers and reporting this information impacts their ability to perform those negotiations.

The ripple effects on a lack of claims data for Medicare Advantage participants (estimated to be at least 25% of Medicare’s 50 million+ enrollees) has a big impact on research where the majority of what we know from such data only covers the 75% enrolled in FFS. Questions arise as to how good our national estimates are based on data that are missing up to 25% of the US senior population. Researchers work to correct for this problem and those efforts are aided by the idea that Medicare Advantage participants are often healthier and put less burden on the health care system, although this claim has been challenged by some researchers recently.

So how does MACRA change all of this? It is possible that the APM route may present the same challenges and burdens in cost and claims data collection as Medicare Advantage, and as such, APM providers may be eventually freed from these requirements. MACRA’s changes are important in that it allows the provider to decide which payment model to follow and not the patient as is the case in original Medicare versus Medicare Advantage. It isn’t clear what impact that switch will have on claims data and our ability to use them for research. The nature of the APM framework is to aggregate many services into a single claim, which can impact the frequency and types of claims that may be filed. We may not be able to make the same assumptions that we make for the Medicare Advantage seniors, and those assumptions are key in our general understanding of the information we get from claims data. Right now, APM is comprised of various models with different incentives and implications for the quality of claims for research.

Is the loss of these data a forgone conclusion? Not necessarily. MACRA entails changing payment systems, not changing reporting of claims. Likewise, MACRA offers other bonuses that researchers will eventually be able to make use of such as incentives for providers to adopt electronic health records, which offer researchers a potent avenue for higher quality data on health services, conditions, and utilization. It is important that the research community stays up to date on these changes and understands how these large initiatives impact not only providers on the ground but also how we gain information for reporting and research purposes.

That’s all for today. Join us again next month to explore more big ideas in data and health. In the meantime, follow me on Twitter @DrJasonBrinkley and feel free to send me comments and rebuttal on this or any of my other posts. I’m not an expert on MACRA, so I would like to thank friends and colleagues whose insights helped shape this post.

Jason S. Brinkley, PhD, MS, MA is a Senior Researcher and Biostatistician at the American Institutes for Research where he works on a wide variety of data for health services, policy, and disparities research. He maintains a research affiliation with the North Carolina Agromedicine Institute and serves on the executive committee for the NC Chapter of the American Statistical Association and the Southeast SAS Users Group. Follow him on Twitter. [Full Bio]

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