Tag Archives: Charlie Mills

Transition from RAPS to EDS data decreases Medicare Advantage risk scores

Milliman consultants Deana Bell, David Koenig, and Charlie Mills performed a study of how the transition from Risk Adjustment Processing System (RAPS) data to Encounter Data System (EDS) data is affecting payment year (PY) 2016 risk scores and revenue for Medicare Advantage organizations (MAOs). Fifteen MAOs participated in the study, reflecting a cross section of small- and medium-sized organizations and representing over 900,000 members in 154 plans. The consultants offer perspective in their article “Impact of the transition from RAPS to EDS on Medicare Advantage risk scores.”

Overall, the study found that the median percentage difference between PY 2016 risk scores based on RAPS and the EDS-based risk scores is 4.0%. The percentage difference is larger for special needs plans (SNPs) and smaller for general enrollment plans as shown in Figure 1. The prior year’s diagnoses make up a larger component of SNP members’ risk scores, compared to general enrollment plans, so the risk score impact for SNP plans is larger.

[The authors] have not attempted to quantify what portion of the difference between RAPS and EDS is due to incompleteness of the EDS submissions, issues with CMS’s return files (revised MAO-004 files), changes to filtering logic, and the effect of claims coding errors.

As an illustration, the potential Part C PY 2016 revenue using the median difference of -4% between RAPS and EDS results in a reduction of approximately $40 per member per year, assuming approximately $800 in Part C risk-adjusted revenue and a 1.0 RAPS-only risk score. To the extent that this -4% gap persists in future years, the revenue impact will grow because the EDS-based risk score will make up an increasing portion of the final risk score (e.g., with the 25% EDS weight in PY 2017, the per member reduction would be about $100 per year).

This article is the second in a series of articles on the transition to EDS. For more information about the EDS and RAPS data used in MA risk scores, read “Medicare Advantage and the Encounter Data Processing System: Be prepared.”

Benchmarking analytics for provider reimbursements

Managing provider reimbursement levels is an important function for health plans. Provider reimbursement analytics can offer health plans the foundation they need to effectively manage reimbursements.

In their article “Provider reimbursement analytics,” Milliman consultants David Lewis and Charlie Mills highlight the advantages and disadvantages of the two primary analytical approaches for evaluating provider reimbursement levels. The authors also discuss the pros and cons of the three main baseline fee schedules used in provider contract benchmarking, one of which includes Milliman GlobalRVUsTM.

Encounter data submission consideration for Medicare Advantage organizations

The Centers for Medicare and Medicaid Services (CMS) is shifting to the Encounter Data System (EDS) as the sole basis for risk scores of Medicare Advantage organizations (MAOs). EDS data will have a substantial influence on risk scores and revenue as early as payment year (PY) 2016.

In this article, Milliman consultants offer perspective on several analyses MAOs should consider to prepare data submissions for CMS. The authors also discuss some challenges MAOs may face when verifying that the data submitted through the EDS are complete and accurate and that all appropriate diagnosis codes are being accepted for risk adjustment by CMS.

Here’s an excerpt:

To provide an effective review of an MAO’s diagnosis code submissions, the following analytics can be undertaken:

• Calculation of risk scores from each diagnosis source: RAPS, EDS, and source claims/ chart review data
• Plan-level and member-level comparisons of risk scores based on each diagnosis source
• Analysis of submission gaps
• Analysis of coding gaps

To perform the EDS submission review, a possible first step is to create a “plan report card,” which summarizes the risk scores under accepted RAPS and EDS submissions and the risk scores based on all diagnosis sources (claims and chart review data) after applying the MAO’s specific RAPS filtering logic and the EDS filtering logic released by CMS.

Figure 1 provides an example of a potential Plan Report Card for PY 2016 EDS submission review. In this example, there is a 4.1% gap between the EDS risk scores and the risk scores after the MAO applied the EDS filtering logic to the source claims data. Also, based on the CMS return data, the EDS risk scores are four points lower than the RAPS scores. This indicates that the EDS submissions may be incomplete and that there are diagnoses in the source claims data that the CMS filtering logic has rejected.

encounter-data-processing-system_figure-1

If submissions to CMS contain all necessary data elements to successfully pass the filtering logic, the risk scores based on RAPS and EDS return data should match the risk scores calculated from the source claims and chart review data. In addition, if the RAPS and EDS filtering logic are the same, the RAPS and EDS risk scores should also be the same. However, there can be gaps between what is submitted and accepted by CMS and the claims and chart review data because of:

• Incomplete data submissions (e.g., claims being inadvertently filtered out or dropped, missing chart review data)
• Inaccurate data submissions (e.g., the wrong medical codes, such as incorrect bill type, being used in the submissions)
• CMS system errors (e.g., failure to match diagnosis data with the correct member)
• Other potential process errors

Furthermore, comparison of the RAPS and EDS risk scores will indicate whether the MAO’s revenue is being adversely affected by the move from RAPS to EDS. A focused look at the MAO’s own coding practices as they compare to Medicare FFS coding standards and EDS filter criteria can identify the coding gaps that may drive lower risk scores under EDS.

Qualifying APM participant considerations

This paper by Milliman’s Charlie Mills, Pamela Pelizzari, and Christopher Kunkel explores the challenges and opportunities regarding participation in an Advanced Alternative Payment Model (APM) track under the Medicare Access and CHIP Reauthorization Act (MACRA). The authors also discuss why becoming Qualifying APM Participants (QPs) may be desirable to some providers as well as the risks they might encounter through the process.

Here is an excerpt from the article:

Opportunities associated with QP status

Financial opportunities

Despite the potential downsides to participating in Advanced APMs and seeing QP status, there are also potential financial benefits, including the following:

A lump-sum payment equal to 5% of their prior year’s payments for Part B covered professional services. QPs can become eligible for this lump-sum incentive payment for years 2019 through 2024. Overall, this is the primary financial opportunity for QPs.

Insulation from the potential downside of the MIPS adjustment. In general, MIPS is a budget-neutral (i.e., zero-sum) program, with a financial downside of 4% in 2019, growing to 9% in 2022. Because QPs and Partial QPs are excluded from MIPS, they are not exposed to MIPS’s downside and do not have to navigate the hundreds of quality and performance measures that make up MIPS.

Opportunities for shared savings from the Advanced APM. QPs will have the opportunity to share in gains (and will generally be required to share in losses) from the Advanced APMs they participate in.

Higher conversion factor increases starting in 2026. Starting in payment year 2026, QPs will receive a conversion factor increase of 0.75% compared with 0.25% for non-QPs. Over time, this could result in significantly higher payment rates for QPs versus non-QPs.

Clinical integration benefits

Several of the currently available Advanced APMs aim to align incentives across different types of providers. For example, ACOs encourage physicians and hospitals to work together to ensure beneficiaries receive appropriate care that can keep them healthy and out of hospitals. In many cases, however, individual physicians do not see the financial benefits of these programs without entering into what can be complex and time-consuming gainsharing arrangements. By providing a 5% lump-sum incentive payment to QPs, MACRA serves to create an even greater incentive for physicians to participate actively in Advanced APMs.

While other payer Advanced APMs do not contribute to QP threshold calculations until performance year 2019 (incentive payment year 2021), it’s possible that the increased engagement physicians have in Advanced APMs that is due to MACRA will have trickle-down effects on other lines of business and patient populations beyond Medicare fee-for-service. This could serve to improve the quality of care and reduce costs for patients covered by other payers.

Benchmarking provider cost using Medicare allowed

There are many reliable research statistics from the private sector and the federal agencies that support the evidence that medical costs are rising and the current pace is unsustainable. Medical cost trend has two primary components, the number of services provided to patients (utilization) and the cost of each of those services (unit cost). While utilization management can be important for achieving cost savings, some employers are now giving further attention to the significant price variation in unit cost. Chart 1 below provides an example of the price variation using the average reimbursement as a percentage of Medicare in Buffalo, New York; Indianapolis, Indiana; Ventura, California; and nationwide. As shown, going from Buffalo to Indianapolis reflects an 80% increase in cost, based on unit price alone.

Benchmarking provider cost using Medicare allowed_Figure 1

We regularly encounter employers who don’t fully understand the impact of provider reimbursement variation on their medical plans’ financial performances. This comes as no surprise, given the limited transparency and complexity of current provider reimbursements.

Limited transparency of provider reimbursement (allowed charges)
For employers, the industry standard technique of benchmarking commercial allowable charges has historically been traditional discount analyses, which compare discounts to billed charges. However, these approaches do not provide the required rigor and precision to understand medical service reimbursement analysis—both across markets and within a given market. This is because billed charges are not standardized across providers or different services. As a result, the exact same discount could mean very different things, depending on the provider and service—in some cases, price differences of over 300%. In addition, providers often optimize their billed charges to enhance reimbursement on contracts based on billed charges.

Complexity
Employers generally have had a difficult time measuring unit cost, which is solely due to the complexity of various medical procedures. There is a large amount of price variation within each inpatient diagnosis-related group (DRG) and outpatient type of service. Chart 2 below provides a powerful illustration of how reimbursement can vary significantly across even a single inpatient DRG or outpatient service category. The chart compares the commercial reimbursement for inpatient joint replacement and an outpatient MRI in three different metropolitan areas with what the government would pay under Medicare allowable. The variation in inpatient joint replacements, a large bundle of complicated services, is much lower than outpatient MRIs, which reflects a specific service that generally has little variation in intensity compared with a joint replacement.

Benchmarking provider cost using Medicare allowed_Figure 2

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What are the key financial considerations for providers when evaluating the Next Generation ACO Model?

The Department of Health and Human Services (HHS) is striving to link 50% of Medicare payments to alternative payment models by 2018. One of the primary alternative payment models offered to Medicare providers is the Next Generation Accountable Care Organization (NGACO). Due to the potential large risk exposure for organizations considering this model, they should work with an actuary to understand the critical elements driving financial success (or failure). In this article, Milliman’s Charlie Mills, Cory Gusland, and Noah Champagne identify five key financial considerations that all ACOs should review before committing to the program. The considerations are ranked by the authors’ perceived importance, with one being the most important.

5. ACO’s CY2014 experience is the baseline for the first three performance years
4. Risk score changes are capped at 3% from the baseline year to each performance year
3. First dollar savings and losses
2. The 2016 benchmark trends are likely understated
1. In order to achieve savings, participants must outperform trended baseline less discount