C812 Task 2 Value-Based Payment Analysis Example

A Point and a Half Above the Line: MIPS Goals, Scoring and the Coding Behind a Composite Internal Medicine Group's Payment Adjustment

Student Name

Leavitt School of Health, Western Governors University

C812: Healthcare Reimbursement, Task 2

Course Instructor

Month Day, Year

A Point and a Half Above the Line: MIPS Goals, Scoring and the Coding Behind a Composite Internal Medicine Group's Payment Adjustment

From Paying for Volume to Paying for Value

For most of its history, Medicare paid physicians a fee for each service, so a practice earned more by doing more, whether or not patients were better off. The Medicare Access and CHIP Reauthorization Act of 2015 replaced the old formula for updating physician payments with the Quality Payment Program, which has two tracks: advanced alternative payment models, in which clinicians take on financial risk for outcomes, and the Merit-based Incentive Payment System (MIPS), which adjusts fee-for-service payments up or down based on performance. This paper explains the goals of MIPS, how clinicians are scored, how a score turns into a payment adjustment, and why coding and documentation have such a large effect on the result. It uses a composite 14-clinician internal medicine group in the 2025 performance year as its example.

Goals of MIPS

MIPS was designed to tie a clinician's Medicare payment to the value of the care they provide rather than its volume alone. Its goals can be summarized in four parts. It aims to reward higher quality and lower cost by measuring both and adjusting payment accordingly. It aims to consolidate earlier, separate programs, including the Physician Quality Reporting System, the value-based payment modifier and the Medicare electronic health record incentive program, into one system with one score. It aims to encourage the use of certified health information technology to share information and engage patients. And it aims to promote continuous improvement in clinical practice by crediting activities such as care coordination and population management (Centers for Medicare & Medicaid Services [CMS], 2025). A further aim, stated by CMS from the beginning, is to move clinicians gradually toward alternative payment models that pay for outcomes more directly.

Performance Categories and Scoring

Each eligible clinician or group receives a final score from 0 to 100 built from four performance categories. The weights shown are those for the 2025 performance year; CMS sets them each year and can reweight categories when a clinician has no applicable measures.

From Score to Payment Adjustment

The final score is compared with a performance threshold, set at 75 points for the 2025 performance year. Clinicians scoring exactly at the threshold receive no adjustment. Those above it receive a positive adjustment that rises with the score, and those below it receive a negative adjustment of up to 9% for the lowest scores. Because the program must be budget neutral, the positive adjustments are funded by the negative ones, so a strong score often earns a smaller bonus than the maximum penalty. The adjustment applies to payments for covered professional services two years after the performance year, so 2025 performance affects 2027 payments.

For the composite group, the 2025 results are illustrative. The group earned 78% of the available quality points, 60% of cost points, 80% of promoting interoperability points and full credit for improvement activities. Its final score is therefore 23.4 for quality (78% of 30), 18.0 for cost (60% of 30), 20.0 for promoting interoperability (80% of 25) and 15.0 for improvement activities, for a total of 76.4. That is 1.4 points above the threshold, enough for a small positive adjustment in 2027. The margin is thin. A drop of five percentage points in either quality or cost performance would have pushed the group below the threshold and into a negative adjustment.

Why Coding and Documentation Matter

Coding affects MIPS in ways that practices often underestimate. The cost category compares the Medicare spending for a group's attributed patients with the spending expected for patients like them, and that expected amount is calculated from the patients' risk scores. Risk scores are built from diagnosis codes submitted on claims during the year. If a patient has diabetes with kidney complications, heart failure and depression but the claims show only 'type 2 diabetes without complications', the patient appears healthier than they are, the expected spending is set too low and the group's actual spending looks high. Incomplete diagnosis coding can therefore lower a cost score even when care was efficient.

Quality measures depend on codes too. Many measures identify eligible patients by diagnosis codes and count successes by specific codes or structured data, such as a result value or a code showing a screening was performed. A diabetic patient whose diabetes is not coded may drop out of the measure entirely; a screening performed but recorded only in free text may count as not performed. Documentation that is complete and structured, and coding that captures every condition the clinician addressed and supported, are therefore part of how value is measured.

This matters because MIPS scores can reflect data and patient mix as much as care. Researchers found that physicians who cared for more socially at-risk patients received lower MIPS scores on average (Khullar et al., 2020), and a later study of primary care physicians found that MIPS scores were only inconsistently associated with performance on process and outcome measures, suggesting that the program may not reliably identify better care (Bond et al., 2022). A practice cannot fix the program's design, but it can make sure its own data are accurate.

Recommendations for the Group

Four steps would protect the group's position. First, a quarterly documentation and coding review of a sample of visits for patients with chronic conditions, checking that each condition addressed in the visit is documented and coded to its full specificity. Second, a review of quality measure data before submission to find patients missing from denominators or screenings recorded in free text rather than structured fields. Third, measure selection guided by the group's strengths: choosing quality measures on which the group performs well and has enough patients for a stable rate. Fourth, a monthly review of the feedback reports CMS provides, so problems are found during the year rather than after it. Together these steps put the group's score on firmer ground and reduce the risk that a data problem, rather than the quality of care, decides its payment.

References

Bond, A. M., Schpero, W. L., Casalino, L. P., Zhang, M., & Khullar, D. (2022). Association between individual primary care physician Merit-based Incentive Payment System score and measures of process and patient outcomes. JAMA, 328(21), 2136-2146. https://doi.org/10.1001/jama.2022.20619

Centers for Medicare & Medicaid Services. (2025). MIPS overview. Quality Payment Program. https://qpp.cms.gov/mips/overview

Khullar, D., Schpero, W. L., Bond, A. M., Qian, Y., & Casalino, L. P. (2020). Association between patient social risk and physician performance scores in the first year of the Merit-based Incentive Payment System. JAMA, 324(10), 975-983. https://doi.org/10.1001/jama.2020.13129