Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following Coronary Artery Bypass Graft (CABG) Surgery

The Kansas Hospital Associaton has concerns regarding the substantive changes identified in this measure.

The inclusion of Medicare Advantage (MA) beneficiaries raises concern, as hospitals have limited ability to account for or influence MA plan utilization management policies, including prior authorization requirements, network limitations, plan directed discharges and post-acute care restrictions. These plan-level factors may affect utilization outcomes in ways that are unrelated to hospital performance and could introduce variability that is outside the hospital’s control.

We recommend reconsideration of the inclusion of MA beneficiaries in the cohort utilization calculations to ensure the measure more accurately reflects hospital performance.

The American Medical Association (AMA) believes that additional analyses are needed before revised measures are implemented. Like our concerns raised on the readmission and excess days in acute care measures, it is not clear to what degree is the reported association of lower readmissions with higher mortality found over longer or shorter time periods such as, one year or one week, as compared to the first 30-days post discharge. Gupta and co-authors report that the inverse association was still evident at one year.² To what degree are any positive or negative correlations related to all-cause mortality and/or readmissions versus the condition-specific outcome? It is also worth examining whether trends exist based on unadjusted data and adjusted data. Most of the studies identified through our search of the literature, including Dharmarajan, et al.[1], used risk-adjusted data. Most individual patient care decisions are not made with risk-adjustment in mind. To better understand the outliers (those who died), there is a need to investigate and determine whether there is small, but important associations between patient mortality and readmissions rates. Therefore, are we masking the issue by only examining the adjusted rates? Examination of unadjusted and risk-adjusted rates could help address this concern. We also believe that the timeframe of the mortality measures and whether the post discharge period is appropriate must be reexamined.

In addition, this measure includes some of the same changes that CMS has made to the readmission measures in Hospital Readmissions Reduction Program (HRRP); specifically, the risk adjustment model was updated to use individual ICD-10 codes rather than the CMS Hierarchical Condition Category (HCC) model; the measure now includes Medicare Advantage (MA) beneficiaries; and the data collection timeframe is two years. How each of these changes impact the reliability and validity of the measure has not been provided in this submission and we are concerned that without a phased approach, it will be extremely difficult for hospitals to determine their impact (e.g., what is the effect of the expansion to MA beneficiaries as compared to the reduction in the number of years of data used to calculate the measure). We also recommend CMS provide data on how hospitals’ performance shift since the potential impact on each hospital is critical to ensure that the results can be used to drive further improvement in patient care.

Lastly, we also question the lack of socio-economic factors in the risk adjustment due to evidence that hospitals with larger populations of poor patients perform poorly on the measures. We recognize that some of the measures have been tested to consider economic related variables; however, we do not believe the appropriate risk models were tested. The traditional approach of risk adjusting at the patient level may not be appropriate for measures where the measurement period includes care that is outside of the control of the hospital and a 30-day post-acute phase where the availability of community supports, and other resources directly impact a patient’s care. We believe that there may be community-level variables that affect the risk of mortality during the days following hospital admission but are not currently addressed. Measures that extend beyond the hospital stay or outside the locus of control of the measured entity should continue to have socio-economic adjustments addressed and analyzed at different levels (e.g., patient, hospital, and community). 

Due to these concerns and unanswered questions, the AMA does not support inclusion of this measure in the Hospital Inpatient Quality Reporting Program or the Hospital Value-Based Purchasing Program.

[1] Dharmarajan, Wang, Lin, et al. Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge. JAMA. 2017;318:270-278.

As the agency did in last year’s PRMR process, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. We appreciate the general effects this change would have to improve the accuracy and timeliness of this measure, namely doubling the patient cohort and allowing CMS to shorten the performance period. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HVBP program, and testing has only been conducted on the existing (rather than updated) measure using one year of data from 2024. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HVBP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the payments hospitals experience under the HVBP program. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HVBP program and the hospitals that participate in it.

Vizient appreciates efforts to update the MUC2025-046: Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following Coronary Artery Bypass Graft (CABG) Surgery measure by adding Medicare Advantage (MA) population data as more than half of Medicare patients are covered through MA plans. While Vizient recognizes the importance of updating quality measures to reflect a broader range of Medicare beneficiaries, we continue to believe that additional steps are needed to ensure that MA data can be used reliably alongside fee-for-service (FFS) data. For example, as noted in Vizient’s FY 2026 IPPS Proposed Rule comments, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that an analysis to identify the impact of these types of differences has been completed. Vizient encourages P4QM to consider our recommendation that CMS analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

In addition, another important consideration is that MA populations can vary significantly across plans, and in some cases may be selectively healthier. Without careful attention to appropriate risk adjustment, these differences could unintentionally bias performance results. Ensuring that MA data are risk‑adjusted correctly is essential for fair and meaningful comparisons across hospitals.

We request transparent model specifications, transition periods, and social risk adjustment to avoid penalizing hospitals serving vulnerable populations. 

Premier supports Hospital-Level, 30-Day, Risk-Standardized Mortality Rate quality measures. Given the growth in Medicare Advantage (MA) enrollment, Premier supports the expansion of these measures to include MA beneficiaries.

However, Premier questions the application of these quality measures for improvement purposes when the data lags by two years. This can impact both the observed performance by not reflecting today’s outcomes and the risk adjustment by using older data to create expected values for more recent patients. Premier has also observed that the risk standardized results do not change much over time and may not reflect performance improvement because it is heavily driven by the random effect in the model. The use of the Predicted to Expected ratio rather than the Observed to Expected ratio, while helpful to reduce undue influence from outliers, does not provide a good reflection of actual performance. Consequently, CMS should emphasize that this methodology is best suited for payment purposes and not quality improvement purposes. The utility of the measure is further hindered by the facility level hierarchical methodology, which does not allow for drill downs into further subgroups, e.g. by physician grouping.   

Additionally, Premier is concerned that the quality measurement risk adjustment methodology developed by CMS does not perform well. Premier disagrees with the prior research methodology committee’s decision that a C-statistic of 0.6 for model performance is sufficient to use the risk model to adjust quality measure performance. Similarly, the thresholds for validation and reliability are also too low for both public reporting and payment purposes. CMS should revisit its methodology immediately to ensure it is rewarding and/or penalizing hospitals accurately. 

Support with modification: Requires careful attribution to avoid penalizing MA Plans for facility-driven variation.

The American Occupational Therapy Association (AOTA) supports capturing data for Medicare Advantage (MA) beneficiaries in the Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following CABG Surgery measure. Including MA data is critical to providing a complete and accurate picture of outcomes, given the growing enrollment in MA plans. This addition will enhance transparency, allow for meaningful comparisons across coverage types, and ensure accountability for all payers to cover necessary, high-quality care provided to Medicare beneficiaries.