PRMR MUC List

Prediabetes affects 98 million American adults but less than 20% are aware of their condition. The Diabetes Prevention Program is an evidence-based program that reduces the risk of type 2 diabetes among adults with prediabetes. If more people were screened for and diagnosed with prediabetes, including vulnerable populations with increased risk, they could be referred to these programs and reduce their risk of type 2 diabetes by more than half. Increasing awareness of prediabetes is a priority of the United States Preventive Services Task Force (USPSTF) which in 2021 recommended that all adults aged 35-70 with overweight or obesity be screened for prediabetes and type 2 diabetes. The National Clinical Care Commission (NCCC) and the Secretary of Health and Human Services (HHS) called for adopting the screening measure, and Healthy People 2030 has several related objectives including to reduce the proportion of adults who don't know they have prediabetes, which has seen little detectable progress in the last 10 years. Incentivizing the healthcare system to test for prediabetes can help to move the needle on this important issue and is a strategy to address other Healthy People objectives, including to reduce the number of diabetes cases diagnosed yearly, reduce the rate of death from any cause in adults with diabetes, and to increase the proportion of eligible people completing CDC-recognized type 2 diabetes prevention programs. Prevention has been largely neglected in the healthcare system and programs like the Diabetes Prevention Program exist but are underfunded and often underutilized. Incentivizing the diagnosis of prediabetes could lead more people to Diabetes Prevention Programs, reduce rates of diabetes, improve health outcomes and reduce healthcare expenditures for individuals and payors. We urge CMS to implement prediabetes quality measures immediately, so we can help reduce the nationwide burden of diabetes.
Submitted on behalf of:
Jeannette M. Beasley, PhD, MPH, RD
Joshua Chodosh, MD, MSHS
Melanie Jay, MD, MS
Mary Sevick, ScD
Erin Rogers, DrPH, MPH
Nicholas Illenberger, PhD
Scott Sherman, MD, MPH
Earle Chambers, PhD, MPH
Devin Mann, MD, MS
Judith Wylie-Rosett, EdD
Ira Goldberg, MD
Sondra Zabar, MD
Julia Adamian, MD
 

On behalf of Trinity Health, one of the nation's largest Catholic health systems, I broadly endorse this measure to screen for abnormal glucose metabolism, i.e. diabetes or pre-diabetes.

As proposed, this measure would apply, in essence, to all of those 35-70 with an overweight or obese BMI who don’t have previously documented diabetes or pre-diabetes and haven’t been recently screened; this would likely represent a large segment of the U.S. adult population.  Screening every patient in that cohort who has two office visits for any reason during the year is a significant ask.  I’d like to see that “two office visits” language removed and have this screening be an expectation only of those who have a preventative visit.

Daniel Weiswasser, MD

Chief Medical Officer, Medical Groups and Clinical Integration 

Trinity Health

The AAFP appreciates the intent of this measure, and we support the measurement of patient outcomes in general. In our new position paper, Performance Measurement in Value-based Payment Models for Primary Care, we acknowledge the growing focus and importance of outcome measures and patient-reported outcome measures in value-based payment models. “…As the value movement matures, so does the evolution of performance measurement, moving beyond simple process metrics to increasingly prioritizing the measurement and rewarding of outcomes, including PROMs. Despite these advances, accurately measuring outcomes remains challenging, and there is room for continued improvement.^34”

We understand that measurement is one way to push toward quality, outcome, and system improvement. However, we do not support the addition of this measure for use in the CMS MIPS program at this time. We would like to note the following concerns:  

• As currently specified, the measure does not meet the criteria for “meaningfulness.” 
• As clinicians on the TEP noted, there is concern about being held responsible for the quality of life of patients with neurodegenerative disorders with the consideration stated that, more often than not, neurology patients’ health and quality of life gets worse over time due to the disease course, regardless of treatments.
  • Therefore, a physician may be unfairly penalized if they treat a larger percentage of patients with chronic degenerative diseases, despite providing high-quality, evidence-based care. 
• The measure developer did not report any performance scores for this new measure. Therefore, we request performance data, including the identification of whether there is a performance gap.  
• Additional assessment of empiric validity or face validity in a sample more representative of the CMS program population could strengthen the scientific acceptability of this measure.
• As currently specified, this measure does not meet reliability thresholds. In fact, the developer did not even perform reliability testing. 
• As currently specified, this measure does not have external validity. It was not tested in populations generalizable to the proposed CMS program population. 
• There seems to be a lack of evidence of possible interventions or process improvements to improve performance of the measure. 
• Although provider workflows may not need to be modified, practice workflows likely will. Implementation of a new questionnaire is often expensive and resource intensive. 
  • The developer did not comment on the fact that PROMIS measures are copyrighted. It is often very difficult to get an adequate number of responses to achieve statistical significance. Working to increase response rates is often resource intensive. 
• There was no evaluation of empiric validity, which is important for minimizing potential bias and overall credibility and trustworthiness. 
• As currently specified, the measure does not risk adjust. We encourage re-specification that considers risk adjustment for factors such as comorbidities, cognitive impairments, trauma exposure, resource utilization, duration of neurological disease, polypharmacy, physical function, use of an interpreter, etc. 
• The measure, as currently written, has no external validity.
• Appropriateness of scale: This measure could have a very different impact in different populations. Consider patients that speak different languages and/or have different cultural interpretations of quality-of-life questions. It may also lead to different performance rates in populations with unique social barriers to care.

Can Patient-Reported Outcome Measures Improve Clinical Management and Patient Care? | AAFP

34. National Academies of Sciences, Engineering and Medicine (NASEM). Implementing High-Quality Primary Care: Rebuilding the Foundation of Health care. 2021. Accessed November 9, 2023. https://nap.nationalacademies.org/catalog/25983/implementing-high-quality-primary-care-rebuilding-the-foundation-of-health

The American Academy of Family Physicians (AAFP) appreciates the intent of this measure. As stated in our position paper, “Mental and Behavioral Health Care Services by Family Physicians,” screening for depression is integral to ensuring appropriate treatment (follow-up care) and reducing complications. We understand that measurement is one way to push toward health plan and system improvement. However, we do not support the addition of this measure for use in the CMS Medicare Advantage Star Rating Program. We would like to note the following concerns:  

• Most health plans do not provide clinical care. They do not serve as the actual care provider for patients. Thus, a process measure like this that is specific to care delivery should not be used for health plans. 
  • It may encourage health plans to reach out to patients and try to screen them for depression without involving the patient’s primary care physician (PCP) or other usual source of care. This further fragments care and may lead to unnecessary duplication of services and confusion and frustration for patients, among other unintended consequences. 
• For physicians and other clinicians, this measure adds administrative burden. Some electronic health records (EHRs) do not have standardized depression screening tools automatically built into their baseline product.  The screening may therefore need to be a paper-based workflow (i.e. not generate discrete reportable data elements) and/or require resource-intensive IT/HER build and a change in workflows to gather the information. 
• Follow-up after a positive screen is not always documented discretely in EHR data fields, and thus a clinic would have to build a special field in their EHR system to accommodate that. 
• There is risk to unfairly penalize health plans and therefore clinicians who are adequately treating depression and providing high-quality care but are not generating a discrete data element to receive “credit.”
• There is already a depression screening and follow-up measure available in MIPS (Quality ID 134) for clinicians and groups.
• The measure is not endorsed, and it is not an eCQM.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

While we recognize the importance of working to improve affordability and efficiency, as well as the statutory requirement for cost measurement, the proposed cost measures for the MIPS program continue to concern the AAFP as they are currently designed. Before this or any other cost measure is implemented, we believe they should go through a rigorous endorsement process and further testing and refinement. Given the continuous and comprehensive nature of care delivered by family physicians, the AAFP does not believe that episode-based measurement adds value or improves patient outcomes in a primary care context. 

We continue to reiterate concerns previously communicated to CMS by the AAFP, as well as many other physician specialty societies. Those include but are not limited to the following: 

• The current and proposed episode-based cost measures make the unfounded assumption that lower cost is commensurate with higher quality.  While in some cases that may be true, the support for this argument is superficial and among other things, does not account for patient preferences, case mix, and other significant factors that are beyond the measured clinician’s control.
• They lack transparency. The inability of clinicians to improve their performance on cost-related measures because of the lack of visibility into the cost of care outside their direct care setting, as well as many cost-related factors fall outside their sphere of control.
  • The lack of interoperability and transparency across care settings makes these measures difficult for clinicians to impact. Eligible clinicians have no way of knowing how they are performing throughout the performance period, and that hinders their ability to maximize their performance. 
  • Therefore, these measures do not lend themselves to improvement.  
• Risk adjustment methodologies that do not fully recognize the social and economic context of the patient are insufficient to reflect the variance in cost that can result.
• Evidence-based cost measures (EBCMs) are likely to consider the impact of specific condition-related costs at least twice (and sometimes more) in multiple EBCMs. We are concerned this may have a bigger impact on primary care. Given the breadth of care provided by primary care physicians, they are likely to be attributed multiple episode-based cost measures.

Concerns specific to this proposed measure include but are not limited to the following: 

• This measure lumps many different etiologies into one measure, which creates substantial room for variation. There is significant doubt that the measure specifications can adequately control for case mix and differences in denominator populations.
• Clinical documentation and diagnosis and coding of ulcers is inconsistent.
  • There may be unspecified or inaccurate diagnoses, which may not be discretely linked to USCDI elements. 
• It is stated that imaging is often a driver for increased costs. MRIs or other imaging modalities are often necessary to rule out osteomyelitis in a wound.  This can drive up costs but are often necessary for correct diagnosis and treatment which lead to better outcomes. 
• The Preliminary Assessment states that, “for this ratio measure, a lower score indicates better quality of care.” We highly disagree with this. A lower score simply indicates lower costs. Lower costs may actually be associated with lower quality of care. Higher costs are sometimes correlated with higher quality of care. The two are not the same. 
• The developer did not assess alignment with United States Core Data for Interoperability (USCDI)/USCDI+ quality guidelines. Aligning with USCDI standards for data elements can promote interoperability and improve feasibility. 
• This measure adjusts for dual-eligibility. However, Medicaid coverage and therefore dual-eligibility status varies by state which could affect risk adjustment.  Many patients have high social needs, but do not qualify for Medicaid, especially in states that have not expanded Medicaid. 
• Major costs include costs of drugs and even hyperbaric oxygen treatment. Clinicians cannot control the costs of drugs. Some expensive drugs and treatments can produce excellent clinical outcomes, but costs increase. 
• Reliability: The Preliminary Assessment states that “…20% of [measured] entities have a higher risk of misclassification,” which is concerning.
• Usability: Six weeks of field testing may not be sufficient to assume generalizability. 
• This measure needs further testing, as well as an analysis of time-to-value realization.  Improved performance (i.e. lower costs) does not equal better patient outcomes in many cases. We are concerned that efforts to reduce costs could lead to poorer outcomes for patients.   

One possible solution could be a slow, phased implementation of this cost measure. This could entail pay-for-reporting at the outset (or perhaps a zero percent weight) for a few years until the measure has been more thoroughly tested, the specifications have been further refined, and the measure as gained endorsement from a CBE.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

While we recognize the importance of working to improve affordability and efficiency, as well as the statutory requirement for cost measurement, the proposed cost measures for the MIPS program continue to concern the AAFP as they are currently designed. Before this or any other cost measure is implemented, we believe they should go through a rigorous endorsement process and further testing and refinement. Given the continuous and comprehensive nature of care delivered by family physicians, the AAFP does not believe that episode-based measurement adds value or improves patient outcomes in a primary care context. 

We continue to reiterate concerns previously communicated to CMS by the AAFP, as well as many other physician specialty societies. Those include but are not limited to the following: 

• The current and proposed episode-based cost measures make the unfounded assumption that lower cost is commensurate with higher quality.  While in some cases that may be true, the support for this argument is superficial and among other things, does not account for patient preferences, case mix, and other significant factors that are beyond the measured clinician’s control.
• They lack transparency. The inability of clinicians to improve their performance on cost-related measures because of the lack of visibility into the cost of care outside their direct care setting, as well as many cost-related factors fall outside their sphere of control.
  • The lack of interoperability and transparency across care settings makes these measures difficult for clinicians to impact. Eligible clinicians have no way of knowing how they are performing throughout the performance period, and that hinders their ability to maximize their performance. 
  • Therefore, these measures do not lend themselves to improvement.  
• Risk adjustment methodologies that do not fully recognize the social and economic context of the patient are insufficient to reflect the variance in cost that can result.
• Evidence-based cost measures (EBCMs) are likely to consider the impact of specific condition-related costs at least twice (and sometimes more) in multiple EBCMs. We are concerned this may have a bigger impact on primary care. Given the breadth of care provided by primary care physicians, they are likely to be attributed multiple episode-based cost measures.

Concerns specific to this proposed measure include but are not limited to the following: 

• The lumping of conditions that are uniformly fatal (ALS) with those that are much more variable (MS) adds substantial room for variation. There is significant doubt that the measure specifications can adequately control for case mix and differences in denominator populations. 
  • Consider a primary care physician that has 20 patients that fall into this measure. Of those, 4 have ALS. A comparator physician also has 20 patients that fall into this measure, but zero of them have ALS. There is no clear assessment of value. 
• The developer did not assess alignment with United States Core Data for Interoperability (USCDI)/USCDI+ quality guidelines. Aligning with USCDI standards for data elements can promote interoperability and improve feasibility. 
• This measure adjusts for dual-eligibility. However, Medicaid coverage and therefore dual-eligibility status varies by state which could affect risk adjustment. Many patients have high social needs, but do not qualify for Medicaid, especially in states that have not expanded Medicaid. 
• Reliability is low compared to other measures. In testing, only 50% of TINS had a reliability of >0.6. 
• Usability: Six weeks of field testing may not be sufficient to assume generalizability. 
• The Preliminary Assessment states that referral to PT/OT/speech/language has been shown to increase costs. Some communities may not have those supports either in-office or home provided services. Therefore, patients may not have those services and therefore have lower costs. However, PT/OT/speech language therapy can significantly improve quality of life, length of independence and decrease falls. This is quality improvement, but it can also increase costs. 

One possible solution could be a slow, phased implementation of this cost measure. This could entail pay-for-reporting at the outset (or perhaps a zero percent weight) for a few years until the measure has been more thoroughly tested, the specifications have been further refined, and the measure as gained endorsement from a CBE.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

The AAFP appreciates the intent of this measure. We acknowledge the developer’s time and effort to thoughtfully create a measure that is directly implemented as an eCQM, thereby reducing physician and health system burden to implement.  We also appreciate the inclusion of natural language processing (NLP) and discrete data elements. However, we do not support the addition of this measure for use in MIPS as it is currently specified. We would like to note the following concerns:  

• The Preliminary Assessment does not adequately present discussion on incidence of DVT presentation in primary care.  It states, “The lack of a standard definition of venous thromboembolism (VTE), as well as the low performance of existing identification algorithms, points to a need for the novel, data-driven DOVE electronic clinical quality measure (eCQM).” Yet, they propose to measure primary care clinicians’ quality on a diagnosis which does not have a standard definition and is often preceded by contact across the health care system (Urgent Care, ED, surgeons, orthopedics, oncology, etc.).  Even if these entities could be adequately excluded in the measures, the number of cases which are actually “owned” by the primary care physician and adequately measured likely approach zero to one per year. 
• Therefore, this measure should be specified for use with clinicians beyond just primary care. Given the primary care physician shortage, the plethora of patient entry points into the health care system, as well as the goals of the measure to decrease delayed DVT diagnosis and treatment, this measure should be applied more broadly. It should also include urgent care. 
• As currently specified, this measure could unfairly penalize primary care physicians who do not have immediate access (<24 hours) to ultrasound diagnostics.
• As stated in the Preliminary Assessment, a “measure to quantify delayed diagnosis of VTE within a CMS payment program may motivate primary care clinicians to overuse VTE diagnostic resources to avoid a high DOVE rate.” We agree. This measure could lead to an increase in unnecessary ED visits. 
• We question the lack of risk stratification. 
• Reliability is below the acceptable threshold for roughly 60% of measured entities in testing. 
• The inclusion of “cough” and other vague symptoms seems too broad.  Often primary care physicians are squeezing patients in for brief acute visits, overbooking at times, because it’s the right thing to do for the patient.  A cough, especially during respiratory season, does not always prompt a long line of questioning related to DVT. 
• Many health systems have limited or zero implementation of natural language processing (NLP) tools that would be required to support this metric as an eCQM today.  Implementation of this could increase costs and resources required to build out these tools.
• During the recent listening session, the developer mentioned several times that they do not intend for this measure to be used to penalize primary care physicians. However, the MIPS program ties performance to payment and thus penalties are possible.
• A better way to realize the overall goals of this measure would be to develop and widely disseminate easy-to-use tools to assist primary care and other physicians in clinical decision support so they do not miss the diagnosis rather than implement a performance measure with possible penalties. 
• There currently is not enough data on near- and long-term effects of this metric.  It has the potential to increase costs if physicians practice defensive medicine in order to not miss one case of VTE within 24 hours in patients who present with a wide variety of symptoms including cough and any lower extremity pain vs. practicing evidence-based medicine and ordering appropriate tests as indicated.
• This measure could be a good quality improvement measure for internal quality improvement purposes ONLY within a medical clinic. As proposed, we do not support the implementation of this measure in MIPS or any other value-based payment program where payment is tied to performance. 

I appreciate the opportunity to provide a public comment in support of adopting the MUC2024-028 Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes (Screening).

Screening for prediabetes and undiagnosed type 2 diabetes is critical to improving both prevention and care of type 2 diabetes. The Centers for Disease Control and Prevention (CDC) estimates that approximately 97.6 million American adults have prediabetes.¹ They note that more than 80% of adults with prediabetes are not aware that they have the condition. Additionally, the CDC estimates 38.4 million adults have diabetes with 8.7 million being undiagnosed.¹ The prevalence of prediabetes and diabetes also increases with age.¹ Early identification of both prediabetes and type 2 diabetes is crucial so that patients can receive effective interventions to decrease the likelihood of disease progression or complications. 

The Screening measure is based on the United States Preventive Services Task Force (USPSTF) 2021 Prediabetes and Type 2 Diabetes: Screening recommendation.² “The USPSTF recommends screening for prediabetes and type 2 diabetes in adults aged 35 to 70 years who have overweight or obesity.”²

Furthermore, this measure would address a recommendation from the National Clinical Care Commission (NCCC) to Congress and the Secretary of Health and Human Services (HHS), which called for adopting the Screening measure developed by the American Medical Association as part of a strategy to prevent diabetes among high-risk individuals.³

Based on the above recommendations, this measure would be recognized by physicians as clinically appropriate and meaningful for improved patient care. The measure targets an appropriate patient population that would clearly benefit from glucose screening. We believe the measure specifications are feasible to implement by most health care organizations; most organizations routinely capture the data elements in their EHR. Additionally, this measure is both valid and reliable as demonstrated in the testing results. 

Screening for abnormal glucose is an important preventive service and is reasonable to include in accountability programs. 

References:

¹CDC. (2024, July 23). National Diabetes Statistics Report. Retrieved November 15, 2024, from Diabetes website: https://www.cdc.gov/diabetes/php/data-research/ 

²US Preventive Services Task Force. (2021). Screening for Prediabetes and Type 2 Diabetes: US Preventive Services Task Force Recommendation Statement. JAMA, 326(8), 736–743. https://doi.org/10.1001/jama.2021.12531

³Report to Congress on Leveraging Federal Programs to Prevent and Control Diabetes and Its Complications. National Clinical Care Commission, 2021, https://health.gov/about-odphp/committees-workgroups/national-clinical-care-commission/report-congress.

I support this measure. Screening for abnormal glucose metabolism would help with patients getting timely management to avoid progression to T2DM and be engaged in preventive behaviors to attenuate their risk. 

We appreciate the impact of social determinants of health on a person’s health outcomes and agree screening for social risk factors is an important first step in promoting health equity and eliminating health disparities. While we recognize the importance of promoting health equity, we urge CMS to implement this measure carefully and over a longer time period to ensure that resources to support equity initiatives are used in a way that improves patient outcomes, safeguards against the healthcare system accidentally eroding trust with consumers, and is feasible for health plans to meet. Given the current data availability and feasibility challenges with implementing this measure, PRMR should not recommend its inclusion at MA Star Ratings at this time. 

While AHIP agrees with the goal of moving to digital measurement, our members continue to find challenges implementing electronic clinical data systems (ECDS) measures and significant barriers to ECDS implementation remain. Many plans do not have the infrastructure or resources needed to successfully report electronic data. Interoperability between plans and providers continues to be a significant hindrance. Some providers still lack EHR technology and CMS risks missing key data from individual providers and small group practices with minimal or no EHR use by using measures specified for this reporting method only. Furthermore, plans have expressed difficulty getting provider buy-in on ECDS measure reporting. Clinicians who are meaningfully using EHRs may be reluctant or unwilling to share information contained in those records with health issuers. Given the particularly sensitive nature of the data underlying this measure, we are concerned that clinicians may be reluctant to share this information electronically. 

Compounding the challenges with ECDS is the requirement to use LOINC codes to confirm the use of specific screening instruments. This information is generally not included in the EHR and is not available not in claims data. Moreover, clinicians may not be familiar with these codes or have them readily available in their EHR system.

CMS should delay adoption of this measure while the agency works with NCQA to address the ongoing challenges with implementing ECDS reporting and the number of measures transitioning to ECDS reporting. Concerns with ECDS reporting such as lack of interoperability and other challenges impacting data collection should also be addressed prior to consideration of possible QRS measures that would be reported using the ECDS reporting method.

PRMR should recommend that if CMS does adopt this measure that it take a phased-in approach as this measure has only been recently adopted for HEDIS reporting and plans are still working to address reporting challenges. A phased-in approach would allow CMS to work with issuers to confirm this measure can be successfully implemented across various types of health plans, regions, and populations. Such an approach would also allow the community-based organizations (CBOs) who provide services to address social needs an opportunity to grow their infrastructure and ability to exchange data with issuers.

CMS should work with plans to provide guidance on the types of interventions that could apply to this measure and best practices for implementation. These strategies could help CMS and plans better understand how the measure performs, how to successfully connect members with needed resources, ways to effectively partner and share data with healthcare providers, and if there are unintended negative consequences to the measure such as overburdening CBOs or frustrating and eroding trust with consumers. 

We ask PRMR to ensure this measure can be implemented consistently and allows fair comparisons across plans and regions. We are concerned that plans may have different existing capabilities to do this work, and that social needs and the availability of resources may differ by region. Plans may not be able to control the full spectrum of available interventions. Many social services may be provided by government agencies or community-based organizations. In these instances, the availability of interventions may be limited by demand and resource capacity. Additionally, we are concerned that certain services or interventions may not be available in all geographic areas of the country. We note this measure will be particularly challenging for plans operating in rural or frontier areas. We are also concerned that some of the indicators may have small denominators, leading to potentially inaccurate or biased results. 

Recommendations: 

• Delay adoption of the SNS-E measure for QRS until CMS and NCQA can resolve the current issues with documenting, coding, and reporting the data required to calculate this measure. 
• Recommend that is CMS does adopt this measure, it us a phased-in approach to allow plans issuers, providers, and CBOs an opportunity to address challenges with ECDS reporting and build capacity.
• Ensure the measure can be implemented consistently and allows fair comparisons given the potential impacts of variation in the availability of CBOs and the influence of small numbers.  

While AHIP is committed to promoting compliance with all Advisory Committee on Immunization Practices (ACIP) recommendations and improving the number of individuals up to date on recommended vaccinations, we do not believe the AIS-E measures should be added to MA Star Ratings at this time due to ongoing feasibility issues with the measure. First, plans continue to experience challenges accessing immunization registries in all states, and in some cases cannot access them at all. CMS and NCQA work with plans and states to facilitate registry access in all states prior to using this measure in Star Ratings. While efforts such as the Trusted Exchange Framework and Common Agreement (TEFCA) could facilitate gathering the data necessary to report this measure, the health plan and public health agency use cases are not yet fully implemented resulting in no and low participation respectively. In addition, responses to queries under the HEDIS exchange purpose will not be required until March 2026 and fees can be charged to access the data. Moreover, plans continue to report challenges with ECDS reporting, including provider willingness to share data in this way. Additional unresolved challenges with ECDS reporting include a lack of standards for exchange, limits to technologies such as natural language processing to extract unstructured data, limited provider use of necessary codes, no mapping to standard codes, and a lack of interoperability between plan and provider systems. We are concerned at the pace at which CMS is transitioning to ECDS measures and strongly recommend NCQA resolve these issues before adding additional ECDS measures to Star Ratings. We also recommend that CMS work with NCQA to publish results validating ECDS measures against the traditional reporting methods so plans can understand how the versions of the measures perform in relationship to each other.

We also continue to be concerned that the use of a single rate assessing members who are compliant for all indicators could create unfair penalties for health plans. A single all or nothing rate could miss important regional and/or cultural variation in vaccine acceptance. Moreover, an increase in vaccine hesitancy has presented numerous challenges to ensuring compliance with vaccines as scheduled as patients may choose to delay vaccines. AHIP believes the use of a single combination rate could necessitate the addition of exclusion criteria to account for patient choice.

J&J supports this measure’s inclusion in MIPS and would encourage CMS to consider expanding this measure to be included in other key CMS payment programs such as EOM, IQR, OQR, PCHQR, MSSP, ACO REACH, AHEAD. Person-Centered Outcome (PCO) measures work in tandem with clinical care to help people living with complex health needs make progress toward a person-centered outcome goal that matters to them. Clinicians throughout the care continuum and community-based services can use this approach to identify what is important to a person.[1]

[1] National Committee for Quality Assurance (NCQA). https://www.ncqa.org/hedis/reports-and-research/pco-measures/

J&J supports inclusion of this measure in the IQR, HAC and MPIP. Bleeding events caused by anticoagulation medications are common and preventable. This measure will help ensure appropriate use of anticoagulation medications and provider choice of safer anticoagulants.  In general, Direct Oral Anticoagulants (DOACs) are safer and more effective than warfarin, especially when it comes to serious bleeding. DOACs cause half as much life-threatening bleeding than warfarin. They’re also more convenient than warfarin because they do not require frequent blood monitoring and can be given safely in fixed doses.[1]

DOACs are widely used to treat a variety of cardiovascular conditions, including atrial fibrillation (Afib), coronary arterial disease (CAD), venous thromboembolism (VTE), peripheral artery disease (PAD) and stroke prevention. Cardiovascular disease (CVD), including heart disease, stroke and other cardiovascular diseases are the number one cause of death in the United States, accounting for nearly one million deaths (928,741) in 2020 and 128 million US Adults had some form of CVD between 2017 and 2020, accounting for more than $400 Billion in direct ($251.4B) and indirect ($155.9B—lost productivity and mortality) costs.[2] CVD accounted for 12% of total US Health expenditures in 2018 to 2019. This is more than any major diagnostic group.⁴ Black Americans had the highest prevalence of CVD, with 59% of Black men and women having some form of CVD in 2020. ⁴

In 2019, the American Heart Association/American College of Cardiology/Heart Rhythm Society (AHA/ACC/HRS) updated their afib guidelines to strongly recommend using DOACs over warfarin in people with Afib.[3] 

[1] North American Thrombosis Forum. https://thrombosis.org/2020/11/doacs-vs-warfarin/#:~:text=In%20general%2C%20the%20DOACs%20are,given%20safely%20in%20fixed%20doses./ Accessed January 31, 2023. 

[2] American Heart Association. 2023 Statistics At-A-Glance. https://professional.heart.org/-/media/PHD-Files-2/Science-News/2/2023-Heart-and-Stroke-Stat-Update/2023-Statistics-At-A-Glance-final_1_17_23.pdf. Accessed, February 2, 2023. 

[3] https://ahajournals.org/doi/full/10.1161/CIR.0000000000000665

J&J supports CMS’ inclusion of NCQA’s “Depression Screening and Follow-Up for Adolescents and Adults” in the Part C & D Star Ratings program. The inclusion of this measure would close the significant gap in behavioral health outcome measures and address a critical outcome for patients with depression. This measure is well established and has been in the HEDIS program since 2017, and is currently reported for the Medicare, Medicaid, and commercial product lines. Performance on the measure for Medicare enrollees has considerable potential for improvement, including mean performance scores on the remission indicator of under 10%.^[1]

[1] https://www.ncqa.org/wp-content/uploads/Special-Report-Nov-2024-Results-for-Measures-Leveraging-Electronic-Clinical-Data-for-HEDIS.pdf

AHIP appreciates the importance of improving behavioral healthcare and the value of routine screenings for depression. However, we are concerned about the feasibility of implementing this measure in MA Star Ratings at this time and do not believe PRMR should recommend its adoption due to ongoing issues with data availability and measure feasibility. 

This measure is specified to use ECDS reporting and as discussed above, plans have faced numerous challenges implementing ECDS reporting. These challenges could be exacerbated with this measure as behavioral health, small practices, and community organizations were not included in the Meaningful Use incentive program (HITECH Act) and now lag in adoption certified EHR technology. Additionally, behavioral health providers may be particularly reluctant to share electronical clinical data given the potential legal and regulatory barriers, whether real or perceived. Some providers are unsure of the security of electronic data exchange and remain reluctant to adopt it and believe paper or fax methods are more secure and less likely to compromise a person’s privacy. However, a measure that requires ECDS reporting would not support results from providers that do not use EHRs or are unwilling to exchange data electronically.

Compounding the challenges with ECDS is the requirement to use LOINC codes to confirm the use of specific screening instruments. This information is generally not included in the EHR and is not available not in claims data. Moreover, clinicians may not be familiar with these codes or have them readily available in their EHR system.

Additionally, there may be legal or regulatory barriers to sharing behavioral health data. We urge CMS to review federal, state, and territory laws and regulations that may impact the ability to provide complete information for beneficiaries. Current laws and regulations addressing patient privacy may impact the exchange of information about mental health screening and the ability to encourage follow-up care. 

Data availability can also be impacted by the setting where patients receive care. Patients may receive care in community health centers or receive mental health benefits through a behavioral health vendor. In these cases, plans will not have the ability to identify the relevant patients because of the carve-out issue. CMS could consider making changes to the measure denominator to address eligibility issues.

Recommendations: 

• Do not adopt the DSF-E measure for Star Ratings until CMS and NCQA can resolve the current issues with documenting, coding, and reporting the data required to calculate this measure.

Johnson & Johnson strongly urges CMS to consider inclusion of additional depression and schizophrenia quality measures in the Part C & D Star Ratings program. Behavioral health conditions, including schizophrenia and major depressive disorder, are prevalent among Medicare beneficiaries and account for disproportionate healthcare resource utilization.   Research has indicated that the number of people over 55 years living with schizophrenia are expected to double to 1.1 million by 2025.[1]   Major depressive disorder is a serious and debilitating illness and is the second leading cause of disability worldwide.  Moreover, 16% of people in the U.S. report that they have been told by a healthcare professional that they had depression at some point in their lives. In a study of excess direct health care costs of schizophrenia, mean total health care costs were higher for Medicare-insured patients.[2] Research has further shown that nearly 13% of Medicare spending is associated with mental health disorders, emphasizing the urgent need to measure and improve the quality of care delivered to patients with serious mental illness.[3] 

Depression

Given the importance of depression screening and management to the overall achievement of outcomes for at-risk patients, J&J further recommends consideration and adoption of NCQA’s “Depression Remission or Response for Adolescents and Adults” in the Part C & D Star Ratings program. This would close the significant gap in behavioral health outcome measures and address a critical outcome for patients with depression. This measure is well established and has been in the HEDIS program since 2017, and is currently reported in the Medicare, Medicaid, and commercial product lines. Performance on the measure for Medicare enrollees has considerable potential for improvement, including mean performance scores on the remission indicator of under 10%.[4]

Schizophrenia

We further advocate in support of future consideration and inclusion of NCQA’s “Adherence to Antipsychotic Medications for Individuals with Schizophrenia” quality measure in the Part C & D Star Ratings program.

This measure addresses a critical quality gap for at-risk patients with a prevalent serious mental illness diagnosis. In its rationale for the measure, NCQA states that “for people with schizophrenia, nonadherence to treatment with antipsychotics is common, and medication nonadherence is a significant cause of relapse. Measuring antipsychotic medication adherence may lead to less relapse and fewer hospitalizations. Additionally, there is potential to lead to interventions to improve adherence and help close the gap in care between people with schizophrenia and the general population.”[5]^,[6] 

Notably, one systematic review found that 49% of major psychiatric disorder patients were non-adherent to their psychotropic medication, with schizophrenia patients reaching non-adherence rates of 56%.[7] A separate study concluded that patient adherence information for atypical antipsychotic medications can help predict patient adherence to other serious mental illness, anti-diabetes, and antihypertension medications, and that having access to adherence information can improve treatment choices and cost savings. An additional study found adherence to antipsychotics was bivariately associated with fewer relapses, and the healthcare resource use and costs consistently increased with relapse frequency.[8]

The “Adherence to Antipsychotic Medications for Individuals with Schizophrenia” measure has been required as part of the NCQA health plan accreditation (HPA)/Health Plan Ratings (HPR) measure list for the Medicaid product line since at least 2018.[9] In 2022, NCQA added the measure to the health plan accreditation/Health Plan Ratings required measure list for both the commercial and Medicare product lines after validating the feasibility of reporting the measure in the Medicare population.[10]^,[11] 

As stated by NCQA: “There was concern that a small percentage of Medicare (34%) plans were able to report the measure in the testing sample because many were disqualified because of low denominator sizes. However, historical HEDIS data has shown that plans with low denominators resulting from an enrollment of less than 7,000 members (42%) represent only up to 4% of all members for whom Medicare plans report HEDIS measures. On the flip side, Medicare plans are likely to have sufficient denominators (58%) represent 96% of all members for whom Medicare plans report HEDIS measures.”[12] In addition, performance on the measure for Medicare enrollees has potential for improvement, including mean performance scores of under 80%.[13]

Importantly, in the CMS 2020 Advance Notice for the Medicare Advantage program, CMS explored the possibility of including the SAA measure on the Part C & D Program Display Page after NCQA validated the measure for its Medicare product line.[14] We encourage CMS to move forward with including this measure in the Part C & D Star Ratings program to improve care for members with schizophrenia.

[1] Cohen Vahia I, Reyes P, Diwan S, Bankole A, Palekar N, & Ramirez PC, 2008. ‘Schizophrenia in later life: clinical symptoms and social well-being’, Journal of Psychiatric Services, pp. 232–234.

[2] https://www.psychiatrist.com/jcp/economic-burden-schizophrenia-united-states/

[3] Figaroa, Jose et. al., Association of Mental Health Disorders With Health Care Spending in the Medicare Population, JAMA Network, Mar 2020

[4] https://www.ncqa.org/wp-content/uploads/Special-Report-Nov-2024-Results-for-Measures-Leveraging-Electronic-Clinical-Data-for-HEDIS.pdf

[5] Olfson, M., S. Hansell, C.A. Boyer. Medication noncompliance. New Dir Ment Health Serv 73:39–49. HEDIS MY 2022 Vol 1, 1997.

[6] Ascher-Svanum, H., B. Zhu, D.E. Faries, D. Salkever, E.P. Slade, X. Peng, et al. 2010. “The Cost of Relapse and the Predictors of Relapse in the Treatment of Schizophrenia.” BMC Psychiatry 10:2

[7] At:  https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-020-1274-3 and https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534179/

[8] https://www.nature.com/articles/s41537-024-00509-6

[9] https://www.ncqa.org/wp-content/uploads/2018/09/201808013_Health_Plan_Ratings_Methodology.pdf

[10] https://www.ncqa.org/wp-content/uploads/2022/04/2023-HPR-List-of-Required-Performance-Measures_4.25.2022.pd 

[11] https://www.ncqa.org/wp-content/uploads/2022/01/2022-HPR-List-of-Required-Performance-Measures_Updated-1.26.2022.pdf

[12] https://www.ncqa.org/wp-content/uploads/2019/02/20190208_09_SAA.pdf

[13] https://www.ncqa.org/hedis/measures/adherence-to-antipsychotic-medications-for-individuals-with-schizophrenia/

[14] https://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/Downloads/Advance2020Part2.pdf 

December 23, 2024

RE MUC2024-073: Patient Understanding of Key Information Related to Recovery After a Facility-Based Outpatient Procedure or Surgery, Patient Reported Outcome-Based Performance Measure (Information Transfer PRO-PM)

The ASC Quality Collaboration - a non-profit organization representing more than 2,200 ambulatory surgery centers (ASCs) dedicated to advancing high quality, patient-centered care - has several concerns regarding the Information Transfer PRO-PM. 

The measure developer has not presented any evidence supporting the importance and meaningfulness of implementing this measure in the ASC setting.  The literature review submitted includes studies drawn exclusively from the hospital inpatient and hospital emergency department settings. The developer acknowledges that “[n]one of the studies included individuals who underwent an outpatient procedure or surgery”. It is not appropriate to submit a measure for consideration for the ASC Quality Reporting Program without setting-specific evidence to support its adoption. 

Further, the measure has never been tested in the ASC setting to establish key measure characteristics such as reliability and feasibility. All testing for the measure was performed in hospitals, yet ASCs are not comparable to hospitals. There are significant differences in organizational size, operational infrastructure, administrative and support personnel, data collection and analysis capabilities, and availability of technological tools. ASCs are small facilities (median of two operating/procedure rooms), with few employees (median of 21 to 22 FTEs).

We are also concerned regarding the lack of alignment with the survey protocols for the Outpatient and Ambulatory Surgery (OAS) CAHPS Survey, which also touches on the topic of discharge instructions. The OAS CAHPS survey measures will become mandatory for the ASC Quality Reporting Program in 2025. As currently specified, the survey questions for the Information Transfer PRO-PM would have to be fielded separately because the administration timeframe and survey modes for this measure are not the same as those for the OAS CAHPS. CMS and the measure developer, who already have ties to the CAHPS Consortium, should add the survey questions for the Information Transfer PRO-PM to the existing OAS CAHPS survey. In addition, all aspects of survey protocols and administration guidelines should be standardized across survey-based measures so that ASCs do not have to administer a second survey solely to address discharge information. We believe this would be a win-win situation: the necessary information could still be obtained, yet with significantly less burden to ASCs.

Respectfully, 

Becky Ziegler-Otis, Assistant Executive Director - ASC Quality Collaboration

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

While we recognize the importance of working to improve affordability and efficiency, as well as the statutory requirement for cost measurement, the proposed cost measures for the MIPS program continue to concern the AAFP as they are currently designed. Before this or any other cost measure is implemented, we believe they should go through a rigorous endorsement process and further testing and refinement. Given the continuous and comprehensive nature of care delivered by family physicians, the AAFP does not believe that episode-based measurement adds value or improves patient outcomes in a primary care context. 

We continue to reiterate concerns previously communicated to CMS by the AAFP, as well as many other physician specialty societies. Those include but are not limited to the following: 

• The current and proposed episode-based cost measures make the unfounded assumption that lower cost is commensurate with higher quality.  While in some cases that may be true, the support for this argument is superficial and among other things, does not account for patient preferences, case mix, and other significant factors that are beyond the measured clinician’s control.
• They lack transparency. The inability of clinicians to improve their performance on cost-related measures because of the lack of visibility into the cost of care outside their direct care setting, as well as many cost-related factors fall outside their sphere of control.
  • The lack of interoperability and transparency across care settings makes these measures difficult for clinicians to impact. Eligible clinicians have no way of knowing how they are performing throughout the performance period, and that hinders their ability to maximize their performance. 
  • Therefore, these measures do not lend themselves to improvement.  
• Risk adjustment methodologies that do not fully recognize the social and economic context of the patient are insufficient to reflect the variance in cost that can result.
• Evidence-based cost measures (EBCMs) are likely to consider the impact of specific condition-related costs at least twice (and sometimes more) in multiple EBCMs. We are concerned this may have a bigger impact on primary care. Given the breadth of care provided by primary care physicians, they are likely to be attributed multiple episode-based cost measures.

Concerns specific to this proposed measure include but are not limited to the following: 

• We support the intent of incentivizing early detection.  But of all of the cost drivers in US healthcare, we do not think breast cancer screening is the thing to go after. 
• Cost measures should not target preventive care and screenings. Based on the information provided, it sounds like this measure could penalize primary care physicians for increasing breast cancer screenings.
• In the Preliminary Assessment, there was no clear explanation of whether primary care physicians will be held accountable for this measure (in addition to radiologists). Additionally, we urge the developers to explain how a radiologist and/or other attributed physician can control costs for radiology procedures and/or cancer treatments.
• It does not appear there are any exclusions and/or adjustments of/for patients with high-risk status (family history, dense breasts, patients needing MRI, etc.) Additionally, it does not appear there is risk adjustment for anything directly or indirectly related to social needs.
• The Preliminary Assessment states that, “for this continuous variable measure, a lower score indicates better quality of care.” We highly disagree with this. A lower score simply indicates lower costs. Lower costs may actually be associated with lower quality of care. Higher costs are sometimes correlated with higher quality of care. The two are not the same. 
  • Improved performance (i.e. lower costs) does not equal better patient outcomes in many cases. We are concerned that efforts to reduce costs could lead to poorer outcomes for patients.    
• Threats to validity: Clinicians who care for patients with barriers to breast cancer screening and going to follow up appointments could be negatively impacted. If a patient is late to screening, they could have a more advanced presentation upon actually getting the screening done.  Then if they have barriers to getting diagnostic imaging and/or biopsies done (i.e. takes longer than 8 months which is very much a reality for some patients who face difficulty navigating the health system, transportation barriers, homelessness, lost to follow up, drug use impacting the ability to use anesthesia), then the disease is likely to be more advanced at presentation. 

One possible solution could be a slow, phased implementation of this cost measure. This could entail pay-for-reporting at the outset (or perhaps a zero percent weight) for a few years until the measure has been more thoroughly tested, the specifications have been further refined, and the measure as gained endorsement from a CBE.

See attached file.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

The AAFP supports CMS’ goal of reducing health inequities and believes family physicians, along with others, play an important role in helping to identify and alleviate the health-related social needs of patients. However, we do not support the addition of this measure for use in the CMS Medicare Advantage Star Rating Program. We would like to note the following concerns:  

• As stated in our previous comments about the appropriate application of HEDIS measures, we do not support the implementation of this measure for health plans. 
  • There is another social needs screening and intervention measure on this year’s MUC list that is proposed for use in MIPS and is specified for use at the individual clinician and group level (MUC2024-072).
  • If both the health plan AND the patient’s primary care or other clinician are screening for social needs and trying to provide interventions (when needed), then there is a significant duplication of services. This will likely lead to patient confusion, hesitancy, frustration, and survey fatigue. If further fragments care.
• This measure is not digital, nor is it an eCQM.
• It has not been endorsed by a consensus-based entity (was never even submitted).
• The measure does meet reliability testing requirements. In fact, the developer did not even perform reliability testing.
• The community-based organizations (CBOs) who can help patients alleviate social needs are often overwhelmed and do not have the capacity for a mass influx of referrals. 
• The lack of data sharing and interoperability across the health ecosystem presents a tremendous problem and challenge. 

In addition to the above concerns specific to this proposed measure, we would like to reiterate comments we have previously shared with CMS about proposed performance measures for social needs screening and intervention: 

It is important for family and other primary care physicians to be connected to social and community-based organizations that can help to address patients’ social needs using an efficient, centralized approach. These are core tenants of comprehensive, longitudinal primary care, though we note that these types of services are often not billable under the MPFS. Moving to APMs that include comprehensive prospective payment must be prioritized if we are to sufficiently and sustainably support primary care’s role in improving health equity. Further, physicians and other clinicians cannot be held accountable for providing resources to address individual health-related social needs when those resources do not exist in the community.

The overarching goal should be to drive improved health for historically marginalized and medically underserved populations. Addressing health equity and social drivers of health are community issues that require community solutions. Many communities simply do not have adequate social resources and community-based organizations available to help meet patients’ diverse social needs. Even when those resources exist at the community level, community-based organizations are not typically resourced with the funding, skills, or staff to accept referrals from the health care system. CMS should incentivize the development and use of community care hubs or other payer and provider agnostic centralized referral systems to ease the burden on all parties, including the community-based organizations best equipped to address patients’ social needs

The AAFP is very supportive of screening for health-related social needs and has equipped its members with the tools to engage in this important aspect of whole-person care through the EveryONE Project. As screening patients for unmet health-related social needs is increasingly common for many provider types and at many points of entry for patients into the health care and health insurance systems, there is increased interest in measurement of these efforts. The AAFP agrees with CMS that the insights gained through these screenings provide important patient and community level insights but urges caution when considering measurement of this activity as an indicator of care quality in a single health care setting.

The ultimate goal should be to build the infrastructure and capabilities necessary to share these patient-level insights across provider types in a secure and timely fashion with the patient’s permission to do so, just as is done with clinical information. This will ensure that all of a patient’s caregivers are aware of their unique needs while not overburdening patients or their physicians and other clinicians with unnecessary, repetitive assessment efforts. Overwhelming patients with different screening mechanisms at different points along the health care spectrum could be counter-productive to building trust with patients. It is important to recognize that there are challenges and important considerations to address before new measure requirements are introduced. Most importantly, the measure should address those factors or circumstances within the control of the individuals or organizations being measured. CMS’ measurement strategy should account for these challenges and ensure quality measurement does not negatively impact underserved patients or the clinicians caring for them. 

See attached file.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

The AAFP supports CMS’ goal of reducing health inequities and believes family physicians, along with others, play an important role in helping to identify and alleviate the health-related social needs of patients. However, we do not support the addition of this measure for use in the CMS MIPS Program at this time. We would like to note the following concerns:  

• There is another social needs screening and intervention measure on this year’s MUC list that is proposed for use with health plans in the Medicare Advantage Star Rating Program (MUC2024-052). 
  • If both the health plan AND the patient’s primary care or other clinician are screening for social needs and trying to provide interventions (when needed), then there is a significant duplication of services. This will likely lead to patient confusion, hesitancy, frustration, and survey fatigue. If further fragments care.
• It has not been endorsed by a consensus-based entity (was never even submitted).
• The community-based organizations (CBOs) who can help patients alleviate social needs are often overwhelmed and do not have the capacity for a mass influx of referrals. 
• The lack of data sharing and interoperability across the health ecosystem presents a tremendous problem and challenge. 

In addition to the above concerns specific to this proposed measure, we would like to reiterate comments we have previously shared with CMS about proposed performance measures for social needs screening and intervention: 

It is important for family and other primary care physicians to be connected to social and community-based organizations that can help to address patients’ social needs using an efficient, centralized approach. These are core tenants of comprehensive, longitudinal primary care, though we note that these types of services are often not billable under the MPFS. Moving to APMs that include comprehensive prospective payment must be prioritized if we are to sufficiently and sustainably support primary care’s role in improving health equity. Further, physicians and other clinicians cannot be held accountable for providing resources to address individual health-related social needs when those resources do not exist in the community.

The overarching goal should be to drive improved health for historically marginalized and medically underserved populations. Addressing health equity and social drivers of health are community issues that require community solutions. Many communities simply do not have adequate social resources and community-based organizations available to help meet patients’ diverse social needs. Even when those resources exist at the community level, community-based organizations are not typically resourced with the funding, skills, or staff to accept referrals from the health care system. CMS should incentivize the development and use of community care hubs or other payer and provider agnostic centralized referral systems to ease the burden on all parties, including the community-based organizations best equipped to address patients’ social needs

The AAFP is very supportive of screening for health-related social needs and has equipped its members with the tools to engage in this important aspect of whole-person care through the EveryONE Project. As screening patients for unmet health-related social needs is increasingly common for many provider types and at many points of entry for patients into the health care and health insurance systems, there is increased interest in measurement of these efforts. The AAFP agrees with CMS that the insights gained through these screenings provide important patient and community level insights but urges caution when considering measurement of this activity as an indicator of care quality in a single health care setting.

The ultimate goal should be to build the infrastructure and capabilities necessary to share these patient-level insights across provider types in a secure and timely fashion with the patient’s permission to do so, just as is done with clinical information. This will ensure that all of a patient’s caregivers are aware of their unique needs while not overburdening patients or their physicians and other clinicians with unnecessary, repetitive assessment efforts. Overwhelming patients with different screening mechanisms at different points along the health care spectrum could be counter-productive to building trust with patients. It is important to recognize that there are challenges and important considerations to address before new measure requirements are introduced. Most importantly, the measure should address those factors or circumstances within the control of the individuals or organizations being measured. CMS’ measurement strategy should account for these challenges and ensure quality measurement does not negatively impact underserved patients or the clinicians caring for them. 

Given the gravity of type 2 diabetes, identifying patients with prediabetes and preemptively acting to prevent progression to type 2 diabetes is imperative to promote long-term health and wellbeing. Thus, I support the "Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes" measure. The implementation of this as a quality measure can help ensure that those at the greatest risk for developing type 2 diabetes are administered the necessary screenings to identify prediabetes, and it can decrease the chances of at risk patients slipping through the cracks and developing type 2 diabetes as a result.

American Academy of Family Physicians (AAFP) comments 

Recommendation: Do not support

The American Academy of Family Physicians (AAFP) is a champion of safe and effective vaccines. Vaccination is a vital component of comprehensive primary care, and we support recommendations from the Advisory Committee on Immunization Practices (ACIP). However, the AAFP has repeatedly expressed concerns about the use of this composite measure, particularly as a performance measure where physicians can be held accountable for factors beyond their control. We do not support the addition of this measure for use in the CMS Medicare Advantage Star Rating Program. 

We would like to reiterate comments we have previously shared about the use of the Adult Immunization Status composite measure in MIPS and other payment programs: 

• Measure concept – We support the larger goal of improving vaccination rates, and we appreciate NCQA’s desire to hold health plans accountable for proving vaccination status. However, we believe it is premature to implement this composite measure given numerous challenges (touched upon below).  
• Reporting feasibility – Current immunization registries and health data information sharing systems must first be optimized to more effectively aggregate patient information, including immunization records, to evaluate the quality of the care reliably and accurately. This is particularly true for the influenza vaccine which is frequently received by patients in the community at grocery stores, pharmacies, workplaces, etc. Inadequate data aggregation and information sharing increases the burden of reporting, as physicians and their staff must manually track down and enter information for immunizations received outside of their clinic. Despite their best efforts, there will undoubtedly be data gaps that will inappropriately be identified as care deficiencies under this measure. 
• Administrative burden – Given the reporting feasibility challenges highlighted above, health plans may request data from clinicians’ EHR systems, which could create significant administrative burden on physicians and their clinic teams. 
  • While this effort is grounded in good intentions, the reality is that the burden will fall on primary care physicians and their care teams to track down decades-old pediatric immunizations. 
• Increasing vaccine hesitancy among the American population - Holding a clinician accountable for vaccination rates is troubling given the well-documented vaccine hesitancy throughout the United States. 
• Quality improvement vs. performance measurement - At the provider/clinic-level, this measure can serve as an important internal quality improvement measure, but we do not think that health plans should use it as an accountability measure tied to financial incentives or penalties in value-based contracts with physicians. 

On behalf of the American Podiatric Medical Association (APMA), the premier professional organization representing the vast majority of the nation’s estimated 15,000 doctors of podiatric medicine, also known as podiatrists or podiatric physicians and surgeons, we appreciate the opportunity to provide continued input on the Non-Pressure Ulcers episode-based cost measure currently under development. We’ve provided feedback throughout the measure’s development process, including representation on the Clinician Expert Workgroup. Given our clinical focus, we had hoped our feedback would inform refinements to the measure before it was considered for potential use in the cost performance category of the Merit-based Incentive Payment System (MIPS). However, we do not think that the measure can accurately distinguish between good and poor performance among clinicians in terms of cost efficiency as it is currently specified.

While APMA strongly supports the development of an episode-based cost measure for non-pressure ulcers, we do not support the measure in its current form. Despite having representation on the Clinician Expert Workgroup that developed this measure, we still have questions and concerns about the measure’s construct, and the way feedback about the measure is handled, which are outlined below. As such, we do not support the Non-Pressure Ulcers Episode-Based Cost Measure as is currently specified, and we recommend that it be removed from further consideration until additional testing takes place and the results of such testing are clearly and transparently provided to the Clinician Expert Workgroup for consideration and deliberation.

See attached for APMA's detailed response.

I am writing to express my support for hepatitis C treatment and my concerns regarding this measure. See comments attached.

Dr. Cody Brown appreciates the opportunity to provide a public comment in support of adopting the MUC2024-028 Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes (Screening).

Screening for prediabetes and undiagnosed type 2 diabetes is critical to improving both prevention and care of type 2 diabetes. The Centers for Disease Control and Prevention (CDC) estimates that approximately 97.6 million American adults have prediabetes.¹ They note that more than 80% of adults with prediabetes are not aware that they have the condition. Additionally, the CDC estimates 38.4 million adults have diabetes with 8.7 million being undiagnosed.¹ The prevalence of prediabetes and diabetes also increases with age.¹ Early identification of both prediabetes and type 2 diabetes is crucial so that patients can receive effective interventions to decrease the likelihood of disease progression or complications. 

The Screening measure is based on the United States Preventive Services Task Force (USPSTF) 2021 Prediabetes and Type 2 Diabetes: Screening recommendation.² “The USPSTF recommends screening for prediabetes and type 2 diabetes in adults aged 35 to 70 years who have overweight or obesity.”²

Furthermore, this measure would address a recommendation from the National Clinical Care Commission (NCCC) to Congress and the Secretary of Health and Human Services (HHS), which called for adopting the Screening measure developed by the American Medical Association as part of a strategy to prevent diabetes among high-risk individuals.³

Based on the above recommendations, this measure would be recognized by physicians as clinically appropriate and meaningful for improved patient care. The measure targets an appropriate patient population that would clearly benefit from glucose screening. We believe the measure specifications are feasible to implement by most health care organizations; most organizations routinely capture the data elements in their EHR. Additionally, this measure is both valid and reliable as demonstrated in the testing results. 

Dr. Cody Brown believes that screening for abnormal glucose is an important preventive service and is reasonable to include in accountability programs. 

References:

¹CDC. (2024, July 23). National Diabetes Statistics Report. Retrieved November 15, 2024, from Diabetes website: https://www.cdc.gov/diabetes/php/data-research/ 

²US Preventive Services Task Force. (2021). Screening for Prediabetes and Type 2 Diabetes: US Preventive Services Task Force Recommendation Statement. JAMA, 326(8), 736–743. https://doi.org/10.1001/jama.2021.12531

³Report to Congress on Leveraging Federal Programs to Prevent and Control Diabetes and Its Complications. National Clinical Care Commission, 2021, https://health.gov/about-odphp/committees-workgroups/national-clinical-care-commission/report-congress.

CORE developed the Addressing Social Needs (ASN) eCQM to measure screening of patients for social needs within four domains – food insecurity, housing insecurity, utility insecurity, and transportation insecurity – as well as if an intervention activity is performed. The ASN eCQM aims to build upon existing measurement by:

• Enhancing the accuracy of measurement by refining social need domain definitions and requiring technical standards for endorsed screening tools;
• Promoting efficiency and alignment across the ecosystem through use of all-payer eCQMs;
• Improving alignment with national health information technology interoperability standards (USCDI); and

• Encouraging follow-up when screening is positive.

   

The measure is being considered for the Inpatient Hospital Reporting (IQR) Program, the Medicare Promoting Interoperability Program, and the Merit-based Incentive Payment System (MIPS).

It is well documented that racial and ethnic minorities represent a disproportionate share of patients in the ED and are more likely to rely on emergency care for both time-sensitive and non-urgent care needs.[1] We also recognize that much more work needs to be done to address these disparities. Thus, we appreciate CMS’ ongoing effort to assess how best to measure health care disparities and report those results to health care providers.

As emergency physicians, we see patients from all social statuses, and both by law and by oath, we treat all patients that come through our doors. EDs serve as the safety net in many communities, providing a place where those who are most vulnerable and those in need of the most immediate attention can receive care. The unique role of emergency medicine positions EDs as potential drivers of health equity given our compulsory commitment to treating every patient. 

However, despite the disproportionate representation of social vulnerability in so many ED patients, most EDs do not currently have the necessary resources to screen for and initiate interventions on social determinants of health (SDoH) in their patients. The integration of screening for social needs, including food insecurity, housing insecurity, transportation insecurity, and utility insecurity, could facilitate the allocation of critical resources, such as social workers, case managers, and community health workers into emergency care model, addressing health inequities directly from the ED setting. This additional screening would pave the way for a more streamlined continuum of care, potentially transforming the post-ED outcomes and long-term health trajectories of some the country’s most vulnerable populations, as well as reduce costs for low-acuity ED care use for visits in which patients delayed care because they did not have access to a primary care physician or specialist.

However, the current lack of necessary resources to screen for and initiate interventions renders this measure inappropriate for emergency physicians through the MIPS program. Clinicians should not be penalized for their inability to connect patients to necessary interventions due to factors outside of their control. Further, institutions that have the resources to evaluate social drivers of health will perform well on this measure, and therefore choose to report it, which may skew a small subset to high performance. This may cause CMS to judge this measure to be prematurely “topped out” when in fact the majority of clinicians are not reporting on those measures due to the continuing need for improvement. It is in CMS’ interest for the health of patients to encourage physicians to continue to improve in those areas, rather than drop the measure for reporting. The current topped out process leads to high administrative costs and burden because of the need to frequently implement new processes in order to report new measures and the continuous need for new measures to be developed to replace those topped out measures. In addition, it penalizes clinicians who focus on improving their performance on certain quality measures over time and, in some cases, forces them to switch to new measures that may be less meaningful to their clinical practice.

Further, the institutions that have the necessary resources to effectively implement screening processes for social drivers of health often treat patients that do not experience food insecurity, housing instability, transportation challenges, utility difficulties, interpersonal safety issues, and other negative social determinants of health. Thus, the actual reported data may not accurately capture the measurement intent.

However, collection of this data is still valuable to assessing the social needs of patient populations. Thus, we request that the ASN eCQM be included in the Hospital OQR Program or another data collection program that does not penalize individual clinicians or unfairly penalize institutions that have higher proportions of populations that screen positive. Thus, the measure would serve to identify patterns in SDoH, screening rates, and intervention resource availability, rather than putting the onus on an individual provider. 

[1] Richardson LD, Norris M. Access to Health and Health Care: How Race and Ethnicity Matter: ACCESS TO HEALTH AND HEALTH CARE. Mt Sinai J Med. 2010;77(2):166-177. doi:10.1002/msj.20174. 

My name is Dr. Lenore T. Coleman.  I am the President and Founder of Total LIfestyle Change, Inc. (nonprofit) and Healing Our Village of Maryland, Inc. (MBE).  I have been a pharmacist for 45 years and a CDCES for over 15 years.  We need to provide ongoing screening of high risk patients with obesity and cardiovascular disease with a family history of diabetes especially in African American and Latino Populations.  We have provided point of care testing for over 30 years.  In these high risk populations, we have found that 1 out of 3 participants have diabetes or prediabetes.  Unfortunately, we have been providing this service FREE OF CHARGE since there is no reimbursement for Screening for diabetes or prediabetes currently covered by most health plans including Medicaid.  The new measure for prediabetes screening would be very helpful for us to stem the tide of prediabetes and subsequent diabetes.  The data is clear, that with proper treatment and lifestyle changes we can reduce the risk of prediabetes becoming diabetes.  it is time we do something to make sure that the number of people that continue to have prediabetes decreases instead of increases.

There are 25 metrics for the PSSM. KHA encourages simplification of this measure and continuation of this as an attestation. 

Please accept this comment for the following measures:

MUC2024-030 - Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization

MUC2024-032 - Hospital 30-day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Heart Failure (HF) Hospitalization

MUC2024-040 - Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization

MUC2024-041 - Hospital-Level, 30-Day, Risk-Standardized Readmission Rate (RSRR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA)

MUC2024-042 - Hospital-Level, Risk-Standardized Complication Rate (RSCR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA)

MUC2024-043 - Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following Acute Ischemic Stroke Hospitalization with Claims-Based Risk Adjustment for Stroke Severity

MUC2024-045 - Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Pneumonia Hospitalization

MUC2024-046 - Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Coronary Artery Bypass Graft (CABG) Surgery

MUC2024-085 - Hospital Harm – Anticoagulant-Related Major Bleeding

The Kansas Hospital Association requests that CMS or PRMR explain how these measures differ from current measures and specify the changes. Additionally, all COVID patients should be excluded from pneumonia, COPD, and other diagnoses that we know are impacted by COVID. Hospitals are still being penalized due to COVID because of the long term impacts to patients not being recognized in quality measures. As a result, KHA recommends that COVID patients be excluded from all readmissions measures. Additionally, volumes are so low in small PPS and CAHs that the measures end up unfairly penalizing those hospitals and do not accurately reflect the quality care that is provided by these facilities. In addition, having a Medicare Advantage plan is a risk factor for readmission, as hospitals are seeing patients being readmitted because MA denied or delayed that patient’s care.

Please accept this comment for the following measures:

MUC2024-067 - Proportion of patients who died from cancer admitted to the ICU in the last 30 days of life

MUC2024-068 - Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of life

MUC2024-078 - Proportion of patients who died from cancer admitted to hospice for less than 3 days

The MUC list indicates that these measures will be included in OQR and IQR programs. It is unclear how applicable these measures will be to rural hospitals and could increase reporting burden significantly. We encourage more study of these measures to determine rural relevance.   

Please accept this comment for the following measures:

MUC2024-069 and MUC2024-072 - Addressing Social Needs Assessment & Intervention

While the Kansas Hospital Association supports the assessment of social drivers of health and the documentation of the assessment, we do not support requiring intervention be part of this measure. In rural communities, especially frontier communities, there is a lack of social supports and services that makes intervention difficult if not impossible. Additionally, patients may be more apt to decline services offered in small communities where there is less privacy than in a larger, urban community. Another option to address this would be to add exclusions to this measure if there are no support services available in the community to address the individuals’ needs and if the patient declines referral for intervention or the services offered. Further, we urge CMS to provide reimbursement for hospital staff to provide interventions in order to make this a sustainable practice. 

While this measure is very narrow in scope and most rural hospitals will have low to no volume to report, this measure does provide an opportunity to discuss best practices with staff and draw attention to an important condition and issue.

ACEP commends the Partnership for Quality Measurement for including a measure that addresses boarding in the emergency department (ED) for recommendation consideration. Please see attached for our full comments. 

Please accept this comment for the following measures:

MUC2024-075 and MUC2024-095 - Emergency Care Capacity and Quality (ECCQ)

The Kansas Hospital Association would like to note that more often than not, wait times in the ED are driving by lack of bed availability at higher level of care, behavioral health facility or long term care facility, lack of EMS transport, and continuing workforce challenges. This measure does not take into account the challenges in communities with these issues and there is too much in one measure. CMS is already requiring gathering in OP-18 median time to dismissal. Some EHRs have the capabilities to track components of this measure, but not all, and EHR buildout can be costly. This measure appears to be duplicative of OP-22. Is CMS planning to retire OP-22 if this is added?  KHA recommends this measure not be included. Additionally, it appears that the 'retired' ED-1 and ED-2 which were burdensome for hospitals to report, are included in these measures. It is a complicated measure and will cause a significant increase in reporting that some of our hospitals do not have.  This measure also does not align with CMS’s initiative to have all measures moved to eCQM.  This measure is a burden to all hospitals to gather 100% of the time, especially for REH staff to gather these data points. 

I am Associate Professor of Medicine at Johns Hopkins, a practicing general internist and diabetes prevention researcher. I appreciate the opportunity to provide a public comment in support of adopting the MUC2024-028 Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes (Screening).

Screening for prediabetes and undiagnosed type 2 diabetes is critical to improving both prevention and care of type 2 diabetes. The Centers for Disease Control and Prevention (CDC) estimates that approximately 97.6 million American adults have prediabetes.¹ They note that more than 80% of adults with prediabetes are not aware that they have the condition. Additionally, the CDC estimates 38.4 million adults have diabetes with 8.7 million being undiagnosed.¹ The prevalence of prediabetes and diabetes also increases with age.¹ Early identification of both prediabetes and type 2 diabetes is crucial so that patients can receive effective interventions to decrease the likelihood of disease progression or complications. Prediabetes is associated with a 5-year of developing of type 2 diabetes of up to 50%. 

Early diagnosis allows for earlier intervention. As a general internist, I take care of many patients who have been diagnosed with prediabetes. Fortunately, we have a robust Diabetes Prevention Program at Johns Hopkins and we use the medication metformin for prevention so I get my patients into the DPP and on medication to help prevent diabetes. I also take care of many patients with diabetes and have seen the spectrum of complications from retinopathy to chronic kidney disease requiring dialysis to toe amputation from foot infections. 

The Screening measure is based on the United States Preventive Services Task Force (USPSTF) 2021 Prediabetes and Type 2 Diabetes: Screening recommendation.² “The USPSTF recommends screening for prediabetes and type 2 diabetes in adults aged 35 to 70 years who have overweight or obesity.”²

Furthermore, this measure would address a recommendation from the National Clinical Care Commission (NCCC) to Congress and the Secretary of Health and Human Services (HHS), which called for adopting the Screening measure developed by the American Medical Association as part of a strategy to prevent diabetes among high-risk individuals.³

Based on the above recommendations, this measure would be recognized by physicians as clinically appropriate and meaningful for improved patient care. The measure targets an appropriate patient population that would clearly benefit from glucose screening. We believe that the specifications will validly capture the measure concept and it would be feasible to implement by most health care organizations; most organizations routinely capture these data elements in their EHR. 

I strongly believe that screening for abnormal glucose is an important preventive service and is reasonable to include in accountability programs. 
 

References:

¹CDC. (2024, July 23). National Diabetes Statistics Report. Retrieved November 15, 2024, from Diabetes website: https://www.cdc.gov/diabetes/php/data-research/ 

²US Preventive Services Task Force. (2021). Screening for Prediabetes and Type 2 Diabetes: US Preventive Services Task Force Recommendation Statement. JAMA, 326(8), 736–743. https://doi.org/10.1001/jama.2021.12531

³Report to Congress on Leveraging Federal Programs to Prevent and Control Diabetes and Its Complications. National Clinical Care Commission, 2021, https://health.gov/about-odphp/committees-workgroups/national-clinical-care-commission/report-congress.

See attached letter from Jacquie Cooke,  Chief Legal and Regulatory Officer, WeightWatchers

UnitedHealthcare (UHC) supports this measure with modification. We support incorporating health equity and measures specific to Social Risk Factors (SRFs) into the Star Ratings program rather than through risk adjustment. The current HEDIS Screening and Referral to Social Services for Social Needs (SNS-E) measure is an important initial step in creating a standardized and inclusive measure that evaluates social needs screenings and referrals across a wide range of the population, with stratifications based on product line and age. UHC recommends CMS and NCQA start with a smaller denominator and more stratifications. For example, in the Medicare population, we recommend that screening measures focus on (and add stratifications for) those individuals that have SRFs that align with the Health Equity Index (dual eligible/low-income status or entitled to Medicare due to disability) in order to maximize impact. The measure also focuses on Logical Observation Identifiers Names and Codes (LOINC) and should include specifications to directly capture ICD10-CM codes. The 2020 American Health Information Management Association Social Determinants of Health (SDOH) survey indicated that, among organizations that collect SDOH data, 90% use ICD-10-CM to collect data and only 8% use LOINC¹. UHC also supports capturing data from across the heath industry, such as from Health Risk Assessments or provider screenings, to limit duplicative activities.

1. https://www.ahima.org/landing-pages/social-determinants-of-health-survey/

UnitedHealthcare (UHC) does not support adding this measure to the Star Ratings at this time. From a policy perspective, UHC supports the proposal to measure vaccination through clinical data driven measures rather than survey data. This change will help ensure appropriate exclusions, appropriate measurement based on clinical guidelines, and provide a framework to include new vaccinations, such as COVID-19, when formal clinical guidelines are established and remain stable. However, there are currently significant disparities between the number of people who report receiving an influenza vaccination on the CAHPS survey and the figures recorded in Electronic Clinical Data Systems (ECDS) reporting.  As a result, UHC recommends delaying the transition until the accuracy and reliability of clinical data is addressed. 

UnitedHealthcare (UHC) only supports adding the screening indicator to the Star Ratings. Although we agree with the US Preventive Services Task Force (USPSTF) recommendation that patients who screen positive for depression should be evaluated further, the impacts of this measure, both intended and unintended, are not well understood at this time.¹  We recommend CMS proceed with adding only the screening indicator of the measure to the Star Ratings.

1. US Preventive Services Task Force, Barry, M. J., Nicholson, W. K., Silverstein, M., Chelmow, D., Coker, T. R., Davidson, K. W., Davis, E. M., Donahue, K. E., Jaén, C. R., Li, L., Ogedegbe, G., Pbert, L., Rao, G., Ruiz, J. M., Stevermer, J. J., Tsevat, J., Underwood, S. M., & Wong, J. B. (2023). Screening for Depression and Suicide Risk in Adults: US Preventive Services Task Force Recommendation Statement. JAMA, 329(23), 2057–2067. https://doi.org/10.1001/jama.2023.9297

On behalf of the more than 9,000 physiatrists of the American Academy of Physical Medicine and Rehabilitation (AAPM&R), we appreciate the opportunity to submit comments to the Partnership for Quality Measurement (PQM) in response to its 2024 Pre-Rulemaking Measure Review Measures Under Consideration List for Public Comment. 

AAPM&R is the national medical specialty organization representing physicians who are specialists in physical medicine and rehabilitation (PM&R). PM&R physicians, also known as physiatrists, treat a wide variety of medical conditions affecting the brain, spinal cord, nerves, bones, joints, ligaments, muscles, and tendons. PM&R physicians evaluate and treat injuries, illnesses, and disability and are experts in designing comprehensive, patient-centered treatment plans. Physiatrists utilize cutting-edge as well as time-tested treatments to maximize function, quality of life, and independence for their patients, and as such are leaders in the field of providing care to the disability community. With their training and expertise, PM&R physicians strive to deliver high-quality, cost-effective rehabilitative care to help patients achieve the highest level of functional ability and quality of life across the continuum of care. AAPM&R has actively participated in several earlier waves of measure development through comment opportunities and participation on clinical subcommittees including the most recent “movement disorders” cost measure development workgroup.

While AAPM&R has been asking for cost measure development relevant to PM&R physicians for years, and we appreciate being included in this latest wave, we have concerns regarding the proposed cost measure (MUC2024-101) as is. 

• AAPM&R continues to advocate for a simpler cost measure methodology that busy clinicians can understand. 
• AAPM&R has concerns that while all conditions within this cost measure are similar (Parkinson Syndromes, Multiple Sclerosis and Amyotrophic Lateral Sclerosis) there can and will be major differences in care and treatment that could negatively affect a clinician’s cost measure scores. 
• AAPM&R has major concerns that this cost measure has not been properly tested, reviewed by the Measure Applications Partnership (MAP) workgroup or used in any Medicare program. Therefore, we suggest the following:
  • Test this measure for a full year in the MIPS program with no payment penalties attached. 
  • Go through the Consensus-Based Entity (CBE) endorsement process.

Thank you for your considerations of these comment. If AAPM&R can be of further assistance, please contact Beth Radtke, Director of Quality and Research at [email protected]. 

See attached comment letter from Jacquie Cooke, Chief Legal and Regulatory Officer, WeightWatchers