PRMR MUC List

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

While the American Medical Association (AMA) appreciates the expansion to Medicare Advantage patients to provide a broader picture on readmission rates, we do not support inclusion of this measure in the Hospital Readmission Reduction Program given our concerns with its reliability. Testing demonstrated that reliability is 0.56 using the measure’s case minimum of 25 patients and we believe that all measures used in this program should achieve a high level of reliability (0.70 at a minimum). 

As a result, the AMA believes that the PRMR recommendation should be “Do Not Support.”

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

While the American Medical Association (AMA) appreciates the expansion to Medicare Advantage patients to provide a broader picture on readmission rates, we do not support inclusion of this measure in the Hospital Readmission Reduction Program given our concerns with its reliability. Testing demonstrated that reliability is 0.612 using the measure’s case minimum of 25 patients and we believe that all measures used in this program should achieve a high level of reliability (0.70 at a minimum). 

As a result, the AMA believes that the PRMR recommendation should be “Do Not Support.”

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

While the American Medical Association (AMA) appreciates the expansion to Medicare Advantage patients to provide a broader picture on readmission rates, we do not support inclusion of this measure in the Hospital Readmission Reduction Program given our concerns with its reliability. Testing demonstrated that reliability is 0.118 using the measure’s case minimum of 25 patients with two-year projections and we believe that all measures used in this program should achieve a high level of reliability (0.70 at a minimum). While we appreciate seeing how the measure performs using two or three years of data, the number of years of data that will be used to calculate the measure should be clearly defined and we would note that the minimum reliability did not improve significantly with the additional year.

As a result, the AMA believes that the PRMR recommendation should be “Do Not Support.”

I am writing in support of MUC2024-074 Median time to Pain Medication for patients with a Diagnosis of SCD with acute VOC.

While it is important that patients with SCD receive timely care, I am a concerned that, because of the rush to get pain medicine within that first 60 minutes, that patients with SCD will receive suboptimal care by using either motrin/Ketorolac or acetaminophen or alternatively, oral opioids which may not provide sufficient pain relief, but will meet the definition of timeliness.

Care should include

1. rapid evaluation of the patient to make sure that their pain is associated with an acute SCD VOC vs other medical concerns
2. Use of individualized pain plan or weight based dosing 
3. Use of ACEP SCD guidelines 

Sincerely,

Crawford Strunk, MD

Cleveland Clinic Foundation

Comments from a Food Bank Perspective:

Roadrunner Food Bank of New Mexico is engaging in health-focused work when it comes to distributing food to our neighbors throughout the state. By partnering with healthcare entities and health focused organizations, Roadrunner is increasing its nutrition services beyond the distribution parking lots. The goal of this work— to improve food insecurity AND improve health outcomes. Recent studies have associated food insecurity with increased odds of self-reported poor health and development of chronic diseases such as obesity, diabetes, and hypertension for young and older adults. New Mexicans across the state are struggling with nutrition related chronic diseases. 30.9% of the adult population are living with obesity, 36.1% of the adult population are diagnosed with prediabetes, and 12.3% of the adult population have been diagnosed with diabetes.¹ Roadrunner is determined to provide our neighbors with nutritious foods that can help prevent and/or manage nutrition related chronic diseases, such as prediabetes, diabetes and other comorbidities which  is why additional diagnostic tools (abnormal glucose measuring) are necessary to sustain health and well-being for New Mexicans. 

Healthy Foods Center

The Health Foods Center (HFC) at Roadrunner provides healthy food options to people referred by a healthcare partner in the Alburquerque and surrounding areas. Currently the Healthy Foods Center serves an estimated unique 415-530 households in any given month: approximately 1,000 individuals. Going into 2025, Roadrunner hopes to transform the Healthy Foods Center into a more focused Food Is Medicine: Medically tailored grocery access point. This includes Nutrition counseling, wrap around services, in-depth collaboration with Public Benefits team, tracking identified health outcomes (I.e. more involvement with healthcare partners, integration within a closed loop referral system, etc.) This program will be intended to continue to deliver health focused groceries to referred community members, depending on which programmatic track they are referred to, they will have additional support and participation goals as well as create a broader access point for general produce RX referrals. The health of our neighbors begins with nutrition which is why approaching food insecurity through a food is medicine framework is essential for influencing positive health outcomes.

CDC Diabetes Equity Grant

Through partnership with Presbyterian Healthcare Services, Roadrunner is engaging in Diabetes equity work throughout the state with a goal of expanding diabetes resources and increasing access to healthy food. Fifty percent of food insecure households have someone in the home with high blood pressure, and thirty-three percent of food insecure households have someone in the home with diabetes.² These percentages reflect the need to ensure the food and resources we are distributing through our network lead to better health outcomes. By engaging our food distribution partners in health equity initiatives and diabetes education, our neighbors are getting services they need. Diabetes resources such as cooking classes and Diabetes Self-Management education classes offered by Presbyterian are expanding throughout the state with Roadrunner holding a large role in outreach and resource navigation. Roadrunner is assisting our partners in promoting healthier lives for New Mexicans managing diabetes.  

Prediabetes Quality Measure

Food is an essential element to managing chronic diseases. When our neighbors are experiencing food insecurity, it is common for many to overlook their health until symptoms arise, often, putting off preventative measures and screenings. For Type 2 diabetes, symptoms can take several years to develop and can be mild or go unnoticed. Most people with type 2 diabetes are diagnosed 4–7 years after the onset of hyperglycemia, and some people may not be diagnosed until they experience diabetes-related health problems, such as blurred vision or heart disease.³ This abnormal glucose screening has the potential of improving the lives of many New Mexicans who are food insecure and experiencing prediabetes.  

References:

1. https://diabetes.org/sites/default/files/2023-09/ADV_2023_State_Fact_sheets_all_rev_New_Mexico.pdf
2. https://www.rrfb.org/learn/hunger-research/hunger-in-new-mexico/
3. https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/type-2-diabetes#:~:text=Symptoms%20of%20type%202%20diabetes,blurred%20vision%20or%20heart%20disease.

The Renal Physicians Association (RPA) is the professional organization of nephrologists whose goals are to ensure optimal care under the highest standards of medical practice for patients with kidney disease and related disorders. RPA acts as the national representative for physicians engaged in the study and management of patients with kidney disease. 

RPA recognizes the importance of improving transplantation rates for patients with ESRD, but does not support the attribution of successful or unsuccessful waitlisting to individual practitioners or group practices and thus cannot support this measure.  As previously noted, RPA believes that while referral to a transplant center and initiation or even completion of the waitlist evaluation process might be appropriate measures for these levels of analysis that could be used in CMS’s quality programs, the proposed clinician/group level Prevalent Standardized Waitlist Ratio (PSWR) measure is not.  Waitlisting is a decision made by the transplant center and is beyond the control of a practitioner or practice. 
 

RPA’s specific concerns are outlined below. 
 

Attribution.  As above, we strongly object to attributing successful/unsuccessful placement on a transplant waitlist to individual clinicians or group practices and believe this is a fatal structural flaw with the measure. The transplant center decides whether a patient is placed on a waitlist, not the practitioner or group practice. There are many obstacles and delays in the evaluation process with multiple parties that have nothing to do with the treating nephrologist or group. In fact, both TEP reports cited in the measure’s evidence highlight similar concerns: “…there were ongoing concerns expressed about the ultimate control exerted by transplant centers in the decision to waitlist. In particular, a number of TEP members called attention to wide variations in transplant center practices with respect to waitlisting criteria, exclusion criteria, and the likelihood of waitlisting.”
 

RPA believes penalizing a clinician/group practice each month through the PSWR for these or other delays is not only inappropriate; it is fundamentally misaligned with principle that measures’ attribution models should fairly and accurately assign accountability. RPA emphasizes our commitment to improving transplantation access, but we believe other measures with an appropriate sphere of control should be pursued. 
 

Variation in Transplant Center Eligibility Criteria. RPA notes that criteria indicating a patient is “not eligible” for transplantation can differ by geographic location.  For instance, one center might require evidence of an absence of chronic osteomyelitis, infection, heart failure, etc., while another may apply eligibility exclusions differently or have additional or different criteria.  The degree to which these biological factors influence waitlist placement must be accounted for in any model for the measure to be a valid representation of waitlisting. 
 

Measure Reliability. Finally, the overall IUR of the PSWR is 0.56, interpreted as “questionable” reliability by statistical convention.[1]  Thus nearly half of the observed variation in the measure could be attributed to random noise rather than true performance differences between providers. Additionally, as reliability statistics were not stratified by facility size, we are unable to discern how widely reliability varies across the spectrum of practitioner and group practice sizes.  As has been the case with other CMS standardized ratio measures, we are concerned that the reliability for small providers might be substantially lower than the overall IURs.  To illustrate our point, CMS’s Standardized Transfusion Ratio for Dialysis Facilities (STrR) measure (NQF 2979) was found to have an overall IUR of 0.60; however, the IUR for small facilities (defined by CMS as <46 patients for the STrR) was only 0.3 (“poor” reliability).  Without evidence to the contrary, RPA is concerned that PSWR reliability is similarly lower for small groups, with the unintended consequence of the imposition of penalties on the most financially vulnerable clinician groups treating the most socially and medically disadvantaged patients. RPA believes it is incumbent on CMS to demonstrate reliability for all providers by stratifying data by practice size.

[1] Landis J, Koch G.  The measurement of observer agreement for categorical data.  Biometrics. 1977;33:159-174.

The Renal Physicians Association (RPA) is the professional organization of nephrologists whose goals are to ensure optimal care under the highest standards of medical practice for patients with kidney disease and related disorders. RPA acts as the national representative for physicians engaged in the study and management of patients with kidney disease. 

RPA recognizes the importance of improving transplantation rates for patients with ESRD, but does not support the attribution of successful or unsuccessful waitlisting to individual practitioners or group practices and thus cannot support this measure.  As previously noted, RPA believes that while referral to a transplant center and initiation or even completion of the waitlist evaluation process might be appropriate measures for these levels of analysis that could be used in CMS’s quality programs, the proposed clinician/group level Prevalent Standardized Waitlist Ratio (PSWR) measure is not.  Waitlisting is a decision made by the transplant center and is beyond the control of a practitioner or practice. 
 

RPA’s specific concerns are outlined below. 
 

Attribution.  As above, we strongly object to attributing successful/unsuccessful placement on a transplant waitlist to individual clinicians or group practices and believe this is a fatal structural flaw with the measure. The transplant center decides whether a patient is placed on a waitlist, not the practitioner or group practice. There are many obstacles and delays in the evaluation process with multiple parties that have nothing to do with the treating nephrologist or group. In fact, both TEP reports cited in the measure’s evidence highlight similar concerns: “…there were ongoing concerns expressed about the ultimate control exerted by transplant centers in the decision to waitlist. In particular, a number of TEP members called attention to wide variations in transplant center practices with respect to waitlisting criteria, exclusion criteria, and the likelihood of waitlisting.”
 

RPA believes penalizing a clinician/group practice each month through the PSWR for these or other delays is not only inappropriate; it is fundamentally misaligned with principle that measures’ attribution models should fairly and accurately assign accountability. RPA emphasizes our commitment to improving transplantation access, but we believe other measures with an appropriate sphere of control should be pursued. 
 

Variation in Transplant Center Eligibility Criteria. RPA notes that criteria indicating a patient is “not eligible” for transplantation can differ by geographic location.  For instance, one center might require evidence of an absence of chronic osteomyelitis, infection, heart failure, etc., while another may apply eligibility exclusions differently or have additional or different criteria.  The degree to which these biological factors influence waitlist placement must be accounted for in any model for the measure to be a valid representation of waitlisting. 
 

Measure Reliability. Finally, the overall IUR of the PSWR is 0.56, interpreted as “questionable” reliability by statistical convention.[1]  Thus nearly half of the observed variation in the measure could be attributed to random noise rather than true performance differences between providers. Additionally, as reliability statistics were not stratified by facility size, we are unable to discern how widely reliability varies across the spectrum of practitioner and group practice sizes.  As has been the case with other CMS standardized ratio measures, we are concerned that the reliability for small providers might be substantially lower than the overall IURs.  To illustrate our point, CMS’s Standardized Transfusion Ratio for Dialysis Facilities (STrR) measure (NQF 2979) was found to have an overall IUR of 0.60; however, the IUR for small facilities (defined by CMS as <46 patients for the STrR) was only 0.3 (“poor” reliability).  Without evidence to the contrary, RPA is concerned that PSWR reliability is similarly lower for small groups, with the unintended consequence of the imposition of penalties on the most financially vulnerable clinician groups treating the most socially and medically disadvantaged patients. RPA believes it is incumbent on CMS to demonstrate reliability for all providers by stratifying data by practice size.

[1] Landis J, Koch G.  The measurement of observer agreement for categorical data.  Biometrics. 1977;33:159-174.

To the Centers for Medicare and Medicaid Services: Pfizer is pleased to support the inclusion of MUC2024-081, Adult Immunization Status (AIS-E) of the Part C Star Ratings. As a vaccine manufacturer, Pfizer has interest in health care provider vaccine administration, including vaccine-related quality measures and programs. 

Pfizer strongly supports the inclusion of the AIS measure, which assesses the percentage of adults who are up to date on recommended routine vaccinations for influenza; tetanus and diphtheria (Td) or tetanus, diphtheria, and acellular pertussis (Tdap); zoster; and pneumococcal disease.

This measure helps to encourage uptake of vaccinations that are routinely recommended for adults by the Advisory Committee on Immunization Practices (ACIP) and the Centers for Disease Control and Prevention (CDC).[1] However, according to the CDC, “at least 3 out of every 4 adults are missing one or more routinely recommended vaccines”[2].  

Quality measures are an integral part of helping to encourage vaccine uptake, and inclusion of the AIS measure in the Star Ratings will support efforts to increase vaccination rates among adults and positively impact public health by providing visibility on vaccination receipt. 
 

This important aspect of preventive care is called out in CMS’s Universal Foundation, and including the AIS in the Part C Star Ratings would help encourage Medicare Advantage health plans to work together with providers in the Merit-Based Incentive Payment System MIPS and Medicare Shared Savings Program MSSP to ensure vaccine coverage. The inclusion of AIS in Part C Star ratings also creates common expectations for providers and health care organizations working with Medicaid program and Marketplace plans, where the AIS is also part of quality ratings. 
 

Additionally, the AIS measure can be updated to reflect recommendations for vaccinations related to COVID-19, respiratory syncytial virus (RSV), and hepatitis B vaccinations. Including a composite measure for vaccinations, like the AIS, would allow for updates to the measure that align with public health recommendations in a more comprehensive manner than individual vaccine measures. 
 

Pfizer appreciates this opportunity to participate in the Pre-Rulemaking Measure Review (PRMR) process and encourages CMS to include AIS to the Part C Star Ratings. 

[1] https://www.cdc.gov/vaccines/schedules/downloads/adult/adult-combined-schedule.pdf 

[2] https://www.cdc.gov/vaccines/hcp/adults/for-practice/increasing-vacc-rates.html 

As a program coordinator for a rural  Diabetes Prevention Program (DPP), and as a Certified Diabetes Educator with over 12 years experience, I am keenly aware of the need to encourage providers to more regularly screen  for diabetes and prediabetes to help prevent the disease and its extremely expensive treatments and complications. The screening measure for abnormal glucose that has just been added to the CMS 2024 Measures Under Consideration (MUC) list, is an excellent step to help healthcare providers (HCPs) become more consistent and confident in such screening.

I run a very effective DPP that has acheived Full Plus CDC recognition status. Our program is very successful and participant results demonstrate this including significant weight loss, increased physical activity and decreased A1C's (all critical components in preventing diabetes.   However, this success is rarely because providers refer people to the program. Some providers still do not see prediabetes as a real threat, and sometimes do not screen until people have symptoms of diabetes. This practice can prevent people from having the opportunity to prevent or delay diabetes, through programs like the DPP, or DSMES.  By approving the screening measure for abnormal glucose on the MUC list, more providers may learn to  develop the habit of screening early and appropriately, which could allow more people the opportunity to take steps to avert diabetes through programs like the DPP.  And for those who are diagnosed with diabetes, they then have a greater chance of preventing complications by have it well managed as early as possible.

I work very hard and spend much time trying to reach those at risk  for diabetesin our county, however, it would be so much more effective if all providers would screen for diabetes, and refer those with prediabetes to programs like the DPP.  By doing so, I could focus more on the delivery of the program, and reach even more people, potentially making a significant impact on prediabetes and diabetes in our area. Please consider approving the MUC screening measure for abnormal glucose.

Sincerely,

Nancy Gimenez RN/BSN/MS

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

As a primary care provider and health services researcher at UCLA focused on diabetes prevention, I know well that 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 type 2 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. These include both lifestyle and pharmacologic evidence-based interventions.

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 and health systems 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, since most organizations routinely capture these data elements in their EHR. Additionally, this measure is both valid and reliable as demonstrated in the testing results and has been shown to be acceptable to both patients and physicians.

In summary, O. Kenrik Duru, MD, MS believes that screening for abnormal glucose is an important preventive service and that it is reasonable to include in accountability programs.

Sincerely,

O. Kenrik Duru, MD, MS
Professor of Medicine
Division of General Internal Medicine/Health Services Research
Co-Director, Office of Physician-Scientist Career Development
David Geffen School of Medicine at UCLA
1100 Glendon Avenue, Suite 900
Los Angeles, CA 90024

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.
 

AOTA supports adopting the Person-Centered Outcome Measures: Goal-Identification, Follow-Up, and Goal Achievement measure for use in the Merit-Based Incentive Payment System (MIPS) Program.  Aligning care with clients’ goals improves client engagement, reduces unwanted care, and empowers clients to make decisions about their care.  Occupational therapy practitioners use PROMs during a comprehensive evaluation to develop care plans and to measure outcomes. PROMs can also be appropriate to use in clients who need skilled therapy services with a goal to maintain function. It will be important to provide further clarification on the definition of complex care needs.  

AOTA encourages CMS to add Occupational therapy practitioners as applicable providers for this measure and to consider other PROMS that could enhance the measure’s usefulness. 

AOTA supports the Patient Safety Structural Measure inclusion in the hospital QRP, HBPP, and PPS for exempt cancer hospital QRP.  Embedding this quality measure into organizations may help establish patient safety as a key organizational goal for hospitals and help to hold organizations more accountable for the care they provide.  Hospital-based Occupational therapy practitioners (OTPs) can support the 5 domains by helping to identify organizational gaps in achieving compliance and how to close these gaps – offering unique perspectives through an occupation-based lens. It should be noted that hospital staff (including OTPs) may experience additional administrative burden when using the measure due to the scope and depth of the measure. AOTA encourages CMS to monitor provider responses and adjust as needed to balance the goal of the measure with the demands of providing high-quality clinical care.  

AOTA supports CMS’ proposal to add the Social Need Screening and Intervention measure to the Medicare Part C star ratings.  Social drivers of health impact an individual’s quality of life, health, and daily functioning. Understanding social drivers impacting a patient’s wellbeing is an important aspect of quality healthcare delivery. For a patient experiencing health inequity, economic stability influencing food or housing insecurity, transportation, and interpersonal safety can impact their health condition and ability to access quality health care, as well as influence engagement and outcomes. It is important that we not only screen but provide follow-up interventions to address social needs that can have a negative effect on healthcare outcomes.   

AOTA supports the adoption of the Addressing Social Needs Assessment and Intervention measure in all proposed programs. The focus on screening and intervention is appreciated to close service gaps.  Social drivers of health impact an individual’s quality of life, health, and daily functioning. Understanding social drivers impacting a patient’s wellbeing is an important aspect of quality healthcare delivery. For a patient experiencing health inequity, economic stability influencing food or housing insecurity, transportation, and interpersonal safety can impact their health condition and ability to access quality health care, as well as influence engagement and outcomes.  

AOTA encourages CMS to include Occupational therapy (OT) as a confirming service for this measure in the Merit-Based Incentive Payment (MIPS) Program.  Occupational therapy practitioners assess social drivers of health as part of the comprehensive evaluation process, including use of the occupational profile, and address social drivers of health through their client-centered interventions. The Occupational Therapy Practice Framework: Domain and Process, Fourth Edition¹ states that every OT evaluation includes the occupational profile and the analysis of occupational performance. The occupational profile (www.aota.org/profile) includes patient information such as: Occupational history (i.e., life experiences, key issues or concerns related to social determinants of health); Values and interests; Personal information (e.g., age, sexual orientation, gender identity, race and ethnicity, cultural identification, social background, upbringing, psychological assets, education, lifestyle); and Priorities and desired targeted outcomes. This information is critical in developing a patient plan of care based on individual patient need in the context of their own environment. 

AOTA supports the Patient Understanding of Key Information Related to Recovery After a Facility-Based Outpatient Procedure or Surgery, Patient Reported Outcome-Based Performance measure. Providing personalized, clear discharge instruction is important to compliance and follow through with medical recommendations and prevent unnecessary hospital readmissions. Several factors can influence a patient’s understanding of discharge instructions including health literacy level and functional cognition.  

AOTA supports the Assessment of autonomic dysfunction and follow-up measure. Identifying and addressing autonomic dysfunction can prevent symptoms from worsening (fainting and having a fall that results in a fracture) and have a positive impact on a client’s ability to engage in meaningful activities.  

Listing only 1 discipline in the dysphagia follow-up actions, while other disciplines address dysphagia, can negatively impact access to critical services. Occupational therapists and occupational therapy assistants provide skilled care to clients of all ages with dysphagia. Swallowing is an essential activity of daily living: the inability to swallow negatively affects nutrition, overall health, and quality of life. Dysphagia is within the scope of Occupational therapy practice as supported by educational curriculum and a history of application in practice.  Occupational therapy practitioners can also provide interventions to address urinary urgency or incontinence which can have a negative impact on a client's sense of well-being and engagement in meaningful activities.

AOTA supports the patient reported falls plan of care measure. Falls continue to be a frequent cause of injury and are costly to the healthcare system, especially for older adults.  This measure will raise awareness of falls rates, can improve patient safety and lower healthcare costs by preventing or reducing future falls.  

A client may need multiple services to reduce fall risks.  AOTA encourages the measure developer to consider modifying the language for plan of care inclusion. For example, a client living at home may require a home safety evaluation by an Occupational therapy practitioner to adapt living spaces to increase safety and independence AND Physical therapy services for gait training. 

AOTA supports adopting the Quality of life outcome for patients with neurologic conditions measure.  Neurologic conditions can significantly impact a client's ability to participate in meaningful activities and general sense of well-being. Quality of life outcome measures can facilitate discussions that address what matters most to clients and improve care coordination. Occupational therapy is an important component of interdisciplinary care for persons with neurologic conditions, addressing physical, cognitive, and psychosocial barriers to participation in meaningful activities.  

AOTA supports CMS’ proposal to add the Depression Screening and Follow-Up for Adolescents and Adults measure. We appreciate the inclusion of non-pharmalogical interventions to meet the follow-up requirement for this measure. Depression can affect a client’s ability to take care of themself and complete necessary tasks, including ADLs and IADLs. The history of occupational therapy is rooted in mental health, and occupational therapy can have a direct, positive impact on behavioral health conditions. Through engagement in meaningful occupations, occupational therapy practitioners play a transformative role in helping people with behavioral health challenges through their expertise in occupational performance, activity analysis and design, environmental analysis, neurophysiology, psychosocial development, and group dynamics. Occupational therapy clinicians also work with individuals diagnosed with sleep insufficiency, which has been linked to chronic diseases including depression.

AOTA supports the Parkinson’s Syndromes, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS) cost measure inclusion in the Merit-Based Incentive Payment System (MIPS) program.  As stated in the measure rationale, Occupational therapy services can provide significant benefits for clients with movement disorders.  

AOTA encourages CMS to consider adding Occupational therapy practitioners (OTPs) to the attribution list and not including attribution checks related to medications for the condition prescribed. OTPs are ineligible to prescribe medications, yet every cost measure that has been developed—except for the low back pain measure—has chosen to include medication prescription within cost measure requirements, eliminating OTPs from reporting on otherwise appropriate measures of cost management. The inclusion of OTPs in MIPS cost measures is not only warranted by their active involvement in cost measure development but is also essential to achieving the program’s goal of improving care quality while controlling costs. 

The Academy of Nutrition and Dietetics (hereafter the “Academy”) 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 and other qualified health care providers 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. 

The Academy believes that screening for abnormal glucose is an important preventive service and is reasonable to include in accountability programs. 

Screening for prediabetes and undiagnosed type 2 diabetes is essential for early intervention, particularly from a nutrition perspective. Early identification enables timely implementation of Medical Nutrition Therapy (MNT)⁴, a key strategy to prevent, manage, and treat prediabetes, diabetes, and related weight concerns. By detecting these conditions sooner, providers can take proactive steps, such as referrals to registered dietitians to delay disease progression and optimize patient care.

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.

⁴ Medical Nutrition Therapy (MNT) is an evidence-based application of the Nutrition Care Process. The provision of MNT (to a patient/client) may include one or more of the following: nutrition assessment/reassessment, nutrition diagnosis, nutrition intervention and nutrition monitoring and evaluation that typically results in the prevention, delay or management of diseases and/or conditions. Commission on Dietetics Registration, Definition of Terms, November 2024.

Comments on behalf of the American Academy of Pediatrics, attached.

AOTA believes that the client's perspective is critical to measuring the performance of Home Health Agencies (HHAs) and appreciates efforts to streamline the HHCHAPS survey. The proposed changes to question number 7 in the Survey of Care to Patients removes the focus from whether the patient received skilled rehabilitation services.  AOTA encourages CMS to consider the impact of this change, especially at a time when therapists have reported a decline in skilled therapy utilization under PDGM.  

If the new language is adopted, it will be important it is not applied to skilled rehabilitation, as the question and examples provided might not reflect skilled therapy services.  

MUC2024-027: Patient Safety Structural Measure (submitted to the Hospital Committee)

 

Vizient appreciates efforts to support a more resilient pharmaceutical supply chain. P4QM seeks comments regarding the addition of two attestations related to supply resiliency and medication shortages to the Patient Safety Structural Measure (MUC2024-027). However, Vizient strongly suggests P4QM refrain from adding in these attestations and, instead, focus on incentives that can be provided to support hospitals and their efforts to bolster supply chain resiliency. Should P4QM disregard this suggestion, we suggest modifying the language as follows: 

• “Our hospital purchases medications by utilizing contracting provisions that promote supply chain resiliency either directly with vendors or indirectly through wholesalers or Group Purchasing Organizations”
• “Our hospital has policies and procedures to respond to medication shortages and outages.”

In addition, Vizient believes that structural measures, as opposed to outcome and process measures, are not appropriate to include in the Value-Based Purchasing (VBP) program, which is a pay for performance program. While Vizient has concerns about the measure, including its use in pay for reporting programs, we urge CMS to refrain from considering its inclusion in the VBP program.

Further, in reviewing the measure, there was no justification, evidence-based or otherwise, to include these specific terms in the attestation. This suggests that there may be even greater uncertainty regarding the implications of this measure, including whether it will enhance supply resiliency. 

While Vizient believes we understand the intent of the attestations, much of the language in the attestations is difficult to interpret and would pose implementation challenges, even if more specificity is provided. Therefore, significant deference should be provided to hospitals and this deference should be made clear, should these attestations advance. 

Comments regarding “Our hospital purchases medications by utilizing contracting provisions that promote supply chain resiliency, including multi-year contracts with volume guarantees and stringent “failure to supply” clauses, either directly with vendors or indirectly through wholesalers or Group Purchasing Organizations.”

Regarding this first attestation, Vizient is concerned the clarifying language (i.e., “including multi-year contracts with volume guarantees and stringent “failure to supply” clauses”) may unintentionally limit different approaches to purchasing medications, add undue burdens on hospitals and create unnecessary confusion, among other potential unintended consequences. For example, “multi-year contracts with volume guarantees” may place providers in a challenging position of purchasing unneeded products to satisfy volume guarantees, straining hospitals’ already limited resources. Further, a volume-based guarantee may be challenging for hospitals to meet since contracts may use alternative metrics (e.g., compliance rates).[1] 

Another example of how the measure attestation creates confusion is the language regarding “stringent ‘failure to supply’ clauses”, as it is unclear what would qualify as “stringent” or who would make this determination. While providing examples of types of provisions that promote supply chain resiliency may be useful, it is more critical that such examples are not interpreted as requirements and that there be flexibility in contracting. In other words, examples of potential contract terms should not dictate the types of provisions that are broadly included in contracts. 

In addition, Vizient notes that it is unclear from the modified measure Patient Safety Structural Measure (MUC2024-027) which medications are impacted by this attestation. For example, it would be extremely burdensome for a provider to purchase all medications using these specific contract provisions, particularly if a change was required with limited notice. While Vizient appreciates that the agency has not dictated which or what proportion of medications should be purchased to meet this attestation requirement, CMS should make clear that it is not dictating the scope or volume of medications that must be purchased using these strict contract terms.

Furthermore, Vizient notes our significant concern that the addition of this attestation requirement without positive payment adjustment opportunities for providers could have negative financial consequences. For example, no information is provided regarding the pricing implications of requiring specific changes to contract terms and no positive payment adjustment is contemplated. Providers may then be placed in the challenging position of having to renegotiate contracts while also facing financial penalties, such as those through the VBP program, due to this measure. 

Overall, Vizient recommends that the hospital committee and CMS oppose this measure, as incentives to support supply chain resiliency should be prioritized over penalties. Should this recommendation be disregarded, as noted above, we suggest that the following language be removed to ensure that there is greater flexibility in contracts, “including multi-year contracts with volume guarantees and stringent “failure to supply” clauses.” As a result, the attestation would read, “Our hospital purchases medications by utilizing contracting provisions that promote supply chain resiliency, either directly with vendors or indirectly through wholesalers or Group Purchasing Organizations.”

Comments regarding “Our hospital has policies and procedures to respond to medication shortages and outages, including ensuring continuity of pharmaceutical services to meet patient needs during emergencies for a minimum of 7 days.”

Vizient supports efforts to prevent drug shortages, enhance supply chain resiliency and support providers during periods of drug shortages. Vizient is also a pioneer in strategies to mitigate shortages, specifically through the establishment of buffer inventories, like those available through our Novaplus Enhanced Supply program. However, Vizient is concerned that the proposed language regarding the attestation (e.g., “ensuring continuity of pharmaceutical services to meet patient needs during emergencies for a minimum of 7 days”) is difficult to interpret and could be challenging to implement. For example, it is unclear whether CMS intends to include access to medications as “pharmaceutical services” or whether the agency is referring to services provided or performed by a pharmacist. In addition, it is unclear what is meant by “during emergencies,” as this can be interpreted very differently (e.g., provider interpretation of an emergency, hospital emergency, public health emergency declaration). Also, in emergency situations that are challenging to prepare for (e.g., those that increase demand for a specific product), medications may not be available or allocations may be applied, which limits access to supply. Further, requiring such a minimum supply level may deter providers from using such medications for patient care purposes.

Also, Vizient notes that certain medications, particularly controlled substances which are highly regulated, and medications that are in shortage, already pose challenges for hospitals to acquire to meet short-term needs. Thus, acquiring at least a 7-day supply of these medications could be beyond the providers’ control.

Lastly, Vizient notes that imposing additional proactive purchasing requirements can be financially challenging for hospitals that already operate on thin margins, and there would be costs associated with storing and managing the additional inventory. Should this attestation be included in the IQR, hospitals would have to pay additional funds to purchase, store and manage these medications without any additional financial support or reimbursement. As such, Vizient urges P4QM and CMS to refrain from including this attestation in the measure and to instead provide incentives to hospitals. Should this recommendation be disregarded, Vizient suggests that the following language be removed from the attestation to support greater flexibility for providers: “including ensuring continuity of pharmaceutical services to meet patient needs during emergencies for a minimum of 7 days”. As a result, the attestation would read, “Our hospital has policies and procedures to respond to medication shortages and outages”.

[1] For example, a contract may use a compliance rate based on prior purchases from a pool of several products (in contrast to NDC-specific volume requirements) which still offers manufacturer’s stability but provides flexibility to providers but is not a specific volume guarantee for a specific NDC.

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

Vizient commends the efforts by P4QM to update the MUC2024-030: Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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

Vizient commends the efforts by P4QM to update the MUC2024-032: Hospital 30-day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Heart Failure (HF) Hospitalization measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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

Vizient commends the efforts by P4QM to update the Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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

Vizient commends the efforts by P4QM to update the Hospital-Level, 30-Day, Risk-Standardized Readmission Rate (RSRR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

I whole-heartedly support the American Society of Hematology’s (ASH) new quality measure titled “Median Time to Pain Medication for Patients with Sickle Cell Disease with Vaso-Occlusive Episode.” I appreciate the hundreds of hours, meetings, and collaborations between both hematologists and emergency room providers (amongst others!) that went into the drafting of this important measure, and I know that consensus on the details of what is outlined in the measure draft was challenging to say the least. It is an important initial step in what I hope will be a series of steps to increasing accountability and quality of care for our patients with sickle cell disease, and I'm grateful to my colleagues that are leading the way in positive policy change, step-by-step.

Sincerely,

Mary Shapiro, MD

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

Vizient commends the efforts by P4QM to update the Hospital-Level, Risk-Standardized Complication Rate (RSCR) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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.

Vizient commends the efforts by P4QM to update the Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following Acute Ischemic Stroke Hospitalization with Claims-Based Risk Adjustment for Stroke Severity measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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

Vizient commends the efforts by P4QM to update the Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Pneumonia Hospitalization measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

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

Vizient commends the efforts by P4QM to update Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Coronary Artery Bypass Graft (CABG) Surgery (submitted to the Hospital Committee) measure by adding Medicare Advantage (MA) population data since more than half of Medicare patients are covered through MA plans. While Vizient appreciates the importance of updating this measure to reflect a broader range of Medicare beneficiaries, we anticipate that additional steps are needed to ensure that MA data can be used alongside fee-for-service (FFS) data. For example, there may be differences in how FFS claims and MA encounter data are recorded, yet it does not appear that this type of analysis has been completed. Vizient encourages CMS to analyze the data to ensure encounter data is accurate and comparable between FFS and MA before including MA beneficiaries in these measures.

Also, Vizient requests clarification regarding the rationale for the scope of measures for which MA data will be added, particularly since only one mortality measure is included (as opposed to several readmission measures). While other mortality measures exist, it is unclear why none were included on the MUC list. This issue should be clarified before only one mortality measure would have MA data included in CMS programs.

Additionally, with many measures being considered related to the 30-day RSRR, consistent with our prior comments, we caution CMS that evaluating measures for 30-day readmission rates is highly challenging given the many factors beyond a hospital’s control that can increase the likelihood of a readmission within a 30-day period. Vizient recommends CMS identify measures more within the provider’s locus of control, such as adherence to clinical care practices or possibly a shorter readmission assessment period (e.g., 3 to 7 days). 

MUC2024-069: Addressing Social Needs Assessment & Intervention 

Vizient commends P4QM for its efforts to prioritize health equity but have concerns regarding the Addressing Social Needs Assessment & Intervention measure. Vizient recognizes and supports the critical need to assess and address social needs to provide an opportunity to improve population health and advance health equity but is concerned with the burden associated with this measure, among other concerns, as noted below.

Based on Vizient’s review, one of the main differences between this new measure and the currently implemented health equity measures (e.g., Screening for Social Drivers of Health (SDOH) and Screen Positive Rate for Social Drivers of Health Care Setting) is the new language requiring “qualifying follow up action” within the visit for any positive social needs. Vizient is concerned that adding these requirements is overly burdensome, outside the hospitals’ locus of control and does not adequately recognize that hospitals are also working to treat patients’ acute health care issues. Such burdens are exacerbated when hospitals are also expected to oversee how health related social needs (HRSNs) are resolved. While hospitals play a critical role in aiding patients in many aspects of their life, Vizient is concerned that, through this measure, CMS would place unreasonable expectations on hospitals that are already working to address SDOH and provide care.

Vizient is also concerned that the Addressing Social Needs Assessment & Intervention measure could create confusion because it does not include a standard definition for “intervention,” “qualifying follow up action,” “assessed,” “social needs,” and/or all of the listed qualifying actions. In addition, the domains of HRSNs are not clearly defined. Clear and consistent definitions are critical to collecting data that can be meaningfully used by the healthcare system to improve patient outcomes and is also critical for benchmarking purposes. Additionally, defining these terms supports identification and proper use of validated screening tools. As P4QM is aware, standardization is critical for ensuring that patient data collected by health systems and other providers can be effectively utilized to address patient needs and identify broader, community-wide needs to improve SDOH. Vizient is concerned that this measure as written will limit the utility and comparability of collected data, even though the measure is an electronic clinical quality measure. We recommend that P4QM work with stakeholders to more clearly define terms and domains related to this measure.

Further, the Addressing Social Needs Assessment & Intervention Measure does not account for geographic variations in communities and therefore may be missing an opportunity to ask or prioritize screening for certain social needs drivers that are relevant to the community. Vizient is concerned that the ability of hospitals to perform interventions after assessing patients’ social needs may be affected by the resources available in some areas (e.g., those hospitals in locations with fewer resources may appear to perform worse due to limited intervention options). As noted in Vizient’s 2023 MUC list comments (available at: https://vizientinc-delivery.sitecorecontenthub.cloud/api/public/content/367ac0aa486343e1b1c108fb53d739f7), our analyses have shown significant variation in community need across large geographic areas as well as within local markets at the zip code and census tract level. If this measure does not account for geographic variation of social drivers impacting the population, interpretation of these data points could not only be misleading but could also take away the opportunity to prioritize asking patients about social needs that are meaningful to them. Further, hospitals with higher levels of community need may be further challenged to support patients and maintain relationships of trust with patients if they perform redundant, generic screenings without having the resources or capacity to better address social needs. To help address these concerns, accommodations for geographic variation could be achieved through benchmarking using an index of local obstacles to care (e.g.,  the Vizient Vulnerability Index™, more information available at: https://www.vizientinc.com/what-we-do/health-equity/vizient-vulnerability-index-publicaccess).

Finally, Vizient questions the decision to remove interpersonal safety as a domain of social need. We understand it can be challenging to screen patients for this domain but are also aware of the important impact that screening and appropriate referrals can have to support patients screening positive in the interpersonal safety domain. Further, widely utilized screening tools utilize this measure, so removing it could be disruptive to current practices or signal that this domain is less important than other domains to screen. We suggest maintaining the interpersonal safety domain within this measure but also encourage opportunities to provide hospitals with greater flexibility in how screening for this domain occurs (e.g., if performed differently from standard screening protocol) and CMS sharing best practices for screening in this domain.

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

Vizient appreciates P4QM’s efforts to reduce patient harm and improve outcomes for patients requiring emergency care in an emergency department (ED) by addressing the variation of emergency care and measuring the capacity and quality of emergency care in the Emergency Care Capacity and Quality (ECCQ) measure. However, we have concerns regarding the appropriateness of the stratification (e.g., Four cohorts of the measure will be calculated, stratified by age and mental health visits) and risk adjustment (e.g., Volume-standardization is harmonized with other existing measures and accommodates a “like to like” comparison among hospitals) methodology used in this measure. For example, there may be other factors that need to be risk adjusted or otherwise considered before the measure is advanced, such as patient acuity, differences among facilities’ resources (e.g., if part of a larger health system, trauma centers) and different patient populations. Without proper risk adjustment and stratification, the results from this measure could be misleading. Based on this information, Vizient does not believe this measure is ready to be considered for rulemaking and we encourage additional attention to be paid to identify more appropriate risk adjustment and stratification methodologies. 

Vizient also requests clarification regarding the potential burden associated with this measure. While eCQMs are more commonplace, there can still be challenges with reporting eCQMs and it is unclear whether such challenges have been considered.

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

Vizient commends P4QM on its efforts to reduce patient risk of anticoagulant medication-associated bleeding events but have concerns regarding the Hospital Harm – Anticoagulant-Related Major Bleeding measure. Vizient is aware of the importance of reducing hospital harm but would like to caution that this new measure could lead to unintended consequences that could negatively affect patient care. In addition, further clarification of several key definitions within the measure is needed before it should be considered for use in CMS programs.

Vizient is concerned that the structure of the measure may have unintentional results and may not adequately consider the appropriateness of furnishing anticoagulant medications. For example, the measure as currently drafted does not consider that medications and services (e.g., surgical procedures which may increase the risk of bleeding events which may require anticoagulant administration as prophylaxis to prevent thrombotic events associated with certain procedures) other than anticoagulants can cause bleeding events. As a result, the measure may be inappropriately identifying bleeding events as being anticoagulant-related bleeding events. 

Further, Vizient is also concerned that this measure, as currently written, will excessively discourage anticoagulant use, even if it is clinically appropriate. If providers are overly hesitant to administer anticoagulant medications for fear of scoring poorly on this measure, patient care may suffer, as using these medications may outweigh the risks in many circumstances. As a result, we question whether the measure would actually improve patient outcomes.

The measure developers note that this measure is intended to be partnered with the Hospital Harm: Postoperative Venous Thromboembolism (VTE) measure. Vizient has concerns that the partnering of Hospital Harm – Anticoagulant-Related Major Bleeding measure with the VTE measure is not a strong enough strategy to mitigate hospital harm because the VTE measure is no longer used in pay for performance programs, so higher performance on the VTE measure may be less of a priority for hospitals.

Also, Vizient notes that certain hospital accreditation bodies already require accredited hospitals to work towards improved use of anticoagulants so the measure may not be aligned with these efforts. For example, the Joint Commission established National Patient Safety Goal NPSG.03.05.01 (Reduce the likelihood of patient harm associated with the use of anticoagulant therapy), which aims to reduce the risk of harm associated with the use of anticoagulants by implementing standardized protocols and safety measures. Continuing to raise awareness within hospitals and supporting ongoing work to improve protocols would be more helpful than implementing a measure that could have dire unintended consequences. 

Also, this measure overview states that it is difficult to measure newer anticoagulants (i.e., direct acting oral anticoagulants (DOACs) such as apixaban and rivaroxaban) now routinely in use, and risks of adverse bleeding events and other negative outcomes from these newer anticoagulants have been identified. Given this stated challenge, Vizient suggests CMS instead focus on opportunities to encourage a medication management process that is designed to ensure the safe and efficient use of these medications, including through better monitoring, documentation and reporting of adverse events. 

As another alternative approach, Vizient suggests P4QM and CMS consider using the Warfarin - International Normalized Ratio (INR) blood test results measure, which is used broadly by healthcare providers. The Warfarin – INR blood test results measure reflects the percentage of cases that received Warfarin and have an INR of ≥ 5 any point after. Vizient welcomes the opportunity to meet with CMS and P4QM to further discuss this measure. 

Finally, Vizient requests clarification on a definition that was not fully developed in the measure as currently written – the term “coagulation disorder”. The term “coagulation disorder” is broad and encompasses a wide range of illnesses and it would be helpful to have more information on this term to allow hospitals to know which specific illnesses can be excluded from the measure’s denominator. Also, the full list of anticoagulants in the numerator for this measure is behind a firewall and not easily accessed on the Value Set Authority Center website, making this measure more challenging to evaluate from a clinical perspective.

MUC2024-067: Proportion of Patients Who Died from Cancer Admitted to the ICU in the Last 30 Days Of Life

Vizient notes that in the Preliminary Assessment documents for the Proportion of Patients Who Died from Cancer Admitted to the ICU in the Last 30 Days Of Life measure, patients enrolled in a health maintenance organization (HMO) in the 12 months before death are excluded from the population cohort under the denominator section. Vizient requests clarification regarding why this measure excludes only patients enrolled in an HMO, as no explanation is provided in the Preliminary Assessment. Vizient may have more substantive comments depending on the explanation related to HMO patients being excluded.

MUC2024-068: Proportion of Patients who Died from Cancer Receiving Chemotherapy in the last 14 Days of Life

Vizient notes that in the Preliminary Assessment documents for the Proportion of Patients who Died from Cancer Receiving Chemotherapy in the last 14 Days of Life measure, patients enrolled in a health maintenance organization (HMO) in the 12 months before death are excluded from the population cohort under the denominator section. Vizient requests clarification regarding why this measure excludes only patients enrolled in an HMO, as no explanation is provided in the Preliminary Assessment. Vizient may have more substantive comments depending on the explanation related to HMO patients being excluded.

MUC2024-078: Proportion of Patients who Died from Cancer Admitted to Hospice for Less than 3 Days

Vizient notes that in the Preliminary Assessment documents for the Proportion of Patients who Died from Cancer Admitted to Hospice for Less than 3 Days measure, patients enrolled in a health maintenance organization (HMO) in the 12 months before death are excluded from the population cohort under the denominator section. Vizient requests clarification regarding why this measure excludes only patients enrolled in an HMO, as no explanation is provided in the Preliminary Assessment. Vizient may have more substantive comments depending on the explanation related to HMO patients being excluded.

The National Committee for Quality Assurance (NCQA) thanks the Centers for Medicare & Medicaid Services (CMS) and the American Medical Association (AMA) for the opportunity to provide feedback on the ‘Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes’ electronic Clinical Quality Measure (eCQM) for adoption into the Merit-based Incentive Payment System (MIPS). NCQA supports this measure, which addresses the critical topic of early detection and prevention of prediabetes and type 2 diabetes. The measure fills a gap in measurement and aligns with the U.S. Preventive Services Task Force (USPSTF) recommendation for screening every three years in adults aged 35 to 70 years with overweight or obesity.

NCQA is a private, 501(c)(3) not-for-profit, independent organization dedicated to improving health care quality through our Accreditation, clinician quality and measurement programs. We are a national leader in quality oversight and a pioneer in digital quality measurement. Leveraging our strengths as a trusted third party, we are committed to helping organizations navigate their journey toward an equitable, digitally enabled health care system. Our mission to improve the quality of health for all Americans, with an intentional focus on health equity and support for meaningful value-based payment models, propelling our daily work.

Please see the attached letter.

MUC2024-075 Emergency Care Capacity and Quality (ECCQ)

The American Medical Association (AMA) appreciates the development and testing of a measure that addresses a very important issue and believes that this measure will facilitate hospital efforts to improve the care received by patients within the emergency department (ED) setting. We support the revisions that were made to the measure based on public comment during the development process and recommend additional changes that should be considered in the near future. 

We agree with standardizing ED volumes for outcomes 1, 2, and 4; however, we do not believe that outcome 3 should be standardized since hospitals, regardless of the volume, should have an equal opportunity and responsibility to ensure that patients are not kept in the ED longer than necessary.

We also encourage CMS to consider revising this measure in the future to a composite where outcome 3 would be weighted more heavily than the other three outcomes (40% to 20%). This change would enable hospitals and others to evaluate performance across each of the outcomes, while also signaling that boarding times should never be longer than 4 hours. 

We believe that the PRMR recommendation should be “Recommend with Conditions.”

MUC2024-095 Emergency Care Capacity and Quality (ECCQ)

The American Medical Association (AMA) does not support inclusion of this measure in the Rural Emergency (REH) Hospital Quality Reporting Program. REHs have 50 or fewer beds, are required to provide 24-hour emergency and observation services, and can elect to furnish other outpatient services. They cannot have inpatient beds, except those furnished in a distinct part unit licensed as a skilled nursing facility and despite objections from the AMA, a physician is not required to provide the care or oversee the care delivered by non-physician practitioners in an REH. As a result, an REH may have external factors that contributed to extended wait times or boarding outside of its control. For example, they often have trouble finding destination hospitals to accept patients with needs that extend beyond their capabilities and additional time may be needed to transfer the patient to the appropriate facility. 

We believe that the PRMR recommendation should be “Do not Recommend.”

The American Medical Association (AMA) does not support inclusion of this measure in the Rural Emergency (REH) Hospital Quality Reporting Program. REHs have 50 or fewer beds, are required to provide 24-hour emergency and observation services, and can elect to furnish other outpatient services. They cannot have inpatient beds, except those furnished in a distinct part unit licensed as a skilled nursing facility and despite objections from the AMA, a physician is not required to provide the care or oversee the care delivered by non-physician practitioners in an REH. As a result, an REH may have external factors that contributed to extended wait times or boarding outside of its control. For example, they often have trouble finding destination hospitals to accept patients with needs that extend beyond their capabilities and additional time may be needed to transfer the patient to the appropriate facility. 

We believe that the PRMR recommendation should be “Do not Recommend.”

The American Academy of Neurology supports the inclusion of this measure in the MIPS program. The addition of this measure will help provide more meaningful measures for those who care for patients with neurologic disorders.

The American Academy of Neurology supports the inclusion of this measure in the MIPS program. The addition of this measure will help provide more meaningful measures for those who care for patients with neurologic disorders.

The American Academy of Neurology supports the inclusion of this measure in the MIPS program. The addition of this measure will help provide more meaningful measures for those who care for patients with neurologic disorders.

The American Academy of Neurology (AAN) is appreciative of CMS's efforts to develop cost measures relevant to the scope of practice for neurology. 

CMS’s cost improvement methodology is complicated, and the AAN believes that it will be difficult for busy clinicians to understand how to improve on this cost measure and how it drives overall MIPS performance.  

The AAN has concerns about the attribution methodology. Assigning attribution to clinicians who render 30% of the qualifying services is a small percentage to indicate accountability for a patient's total costs during a measurement period. The AAN has additional concerns about the testing data and the low reliability of the measure. We would hope to see much higher reliability for a cost measure that is being proposed for implementation in an accountability program. 

The AAN is concerned this measure will disincentivize clinicians to provide or refer patients for appropriate treatments or testing due to fear of the large costs that will be attributed to them. These concerns were brought up by the expert TEP members in regard to surgical interventions such as deep brain stimulation and intrathecal pumps or disease modifying therapies.

Lastly, the AAN would encourage the measure developer to submit for CBE endorsement before the measure is finalized and approved for implementation in MIPS. It is critical for the CBE committees to review the evidence and methodology to ensure it is reasonable and sound. 

The cost category accounts for a large portion of a participant's score and it is the responsibility of the measure developer and CMS to ensure these measures are well specified and tested. A poorly specified measure could be disastrous for participants and would contribute to financial hardship.

Dr. Tannaz Moin, a physician researcher based at UCLA and VA Greater Los Angeles, 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).

Adoption of this screening measure is critically important and more timely than ever. The CDC estimates that almost 98 million US adults have prediabetes, but we also know that only a fraction are aware that they have the condition.  The USPSTF has emphasize that there is strong evidence to support screening for prediabetes and type 2 diabetes among adults aged 35 to 70 years who have overweight or obesity. Thus, adopting this important measure may help millions of US adults. Screening can help millions of at risk adult become aware of their prediabetes or undiagnosed type 2 diabetes and enable them to engage in evidence-based actions to support their long-term health. Adopting this measure would also 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. Testing of this measure has shown it is both valid and reliable, making it attractive and feasible for diverse health systems to implement. Screening and engagement in risk lowering strategies can help us prevent years of morbidity associated with type 2 diabetes so the time to act is now. Thus, adoption of this measure of screening for prediabetes and undiagnosed type 2 diabetes is critically important for patients, provider, health systems, payors and public health overall.

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