PRMR MUC List

To the Centers for Medicare & Medicaid Services (CMS): 

I support the adoption of 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” in the Hospital Outpatient Quality Reporting Program and Rural Emergency Hospital Quality Reporting Program. This measure is crucial in addressing the timely management of pain during vaso-occlusive episodes (VOEs), a significant challenge in sickle cell disease (SCD) care. Vaso-occlusive episodes in SCD are excruciating and often lead to emergency visits, hospitalization, and prolonged suffering. Timely pain medication alleviates pain, reduces hospital length of stay, and improves patient outcomes. Published data supports a 60-minute benchmark for this measure. The National Heart, Lung, and Blood Institute (NHLBI) recommended pain management for vaso-occlusive crises within 60 minutes of presentation in 2014. ASH endorsed this benchmark in 2020 to improve clinical outcomes for sickle cell disease patients. Several quality improvement (QI) studies support this national benchmark: 

- A 2015 study in Blood found hospitals that met the 60-minute benchmark had shorter hospitalizations and better pain control. 

- A 2019 ACEP project showed timely pain medication administration reduced delayed pain relief and subsequent hospitalizations. 

- A 2020 study in The Journal of Pain and Symptom Management demonstrated a 15% reduction in readmission rates for sickle cell patients who achieved the 60-minute pain medication target. These studies align with expert consensus and emphasize the necessity of adhering to the 60-minute benchmark. Delays in pain treatment can worsen crises, leading to longer stays, higher healthcare costs, and worse outcomes. ASH’s Quality Measure supports this adoption. Given the overwhelming evidence supporting the 60-minute benchmark and its potential to improve patient outcomes, ASH’s quality measure is essential to ensure hospitals and rural emergency healthcare facilities meet the highest standards of care for sickle cell disease patients. Implementing this measure provides hospitals with an evidence-based framework to evaluate performance, identify areas for improvement, and ensure timely and effective care. It will also foster awareness of sickle cell patients’ unique needs and enhance healthcare providers’ training and preparedness to manage pain associated with vaso-occlusive crises effectively. I strongly encourage the Centers for Medicare & Medicaid Services to adopt the ASH quality measure for “Median Time to Pain Medication for Patients with a Diagnosis of Sickle Cell Disease with Vaso-Occlusive Episode” in the Hospital Outpatient Quality Reporting Program and the Rural Emergency Hospital Quality Reporting Program. This measure, grounded in solid scientific evidence and expert consensus, will significantly improve the quality of care for sickle cell disease patients nationwide. Thank you for considering this important issue. 

Respectfully,

W. Andrés Vásconez-Samaniego, MD.

The problem with just using the time factor for administration of pain medication is concerning. ED providers seeing the patient are not always familiar with prior clinical course of the patient. They need a bit of time to complete their assessment and to determine if this is VOC vs acute on chronic pain, or if patient has hypertension or renal disease ( relative contraindication for iv ketorolac). By putting pressure on the ED  providers to give pain medication ASAP, we are circumventing the process of assessment and plan. A better approach could be rapid triage and assessment of patients with SCD presenting to ED presenting with pain. 

I applaud having a measure for timeliness of treatment for sickle cell pain. Please note, however, that the QUALITY of treatment is also important, and the best practices would be:

1. rapid appropriate assessment that this is sickle cell pain and not another medical problem
2. using an individualized pain plan or weight-based dosing of pain medications, 

3. following guidelines from American College of Emergency Physicians and American Society of Hematology                                                               

                      Sickle Cell | ACEP   

    

   American Society of Hematology 2020 guidelines for sickle cell disease: management of acute and chronic pain | Blood Advances | American Society of Hematology

I am writing to support 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” in the Hospital Outpatient Quality Reporting Program and Rural Emergency Hospital Quality Reporting Program.   As a pediatric hematologist, I have witnessed firsthand the severe pain episodes, known as vaso-occlusive crises, that these patients endure. Prompt and effective pain management is not just a matter of comfort; it is a crucial aspect of their care that can significantly impact their overall health outcomes. These pain episodes often require immediate medical attention, and delays in treatment can exacerbate the situation, leading to prolonged hospital stays and increased risk of complications.

The National Institutes of Health (NIH) and the American Society of Hematology (ASH) recommend that patients with sickle cell disease receive prompt pain management upon presentation to the emergency department. Implementing protocols to achieve this can significantly reduce the duration and severity of pain episodes, minimize the risk of acute chest syndrome, and improve patient satisfaction and quality of life.

Best practices to achieve this would include:

1. Implement Rapid Triage Protocols: Ensure that patients with sickle cell disease are quickly identified and triaged to receive timely pain assessments and interventions.

2. Educate Staff: Provide regular training for all emergency department personnel on the unique needs of sickle cell patients and the importance of timely pain management.

3. Streamline Pain Management Processes: Develop and utilize standardized order sets for pain management that facilitate rapid medication administration.

4. Continuously Evaluate and Improve: Regularly review treatment protocols and patient outcomes to identify areas for improvement and ensure adherence to best practice guidelines.

Timely intervention is crucial in managing sickle cell crises effectively. By working together to address these needs, we can enhance the care and support we provide to our patients, reducing their pain and improving their overall health outcomes.

I agree that this rule establishes a bare minimum comparative metric. It will take much more than rapid administration of "a dose of pain medication" to provide excellent care in the emergency department, but this initial measure will provide an explicit report that something is being done, and how long it takes. The definition of acceptable pain medication is quite broad and allows for personalization and flexibility, and implicit in the idea of 'medication administration' is the idea that someone was appropriately triaged and received the most appropriate medication for their situation. We cannot assess these aspects of care delivery with this metric, but this is an appropriate starting point.

I strongly support the adoption of the American Society of Hematology’s (ASH) new quality measure, “Median Time to Pain Medication for Patients with Sickle Cell Disease with Vaso-Occlusive Episode,” in the Hospital Outpatient Quality Reporting Program and Rural Emergency Hospital Quality Reporting Program.

Timely pain management is a critical component of care for individuals with sickle cell disease (SCD) experiencing vaso-occlusive episodes (VOEs). Delayed treatment not only prolongs patient suffering but also increases the risk of complications, including hospital admissions and longer recovery times; ultimately increasing health care resource utilization overall. By tracking and improving the median time to pain medication, this measure prioritizes evidence-based, patient-centered care, ultimately leading to better clinical outcomes.

Additionally, the implementation of this measure addresses longstanding disparities in SCD care, as patients with SCD—many of whom belong to historically underserved populations—often face stigmatization and inadequate treatment in healthcare settings. This measure promotes health equity by establishing accountability and standardizing care for a condition that disproportionately impacts marginalized communities.

Incorporating this measure into quality reporting programs is a vital step toward ensuring that all patients with SCD receive timely, equitable, and effective care. This initiative underscores the importance of aligning healthcare practices with the principles of justice, equity, and evidence-based care.

It is IMPERATIVE that individuals with SCD receive pain medication within 60 min of arrival to the ED to optimize pain management and potentially reduce hospital admissions. Beyond this first level of treatment, healthcare systems need to focus on standardizing inpt pain management AND individualizing pain management with input from patients, families, and providers. 

I endorse sickle cell  guidelines from ASH providing early less than 1 h pain management for patients with sickle cell disease in the ED admitted with Vasoocclusive crisis

One thing to note is that I would suggest the ‘home safety’ question not refer to the beginning of care only.  Just as in the medication proposed question, it should refer to during care under the agency did team members discuss home safety with you.   

Hello,

I am a pediatric hematologist at a large freestanding children's hospital in Houston, Texas. The sickle cell program at our center provides care to over 1200 infants, children, and adolescents with sickle cell disease. I write to provide my strong support for the adaption of this new measure that aims to improve the care provided to individuals with sickle cell disease. A metric that addresses timely pain medication administration to individuals with sickle cell disease would allow for a critically important patient outcome to be recognized and tracked. I acknowledge that some advocates argue against the measure due to its lack of specificity around the type of medication administered (i.e. does no specify opioid administration). However, I believe that by including this measure as written, it will allow for both buy in from a key stakeholder (Emergency Department providers) and consistent tracking and monitoring of pain medication administration for the first time. Doing so would provide solid data from which to build upon in the effort toward more equitable care for these patients. I applaud the team that worked to develop and validate the measure. 

Thank you.

This metric is very concerning and allows for emergency rooms to utilize non opioid therapy such as ibuprofen and acetaminophen as first line. I am very concerned this will not make meaningful change and allow for emergency rooms to just treat initially with ibuprofen or acetaminophen.  Acetaminophen and ibuprofen are not only ineffective for the management of acute vaso-occulsive event (VOE) but also could be dangerous and contraindicated in people with renal and liver disease.  Opioids are the standard for the management of acute VOE based on the NHLBI Guidelines and ASH 2020 sickle cell guidelines. I am highly concerned that this metric not only falls short but could delay the first dosage of opioid and could be dangerous.

I write to support the adoption of the Equity of Emergency Care Capacity and Quality (ECCQ) measure. The emergency department (ED) represents the safety net for patient care in this country, and is often the only point of access for some of our most disadvantaged patients. Emergency departments are required under EMTALA to provide a medical screening exam and stabilizing treatment, but too often now the emergency department is not an environmen that is conducive to providing quality care or to long term staff longevity. This is in particular because hospitals are boarding admitted patients in the ED, limiting available space for care provision. There is strong evidence that this compromises patient care, increases staff burnout, and promotes workplace violence. It is essential that there is a quality measure that ensures these patients are evaluated reasonably promptly and do not remain in the ED longer than necessary, particularly after the decision to admit.

This measure represents a critical step forward in addressing the diabetes epidemic. Incentivizing providers to screen for abnormal glucose levels among high-risk adults aged 35–70 is evidence-based and will likely lead to earlier diagnoses and better management of prediabetes and type 2 diabetes. I strongly support its inclusion in MIPS.

However, I urge CMS to prioritize equitable implementation of this measure to ensure that populations disproportionately affected by diabetes, including racial and ethnic minorities, are effectively reached. This could involve providing guidance on culturally tailored outreach and screening strategies.

Additionally, I encourage future efforts to expand screening measures to include populations not currently covered, such as younger individuals and those without overweight or obesity, to broaden early intervention opportunities.

Finally, I recommend that CMS address potential implementation challenges, such as reducing provider burden and improving access to care in underserved communities, to ensure the measure achieves its intended impact without exacerbating existing disparities.

Please find attached ViiV Healthcare Company’s comments on the Partnership for Quality Measurement (PQM) Pre-Rulemaking Measure Review (PRMR) Measures Under Consideration, encouraging the development and adoption of additional HIV measures.

As a clinical associate professor and medical director in the department of community health and family medicine at the University of Florida, 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. 

I believe that screening for abnormal glucose is an important preventive service and is reasonable to include in accountability programs. The benefit of the measures at our institution would include incorporating it as a quality measure in the health maintenance section of our EHR uso that all primary care clinicians can use the measure to prevent diabetes and its complications for countless of our patients.

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’m 

Good morning.  I am a Diabetes Prevention Program (PreventT2) Lifestyle Coach.  I am in support of the CMS Merit-based Incentive Payment System (MIPS).  A large portion of the individuals who reach out to me to join the DPP program have done so by taking their own initiative, not necessarily their medical provider's recommendation.  I track this measure myself with every Intake.  MIPS would also prioritize clinical orders for A1c levels.  Given that I work in a health system I have access to patient's charts.  In many cases, patients routinely have bloodwork done that doesn't include an A1c.  I've attempted to increase provider awareness and facilitate referrals by implementing a "quick" order for the DPP program.  The "quick order" is in plain view, in all patient charts, and just needs to be clicked by the provider to send a referral to me.  I do everything from there.  It is unfortunate that even though I've created the simplest method possible to refer a patient to the DPP program, it isn't used.  I've worked in numerous  settings throughout my 30-year career in the health care service industry.  Implementation of quality measures / MIPS will not only motivate providers, but it will also increase awareness of the leadership of the health systems they work for (if they are not in an independent practice).  The health systems have their own quality measures: decreased hospitalizations, visits to the ED, etc. that are tied to reimbursement and available for the public to see.  Early action to prevent T2 diabetes can improve outcomes for the health systems by avoiding other quality measures associated due to co-morbidities associated with T2.  My hope for our community is that MIPS will be passed.  They are desperate for more education about lifestyle changes they can make to prevent T2, however, they need to know they have a diagnosis of prediabetes to make that happen.  If I can be of further assistance, please feel free to contact me directly.      

Social Need Screening Interventions:

1. Screening tools: Standardized questionnaires, such as the PRAPARE (Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences) tool, to identify social needs.

2. Community resource connections: Linking individuals with local resources, such as food banks, housing assistance, and employment services.

3. Care coordination: Coordinating care with healthcare providers, social workers, and community organizations to address social needs.

4. Patient navigation: Providing personalized support and guidance to help individuals navigate the healthcare system and access community resources.

5. Health education: Educating individuals on healthy behaviors, disease management, and self-care to empower them to take control of their health.

Implementation Considerations:

1. Integration with existing workflows: Incorporate social need screening into routine clinical workflows.

2. Training for healthcare providers: Educate providers on the importance of social need screening and how to use screening tools.

3. Community partnerships: Establish partnerships with local community organizations to provide resources and services.

4. Data collection and evaluation: Collect data on social need screening outcomes and evaluate the effectiveness of interventions.

The number of individuals with diabetes and prediabetes continues to climb in the United States. It is estimated that approximately 98 million American adults have prediabetes, with more than 80% of them not being aware that they have this disease, and approximately 23% of adults with diabetes go undiagnosed.  It is a disease that causes many complications and death yet can be prevented and reversed if individuals are made aware, by screening/ a simple lab test, that they have the disease and are taught how to treat the condition and change their lifestyle.   Please add screening measures for abnormal glucose to the CMS Merit-based Incentive Payment System so that more people will be aware of their condition. I teach classes for individuals who have been diagnosed with prediabetes and have seen firsthand how they have lowered their A1C levels by learning how to make lifestyle changes by implementing healthier habits. But they would not have seen their need for such a class or these changes without having been screened by their primary care provider.

The AHA does not support use of this measure in the Hospital VBP program—neither the original version currently used in the IQR nor the revised measure under consideration in this cycle. As we have noted across comments to CMS, bolstering and accelerating progress on patient safety is a top priority for America’s hospitals and health systems, and one that we share with CMS. Yet, this structural measure overlaps extensively with multiple CMS Conditions of Participation, and several of the included practices lack a strong evidence base linking their implementation to better care and outcomes. In adopting the previous version of the measure, CMS dismissed these concerns and expressed confidence that the measure’s use would lead to better outcomes. Yet, the measure has not even been implemented in hospitals yet – the first data on the prior version of this measure will not be submitted to CMS until mid-2026. As a result, we do not have any evidence to suggest that the use of this measure has led or will lead to better care. In fact, in the time since CMS has adopted this measure, hospitals have expressed considerable confusion about what CMS means by the attestation statements included in the measure and have not found the attestation guide CMS developed helpful in resolving that confusion.

Notwithstanding the considerable concerns with the measure in its current form, CMS proposes to change the measure and add two attestation statements related to drug shortages. To be sure, we share the agency’s goal of ensuring a more resilient health care supply chain and recognize that supply chain disruptions have the potential to significantly impact patients, families and hospitals. Unfortunately, the two proposed attestations reflect a fundamental misunderstanding of how the drug supply chain functions and could inadvertently entrench contracting practices that make it more challenging to strengthen the pharmaceutical supply chain. For example, the attestation focused on multi-year contracting with volume guarantees and “strict failure to supply clauses” seemingly ignores the fact that multi-year contracts can in practice make it more costly or impractical to move away from an underperforming supplier. It also ignores the fact that volume guarantees would be difficult – and perhaps not even desirable – to enforce because nearly all distributors revert to the use of an allocation system in the event of shortages. That allocation system is designed to ensure the continued availability of limited product for as many customers as possible by reducing the volume delivered to individual customers. Lastly, CMS does not sufficiently define their term “strict failure to supply clauses.” 

These two new attestations also seemingly misplace the accountability for making the drug production supply chain more resilient with hospitals. In fact, shortages are a complex challenge that requires the implementation of evidence-based solutions across multiple stakeholders to resolve. These two attestations alone would not only be ineffectual but potentially detrimental to these efforts. The fact that this revised measure has not even undergone testing for face validity, let alone reliability or feasibility, without input from a technical expert panel or any stakeholders, calls into question whether this measure can provide useful information on patient safety.

Lastly, with respect to implementation in the VBP, we continue to note that tying hospital performance and payment to participation in a Patient Safety Organization is likely inconsistent with the intent of the Patient Safety and Quality Improvement Act of 2005. The PSQIA explicitly made hospital participation in PSOs voluntary. Tying this measure to VBP performance would create a de facto mandate to participate in PSOs. We continue to urge CMS to remove this attestation from the current version of the Patient Safety Measure and any subsequent updates to it.

The AHA has several questions and potential concerns regarding the use of this End-of-Life measure in the IQR. While we understand the rationale behind reducing unnecessary services at the end of life, this particular measure may not sufficiently take important context into account. Most glaringly, a claims-based measure would be unable to account for patient and family preference. Further, there are times when a patient may be admitted to the ICU in the wide, 30-day window for reasons that are entirely clinically appropriate, and it is unclear whether and how CMS considered this in the measure design. In addition, we question whether the attribution strategy would adequately define the relationship between a patient with cancer and a hospital directing the patient’s care at the end of life.

The AHA does not support the use of this measure in CMS programs. It suffers from several conceptual and logistical flaws that would make it fundamentally unworkable without any benefit to patient outcomes. We understand that CMS is looking to expand beyond the already adopted screening measures to determine the extent to which providers are able to not only identify health-related social needs, but also address them. However, this measure is inconsistent with the social driver of health screening measures currently used in CMS programs and would complicate (and likely stymie) any progress made in this area. For example, this proposed measure does not include interpersonal risk as a social driver while the current IQR and OQR measures do. The measure would pose significant feasibility challenges due to data element requirements and EHR field methodology. Specifically, CMS would require the use of screening tools that conform to specific technical specifications, a marked departure from the flexibility CMS has provided to hospitals under the current SDOH screening measures that enable them to choose screening tools that fit their patients, systems and processes the best.

In addition to these technical concerns, we foresee significant challenges in using this measure to assess hospital performance. Social needs are not uniformly distributed across the country, and there is wide variation in community and state/federal resources that would be available to support the included qualifying follow-up actions. As a result, being able to deliver on follow up actions could simply be inherently more difficult for some hospitals than others, and could lead to performance variation that does not have anything to do with the care the hospital delivers. Indeed, the supporting documentation suggests that 9 out of 14 TEP were neutral or disagreed that the measure could differentiate good performance from poor performance.  These issues all raise questions about whether this measure would meaningfully advance how hospitals, patients and communities work together to identify and address health-related social needs.

The AHA hopes that the measure developer and Battelle staff may be able to answer some questions regarding this measure prior to the Recommendation meeting. First, the specifications note that this measure is intended to be paired with the “Hospital Harm: Postoperative VTE” measure, but that measure is not currently used in the IQR nor is it on the MUC list. We request clarification on this approach—that is, if the measure is intended to be used in tandem with another, why is only one measure being considered? Would the two measures be considered “balancing” measures to address the potential unintended consequence of subsequent underdosing of anticoagulants and thrombolytics? If so, is there evidence to demonstrate that this approach has the intended effects? 

Second, the measure developer noted that they are currently subjecting the measure to risk adjustment and stratification approaches, with the intent to assess whether changes should be made to the program in future years. We hope that part of this analysis includes stratification across various patient subgroups, including those related to social drivers of health; we ask why that analysis was not performed prior to this measure coming under consideration, as would be consistent with CMS’s Universal Foundation strategy.

The AHA does not support the use of this measure in the OQR or REHQR. The measure suffers from several logistical and conceptual flaws and would not be an effective step in improving ED efficiency and reducing excessive boarding. Technically, we note the overlap with two measures currently used in the OQR (OP-18 and OP-22) and note that the loss of CBE endorsement of (and host of other issues with) those measures suggest that ED throughput is not a well-defined and useful concept for quality measurement. Further, supporting documentation notes concerns with facilities not reporting standardized terminology related to patient placement. The measure developer suggests that stratifying the measure by age and principal diagnosis of a mental health condition and potentially by other factors would provide better insight into performance; however, this analysis has not been done and no stratification methodology is suggested for this measure, and thus as proposed it provides very little useful information.

Conceptually, the measure’s specifications provide an uninformed, narrow and idealized understanding of how EDs operate, and appear to assume that EDs operate in a vacuum rather than as part of a larger and more complex hospital care continuum. Using these apparently arbitrary time windows to determine appropriate access assumes that the rest of the system is able to accommodate ED volume, when in reality other parts of the hospital (such as ICUs) do not make care decisions based on ED throughput times but rather based on patient clinical needs. Differences in case mix will result in unfair comparisons between facilities that have high volumes of trauma patients or patients being seen for behavioral health conditions, where treatment and/or transfer to the appropriate care setting might take longer through not deficiency of the ED. The preliminary analysis does not point to any evidence-based guidelines on how to improve performance on this measure, indicating that there is no clear line between particular actions the hospital should take and improved outcomes. For these reasons, this measure is not appropriate for use in CMS quality measurement programs.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HAC program, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HAC penalties are calculated based on a hospital’s ranking in performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could lead to significant changes in the distribution of scores, and as a result, in the penalties that hospitals incur under the HAC Reduction program. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HAC program and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

As the AHA understands it, CMS included this updated measure on the MUC list because it intends to include Medicare Advantage beneficiaries in the denominator. However, it is unclear from the supporting documentation whether any analysis has been done to determine the implications of including these beneficiaries for the outcomes of the HRRP, and testing has only been conducted with a single year of data. While MA beneficiaries are increasing as a proportion of total Medicare enrollees nationally, MA market penetration and specifics of enrollee makeup still varies widely. Because HRRP payment adjustments are calculated based on the distribution of all participating hospitals’ performance on measures within the program for Medicare Fee-for-Service beneficiaries, the inclusion of MA beneficiaries in this calculation could mean significant changes in the distribution of scores, and as a result, in the penalties hospitals experience under the HRRP. We hope that the measure developer can provide additional insight into how this significant change to the measure’s specifications would impact the HRRP and the hospitals that participate in it.

The AHA is concerned by the increasing burden on patients due to the ever-growing list of provider survey questions they are being asked to answer. While hospitals and health systems deeply value the patient perspective and use data from patient experience and PRO-PMs to make care safer, higher quality and more equitable, these measures also require patients to provide a significant amount of information. Often, this process is redundant or overlapping. With the recent adoption of the PRO-PM for THA/TKA in the ASCQR and the OAS CAHPS survey (both of which are voluntarily reported today), in addition to individual CAHPS clinician surveys, we worry that CMS’ plans to rely upon patients for an increasing amount of data production would affect survey response rates across the board and lead to confusion among patients about what aspect of care they are being asked to assess. We continue to believe that the administration timeline of the survey informing the measure under consideration overlaps with that of other ASC patient experience surveys.

In addition, the measure suffers from the same conceptual disadvantages as its OQR counterpart—namely, that while the name of the measure suggests that its purpose is to evaluate the clarity of clinical information provided by evaluating the patient’s level of understanding of that clinical information. These are two disparate items that, while related, are not necessarily captured by this measure. In other words, this measure does not evaluate the quality of information provided to the patient, but rather the patient’s ability to comprehend it; PRO-PMs are inherently subjective, but this topic (i.e. clarity of information provided) can be, and is, assessed objectively using other measures (such as the Transfer of Health Information to the Patient measure used in post-acute care quality reporting programs, which assesses the content and timeliness of medication profiles provided to the patient at discharge).

Depending on the questions that are within the survey the information included could be used to help measure and improve quality outcomes. Question to determine how quickly the HHA opened a case, if selections were given, services offered, time spent in the home, if assistance with medication was offered, and if they were overall satisfied with the care received would be helpful. From a long-term care perspective if a number of these areas are missed a poor-quality outcome is likely. The exclusions make sense.  Questions pertaining to ability to pay bills, get to appointments, access to food, and support would be helpful for equality-based quality improvement. A survey can ask a patient if they feel that the HHA helped take care of their health, but I think that there is a lot of questions that could be asked that could collect data that could allow to see if things were done by the HHA that would allow for a great outcome from the patient perspective. 

To the Partnership for Quality Measurement’s Pre-Rulemaking Review Committee and the Centers for Medicare & Medicaid Services:

On behalf of over 39,000 orthopaedic surgeons and residents represented by the American Association of Orthopaedic Surgeons (AAOS), we appreciate the opportunity to comment on several of the measures on the Centers for Medicare & Medicaid Services’ (CMS) 2024 Measures Under Consideration (MUC) list. AAOS members and their patients are specifically impacted by five of the measures under consideration for CMS quality reporting programs. 

Please see the attached letter for our comments on this measure.

To the Partnership for Quality Measurement’s Pre-Rulemaking Review Committee and the Centers for Medicare & Medicaid Services:

On behalf of over 39,000 orthopaedic surgeons and residents represented by the American Association of Orthopaedic Surgeons (AAOS), we appreciate the opportunity to comment on several of the measures on the Centers for Medicare & Medicaid Services’ (CMS) 2024 Measures Under Consideration (MUC) list. AAOS members and their patients are specifically impacted by five of the measures under consideration for CMS quality reporting programs. 

Please see the attached letter for our comments on this measure.

To the Partnership for Quality Measurement’s Pre-Rulemaking Review Committee and the Centers for Medicare & Medicaid Services:

On behalf of over 39,000 orthopaedic surgeons and residents represented by the American Association of Orthopaedic Surgeons (AAOS), we appreciate the opportunity to comment on several of the measures on the Centers for Medicare & Medicaid Services’ (CMS) 2024 Measures Under Consideration (MUC) list. AAOS members and their patients are specifically impacted by five of the measures under consideration for CMS quality reporting programs. 

Please see the attached letter for our comments on this measure.

To the Partnership for Quality Measurement’s Pre-Rulemaking Review Committee and the Centers for Medicare & Medicaid Services:

On behalf of over 39,000 orthopaedic surgeons and residents represented by the American Association of Orthopaedic Surgeons (AAOS), we appreciate the opportunity to comment on several of the measures on the Centers for Medicare & Medicaid Services’ (CMS) 2024 Measures Under Consideration (MUC) list. AAOS members and their patients are specifically impacted by five of the measures under consideration for CMS quality reporting programs. 

Please see the attached letter for our comments on this measure.

To the Partnership for Quality Measurement’s Pre-Rulemaking Review Committee and the Centers for Medicare & Medicaid Services:

On behalf of over 39,000 orthopaedic surgeons and residents represented by the American Association of Orthopaedic Surgeons (AAOS), we appreciate the opportunity to comment on several of the measures on the Centers for Medicare & Medicaid Services’ (CMS) 2024 Measures Under Consideration (MUC) list. AAOS members and their patients are specifically impacted by five of the measures under consideration for CMS quality reporting programs. 

Please see the attached letter for our comments on this measure.

Comments in support of MUC2024-028 Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes

To CMS: Thank you for giving me the opportunity to deliver my remarks today, Dec. 17, 2024. I have attached a PDF of these comments.

Katie Adamson, Co-Chair, Diabetes Advocacy Alliance

I wanted to comment on the importance of the measure "Screening for Abnormal Glucose Metabolism in Patients at Risk of Developing Diabetes". The US Preventive Services Task Force has recommended screening and treatment of prediabetes as a strategy to prevent the development of diabetes for several years. Further, the Healthy People objectives (D-02) include an objective to reduce the proportion of adults who don't know they have prediabetes. Unfortunately, our studies have indicated that clinicians and the health system are not following this guidance (Mainous, 2022; Mainous 2016). Not only do nearly 40% of adults who meet the criteria to be screened are not screened but we have found that of those who screen positive only 5% were actually treated. Further, physician attitudes play a large role in screening and treatment of prediabetes. I have argued that the incentives are misaligned in the health care system where we incentivize diabetes management but not diabetes prevention (Mainous, 2020). I believe that adding this measure to the MIPS will be a great step in aligning incentives to diabetes prevention.

Mainous AG 3rd, Tanner RJ, Scuderi CB, Porter M, Carek PJ. Prediabetes Screening and Treatment in Diabetes Prevention: The Impact of Physician Attitudes. J Am Board Fam Med. 2016 Nov 12;29(6):663-671. doi: 10.3122/jabfm.2016.06.160138. 

Mainous AG 3rd, Yadav S, Xie Z, Huo J. Cost or revenue: is diabetes prevention doomed due to misalignment of incentives? Fam Med Community Health. 2020 Jan 19;8(1):e000274. doi: 10.1136/fmch-2019-000274. 

Mainous AG 3rd, Rooks BJ, Wright RU, Sumfest JM, Carek PJ. Diabetes Prevention in a U.S. Healthcare System: A Portrait of Missed Opportunities. Am J Prev Med. 2022 Jan;62(1):50-56. doi: 10.1016/j.amepre.2021.06.018. 

Valley Medical Center 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. 

Valley Medical Center 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.

We are writing today to express our strong support for ensuring that measures that screen beneficiaries for social needs and interventions, such as MUC2024-052, the Social Need Screening and Intervention Measure, are aligned across federal programs. The adoption of the SNS-E measure supports the regulatory requirements for MA plans around coordination with community and social services and could help to better serve at-risk beneficiaries.

Evidence suggests that systematic screening of health-related social needs – similar to what is required by this proposed measure – is essential to ensure that health plans are accountable for both identifying members with the greatest social risk and ensuring those members secure an appropriate intervention, including relevant SDOH supplemental benefits, connections to community resources, and/or enrollment in SNAP, WIC, LIHEAP, and other programs.

The inclusion of utilities insecurity and interpersonal/violence safety screening and intervention rates to the SNS-E measure is critical, especially in light of studies that show the association between utility insecurity and health outcomes and interpersonal safety’s direct association with injury, psychological distress, and death in all age groups.

The Commonwealth Fund looks forward to continuing to work with CMS to advance evidence-based measures to help meet the social needs of beneficiaries enrolled in Medicare Advantage.

Thank you for your consideration and your commitment to advancing the health of all Americans.
 

Rachel Nuzum

Senior Vice President for Policy

The Commonwealth Fund

Melinda Abrams

Executive Vice President for Programs

The Commonwealth Fund

I am a nurse scientist focusing my work on people living with Sickle Cell Disease. Pain continues to be a significant problem for this group of patients, particularly time to administration of pain medication, which is a critical aspect of care for this population. Evidence is clear that this  disparity continues, in addition to causing delays in managing pain, this issue also influences patient and family decision making in seeking future care and in their trust of the healthcare system. I fully support incorporating this measure because it would provide a significant opportunity to improve care.

As a director of an adult sickle cell program, prior quality director with implementation in time to pain medication, and a member of the American Society of Hematology Technical expertise group, I strongly support this measure and efforts to improve sickle cell care.  While I would want to ensure assistance for implementation for any programs that seek the support and ensure adequate tracking of the metric, I think this is significant first step to evaluating equity of care for patients with sickle cell disease. 

It is gratifying to see this quality measure for ED care for sickle cell disease. As a pedi ED attending and researcher in this area for 15+ years, working to improve ED care for children and adults with SCD, collecting this data is a significant step to understanding the health care system performance for adults and children with SCD. Although median time to pain medication is only 1 facet of ED care, it will be helpful to know that status of ED care currently. From the CMS listening session today, I learned that pain medication data will be stratified into parenteral opioid medications, oral pain medications, and other pain medications (such as ketamine, etc), which has alleviated my biggest concern - that we would not understand if the patients are receiving guideline-adherent care, i.e., parenteral opioids as their first pain medication. 

Addition comments/suggestions I would like to share are:

1.  Dissemination of the ASH guidelines with this measure will be critical, to help educate ED clinicians that parenteral opioids are recommended as first-line therapy for most patients with SCD. For a small minority, oral pain medications are appropriate, per their individualized pain plan developed by their hematologist. 

2.  ASH/other data stewards should  receive data on at least a quarterly basis, if not monthly, as this information would be extremely helpful for the research and advocacy communities to know what current median times for pain medication administration are, and what medications are most commonly administered first. (for EDs with low volumes of patients with SCD, annual reporting may be be more appropriate)

            2a. It will be important to see the % of patients who receive parenteral opioids as their first pain medication vs the % of patients who receive non-parenteral opioids as first pain medication.  We would expect to that most patients with SCD receive parenteral opioids first, and a small % of patients receive non-parenteral opioids (they may account for a significant proportion of ED visits).

            2b. Stratifying the data for adults vs. children is also important to understanding the differences in care provided by age.

Thank you for considering these comments and suggestions. And thank you for creating this measure for consideration, which is critical to improving ED care for those with SCD experiencing painful VOE, and strengthened by these comments and those given below. 

MUC2024-027 Patient Safety Structural Measure

While the American Medical Association (AMA) supports the ongoing focus of improving patient safety, including targeting a hospital’s leadership and the entity’s overall structure and practices, we continue to believe that leveraging a structural measure, particularly one that primarily looks for the presence of patient safety-focused documents, in the absence of any demonstrated linkage to improvement in patient outcomes should not be pursued. 

Based on our review of the preliminary assessment, CMS did not provide any justification on why two new attestation statements were needed in Domain 2, and we do not support further increasing the complexity of this measure. As stated previously, we believe that there are many activities already integrated into a hospital’s structures and processes including actively engaging patients and families in activities such as a Patient and Family Advisory Council, reporting to a Patient Safety Organization, participating in large-scale learning networks, and tracking progress on safety metrics against external benchmarks. As a result, reporting on this measure will likely lead to overall high performance quickly and it remains unclear the extent to which attesting to these domains has a direct link in increasing the quality and safety of the care delivered within a hospital. 

We again encourage CMS to shift focus from developing this type of measure and target those measures, initiatives, and activities that prioritize the collection and reporting of additional relevant safety data and promote interventions that address them. 

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

MUC2024-030 Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) 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 and limited ability to distinguish better versus worse performers. Testing demonstrated that reliability is 0.159 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.

In addition, we question whether the measure continues to be useful to distinguish hospital performance and drive improvements based on the distribution of hospital’s performance scores where only 8 performed better than the national rate and 13 were worse with 98.9% of the 1,874 hospitals performing no different than the national rate.  

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

MUC2024-040 Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Chronic Obstructive Pulmonary Disease (COPD) 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 and limited ability to distinguish better versus worse performers. Testing demonstrated that reliability is 0.143 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), which the developer was unable achieve until the 10^th decile for this measure. 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.

In addition, we question whether the measure continues to be useful to distinguish hospital performance and drive improvements based on the distribution of hospital’s performance scores where only 1 performed better than the national rate and 17 were worse with 99.3% of the 2,739 hospitals performing no different than the national rate.  

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

MUC2024-041 Hospital-Level 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Elective Primary Total Hip (Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) 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 and limited ability to distinguish better versus worse performers. Testing demonstrated that reliability is 0.361 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.

In addition, we question whether the measure continues to be useful to distinguish hospital performance and drive improvements based on the distribution of hospital’s performance scores where only 29 performed better than the national rate and 5 were worse with 98.1% of the 1,828 hospitals performing no different than the national rate.  

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

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 and limited ability to distinguish better versus worse performers. Testing demonstrated that reliability is 0.302 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. 

In addition, we question whether the measure continues to be useful to distinguish hospital performance and drive improvements based on the distribution of hospital’s performance scores where only 2 performed better than the national rate and 3 were worse with 99.4% of the 893 hospitals performing no different than the national rate.  

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

MUC2024-032 Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following Heart Failure (HF) 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 0.102 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”