Percentage of patient months of pediatric (< 18 years old) in-center hemodialysis patients (irrespective of frequency of dialysis) with documented monthly nPCR measurements.
Measure Specs
General Information
For in-center hemodialysis patients, nPCR provides an estimate of dietary protein intake, which has been shown to provide additional information to spKt/V. Studies have shown that in adolescent patients who achieved target spKt/V levels, nPCR was associated with nutritional status. Furthermore, there is evidence that nPCR < 1 gram/kg/day is predictive of malnutrition and sustained weight loss among adolescent patients.
EQRS is the primary basis for placing patients at dialysis facilities and dialysis claims are used as an additional source. Information regarding first ESRD service date, death, age and incident comorbidities adjustments and transplant is obtained from EQRS (including the CMS Medical Evidence Form (Form CMS-2728) and the Death Notification Form (Form CMS-2746)) and Medicare claims, as well as the Organ Procurement and Transplant Network (OPTN) and the Social Security Death Master File.
Numerator
Number of patient months in the denominator with monthly nPCR measurements.
The number of patients in the study month where (1) the nPCR value and the date the nPCR value was collected are reported or (2) the following 7 components used to calculate nPCR are reported (BUN pre-dialysis, BUN post-dialysis, pre-dialysis weight, pre-dialysis weight unit of measure, post-dialysis weight, post-dialysis weight unit of measure, delivered minutes of BUN hemodialysis session), and the date of collection.
Note: Interdialytic time is also needed to calculate nPCR; however, EQRS currently does not allow collection of that data element therefore the measure does not require reporting of this variable.
Denominator
Number of all patient months for pediatric (less than 18 years old) in-center hemodialysis patients (irrespective of frequency of dialysis).
A treatment history file is the data source for the denominator calculation used for the analyses supporting this submission. This file provides a complete history of the status, location, and dialysis treatment modality of an ESRD patient from the date of the first ESRD service until the patient dies or the data collection cutoff date is reached. For each patient, a new record is created each time he/she changes facility or treatment modality. Each record represents a time period associated with a specific modality and dialysis facility. EQRS is the primary basis for placing patients at dialysis facilities and dialysis claims are used as an additional source of information in certain situations. Information regarding first ESRD service date, death, and transplant is obtained from EQRS (including the CMS Medical Evidence Form (Form CMS-2728) and the Death Notification Form (Form CMS-2746)) and Medicare claims, as well as the Organ Procurement and Transplant Network (OPTN).
Exclusions
Exclusions that are implicit in the denominator definition include adult patients (greater than or equal to 18 years of age), all patients who have not been in the facility for the entire reporting month, and all home hemodialysis and peritoneal dialysis patients. There are no additional exclusions for this measure.
There are no additional or explicit exclusions beyond what is embedded in the denominator's definition.
Measure Calculation
To be included in the denominator for a particular month, the patient must be on in-center hemodialysis for the entire month, must be < 18 years old at the beginning of the month, and must be assigned to that facility for the entire month. An individual patient may contribute up to 12 patient-months per year.
The numerator counts the number of patients in the study month where (1) the nPCR value and the date the nPCR value was collected are reported or (2) the components that allow calculation of nPCR are reported (BUN pre-dialysis, BUN post-dialysis, pre-dialysis weight, pre-dialysis weight unit of measure, post-dialysis weight, post-dialysis weight unit of measure, delivered minutes of BUN hemodialysis Session and the date of collection).
Note: Interdialytic time is also needed to calculate nPCR; however, EQRS currently does not allow collection of that data element, therefore the measure does not require reporting of that variable.
The measure is not stratified.
Public reporting of this measure on DFCC would be restricted to facilities with at least 11 eligible patients for the measure to comply with restrictions on reporting of potentially patient identifiable information related to small cell size. We have applied this restriction to all the reliability and validity testing reported here.
Point of Contact
N/A
Wil Agbenyikey
7500 Security Boulevard
Woodlawn, MD 21244
United States
United States
Importance
Evidence
The primary source of evidence for this measure is the KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for 2006 Updates: Hemodialysis Adequacy, Peritoneal Dialysis Adequacy and Vascular Access.
The guideline states:
“8.2.2 Assessment of nutrition status is an essential component of HD adequacy measurement. nPCR should be measured monthly by using either formal urea kinetic modeling or algebraic approximation. (B)
2008 KDOQI CPR RECOMMENDATION 1: EVALUATION OF GROWTH AND NUTRITIONAL STATUS
1.1 The nutritional status and growth of all children with CKD stages 2 to 5 and 5D should be evaluated on a periodic basis. (A)
1.2 The following parameters of nutritional status and growth should be considered in combination for
evaluation in children with CKD stages 2 to 5 and 5D. (B)
- Dietary intake (3-day diet record or three 24-hour dietary recalls)
- Length- or height-for-age percentile or standard deviation score(SDS)
- Length or height velocity-for-age percentile or SDS
- Estimated dry weight and weight-for-age percentile or SDS
- BMI-for-height-age percentile or SDS
- Head circumference-for-age percentile or SDS (=3 years old only)
Normalized protein catabolic rate (nPCR) in hemodialyzed adolescents with CKD stage 5D.”
National Kidney Foundation. KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for 2006 Updates: Hemodialysis Adequacy, Peritoneal Dialysis Adequacy and Vascular Access. Am J Kidney Dis 48:S1-S322, 2006 (suppl 1).
http://www.kidney.org/PROFESSIONALS/kdoqi/guideline_upHD_PD_VA/index.htm
The 2006 KDOQI Guideline 8.2.2 rating strength grade is ‘B’. The recommendation for Grade B guidelines states ‘It is recommended that clinicians routinely follow the guideline for eligible patients. There is moderate to strong evidence that the practice improves health outcomes.’
In May 2014, an additional literature search was performed. A recent comprehensive review on the subject [4] is included in the citations below as a result of that search. This review continues to be supportive of the concept of monitoring nPCR as part of evaluation of Protein Energy Wasting (PEW) in children/adolescents on dialysis.
- Goldstein, Baronette, et al. nPCR assessment and IDPN treatment of malnutrition in pediatric hemodialysis patients. Pediatric Nephrology (2002) 17:531-534.
- Orellana P, Juarez-Congelosi M, Goldstein SL. Intradialytic parenteral nutrition treatment and biochemical marker assessment for malnutrition in adolescent maintenance hemodialysis patients. J Ren Nutrition 2005 Jul;15(3):312-7.
- Juarez-Congelosi M, Orellana P, Goldstein SL: Normalized protein catabolic rate versus serum albumin as a nutrition status marker in pediatric patients receiving hemodialysis. J Ren Nutr 17:269-274, 2007.
- Mastrangelo A, Paglialonga F, Edefonti A. Assessment of nutritional status in children with chronic kidney disease and on dialysis. Pediatr Nephrol. 2014 Aug;29(8):1349-58. doi: 10.1007/s00467-013-2612-7. Epub 2013 Sep 5.
An additional literature search was performed for the Fall 2024 cycle and no additional relevant publications were identified to support the measure. ISPD Guidelines did not address adequacy in children.
Measure Impact
Direct Evidence: due to the small number of pediatric patients, and sensitivity to their privacy, we have never collected patient level data on the perception of this measure. In addition, we are not aware of peer-reviewed literature that reports on pediatric dialysis patients’ perception of the meaningfulness of the measure.
Indirect Evidence: A kidney dietician is required to be available in all Medicare-certified dialysis clinics. This is particularly important for pediatric patients whose growth is monitored closely. Maintaining adequate protein intake, while being mindful of other minerals such as calcium and phosphorus, are critical for pediatric patients to achieve optimal growth. Therefore, a metric to track protein intake is meaningful to patients who want to achieve normal stature.
Performance Gap
After applying all exclusion criteria, we evaluated the nPCR performance scores for all dialysis facilities that had at least 11 patients in 2022 (n=23). The nPCR varies considerably across this small group of facilities, largely due to poor performance within the bottom quartile. The mean value of nPCR was 0.87 (i.e. 87% of pediatric patients had documented monthly nPCR measurements). The interquartile range (Q3-Q1) is around 0.13, with the bottom quartile of facilities having 85% or less of pediatric patients with documented nPCR measurements versus the top quartile of facilities having 98% or more of their patients with documented measurements. These are the following statistics of performance: Mean (SD) = 87% (20%), Min = 12%, 25th percentile = 85%, 50th percentile = 97%, 75th percentile = 98%, Max = 100%.
Note about Table 1: Deciles were defined differently between Tables 1 and 2. In Table 1, facilities are grouped and ranked according to ascending performance score. In Table 2, ranking is calculated on the basis of ascending facility size.
| Overall | Minimum | Decile_1 | Decile_2 | Decile_3 | Decile_4 | Decile_5 | Decile_6 | Decile_7 | Decile_8 | Decile_9 | Decile_10 | Maximum | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean Performance Score | 0.873 | 0.119 | 0.359 | 0.647 | 0.839 | 0.915 | 0.952 | 0.976 | 0.982 | 0.984 | 0.990 | 1.000 | 1.000 |
| N of Entities | 23 | 1 | 2 | 2 | 3 | 2 | 2 | 3 | 2 | 3 | 3 | 1 | 3 |
| N of Persons / Encounters / Episodes | 384 | 17 | 36 | 31 | 65 | 37 | 25 | 42 | 24 | 67 | 40 | 17 | 67 |
Equity
Equity
We are not providing a response to this optional question.
Feasibility
Feasibility
Data collection is accomplished via EQRS, a web-based and electronic batch submission platform maintained and operated by CMS contractors. Publicly reported measures like this one are reviewed on a regular basis by dialysis facility providers and rare instances of inaccurate or missing data are present (based on comments received during facility preview).
No changes were made
Proprietary Information
N/A
Scientific Acceptability
Testing Data
Calendar year 2022 data derived from a combination of EQRS and Medicare Claims Data.
We excluded three facilities from reliability testing for which there were no calculated nPCR values in 2022. Because calculation of nPCR requires interdialytic time, which is not currently reported in EQRS, we are unable to calculate nPCR for these facilities.
The measured entities used in testing and analysis include reported nPCR or the necessary data elements needed for calculation of nPCR. There are 384 in-center hemodialysis (ICH) pediatric patients from 23 dialysis facilities that have had at least 11 eligible pediatric patients across all regions of the United States.
Public reporting of this measure on DFC or in the ESRD QIP would be restricted to facilities with at least 11 eligible patients in order for the measure to comply with restrictions on reporting of potentially patient identifiable information related to small cell size. We have applied this restriction to all the reliability and validity testing reported here.
Facilities vary in size and include anywhere from 11 to 32 eligible ICH pediatric patients.
In 2022, there were 384 pediatric patients in total, after applying exclusion criteria (i.e., those at small facilities and those older than 18 years). Among them, 46.8% of patients were female, 55.8% were White, 37.0% were Black, 2.12% were Native American/Alaskan Native, 3.7% were Asian/Pacific Islander, 1.3% were Other/Multi-racial, and 30.4% were Hispanic. Please note, the number of patients listed here may not match the total number of patients in Tables 1 and 2 due to patients being counted multiple times if they switched providers during the year.
Reliability
January 2022 – December 2022 EQRS data were used to calculate the inter-unit reliability (IUR) for the overall 12 months to assess the reliability of this measure. The NQF-recommended approach for determining measure reliability is a one-way analysis of variance (ANOVA), in which the between and within facility variation in the measure is determined. The inter-unit reliability (IUR) measures the proportion of the measure variability that is attributable to the between-facility variance. The yearly based IUR was estimated using a bootstrap approach, which uses a resampling scheme to estimate the within facility variation that cannot be directly estimated by ANOVA. We note that the method for calculating the IUR was developed for measures that are approximately normally distributed across facilities. Since this measure is not normally distributed, the IUR value should be interpreted with some caution.
The overall IUR was 0.952, which indicates that about 95.2% of the variation in the measure can be attributed to the between facility differences and 4.8% to the within facility variation.
Note about Table 2: Deciles were defined differently between Tables 1 and 2. In Table 1, facilities are grouped and ranked according to ascending performance score. In Table 2, ranking is calculated on the basis of ascending facility size
The IUR suggests this measure is reliable. However, since the distribution of performance scores is skewed, the IUR value should be interpreted with some caution.
| | Overall | Minimum | Decile_1 | Decile_2 | Decile_3 | Decile_4 | Decile_5 | Decile_6 | Decile_7 | Decile_8 | Decile_9 | Decile_10 | Maximum |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Reliability | 0.952 | 0.9333 | 0.933 | 0.938 | 0.942 | 0.946 | 0.950 | 0.953 | 0.955 | 0.961 | 0.965 | 0.974 | 0.976 |
| Mean Performance Score | 0.873 | 96.948 | 96.948 | 98.653 | 98.058 | 97.649 | 82.578 | 79.863 | 84.783 | 52.150 | 91.896 | 88.178 | 98.374 |
| N of Entities | 23 | 3 | 3 | 2 | 1 | 3 | 2 | 2 | 4 | 2 | 2 | 2 | 1 |
| N of Persons / Encounters / Episodes | 384 | 33 | 33 | 24 | 13 | 42 | 30 | 32 | 68 | 39 | 44 | 59 | 32 |
Validity
Validity testing was not performed due to the small size of the pediatric population.
Data elements in EQRS for quality measures that are used in value-based purchasing undergo regular validity testing to ensure accuracy and results are publicly reported. This process involves a medical record review from 300 randomly selected dialysis facilities with up to 10 patients from each facility also being randomly selected. A total of 24 data elements were most recently reviewed from April – June 2023. A nurse review team compares these data elements from the patients chart to what is reported in EQRS. Although the nPCR value is not one of the data elements directly validated as part of this process, some of the data elements that would be used to calculate nPCR are validated such as patient weight and session duration. Other patient-level data elements include: date of birth, date regular dialysis began, admission and discharge date to facility, type of dialysis treatment and date of death. While the urea nitrogen levels are also not directly validated as part of this process, other laboratory values (calcium, phosphorus) are directly validated and findings should be similar across all laboratory values given the automated process used by most dialysis facilities.
Results of this analysis are notable for the following:
- 96.5% correct matches with 1.6% of entries in either EQRS (0.2%) or Medical Records (1.4%) containing missing information.
- 1.9% incorrect matches
- Date elements showed error rates ranging from 0-2.3%
This analysis reveals a high degree of validity for the key data elements used in the measure. Additional details can be found at: https://qualitynet.cms.gov/esrd/data-validation#tab2
Risk Adjustment
Use & Usability
Use
All Medicare-certified dialysis facilities that are eligible for the measure and have at least 11 patients (due to public reporting requirements).
Usability
In order for facilities to improve performance on this measure, they must increase collection and reporting of the nPCR value or the data elements necessary to calculate an nPCR value on a monthly basis. Given that these data elements are known and monitored during each dialysis session, and the requirement is only to report one of these each month, it is felt that collecting and reporting these is not difficult to achieve.
For DFCC, feedback can be provided any time through contacting the dialysisdata.org helpdesk. Preview periods allow for specific times for facilities review and comment on measure calculations, and provide an opportunity to request a patient list.
We reviewed the comments and questions submitted during the DFCC preview periods that have taken place since the original maintenance (2016-present). We have received only a handful of clarification questions since the measure was added to DFCC, likely due to the very small number of facilities that receive a measure score.
Given that small scale observational studies have shown an association between nPCR and nutritional status among malnourished adolescent patients who achieved target spKt/V levels, we would expect that public reporting of this measure may engage facilities to better monitor the nutrition status of their pediatric patients. With the exception of the most current year, the mean and min values have been steadily increasing since this measure’s inception. Calendar year 2020 was not reported due to CMS's COVID Extraordinary Circumstances Exception (ECE) data policy that restricted the use of EQRS clinical data from a portion of that year.
CY 2017: N = 29, Mean = 76.64%, Std Dev = 32.46%, Min = 0.0%, Max = 99.32%
CY 2018: N = 26, Mean = 78.40%, Std Dev = 25.36%, Min = 0.0%, Max = 100.0%
CY 2019: N = 31, Mean = 90.24%, Std Dev = 13.59%, Min = 37.33%, Max = 100.0%
CY 2021: N = 18, Mean = 92.24%, Std Dev = 10.95%, Min = 57.66%, Max = 100.0%
CY 2022: N = 23, Mean = 87.29%, Std Dev = 20.48%, Min = 11.88%, Max = 100.0%
None that we are aware of.
Comments
Staff Preliminary Assessment
CBE #1425 Staff Assessment
Importance
Strengths:
- Logic Model: A clear logic model is provided, depicting the relationships between inputs (e.g., effective management of pediatric dietary nutrition via an interdisciplinary team), activities (e.g., monthly measurements of normalized protein catabolic rate (nPCR) in pediatric patients), and desired outcomes (e.g., decrease likelihood of malnutrition, hospitalizations, and death, improved quality of care, and an increase in the patient's quality of life). This model demonstrates how the measure's implementation will lead to the anticipated outcomes.
- Evidence and Literature Review: The measure is supported by a comprehensive literature review including clinical practice guidelines that demonstrate a clear net benefit in terms of improved outcomes for pediatric dietary nutrition in in-center hemodialysis patients. The primary source of evidence for this measure is the National Kidney Foundation KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for 2006 Updates: Hemodialysis Adequacy, peritoneal Dialysis Adequacy, and Vascular Access.
- Performance Gap: Data from 2022 shows a performance gap, with decile ranges from 0.119 to 1.000, indicating variation in measure performance across facilities.
- Anticipated Impact: If implemented, the developer posits the measure’s anticipated impact on important outcomes is expected to be improved quality of care and an increase in the patient's quality of life, based on data from the End Stage Renal Disease Quality Reporting System (EQRS).
- Business Case: Overall, the developer provides strong evidence of significant improvements in patient outcomes due to effective management of pediatric dietary nutrition, with a well-documented, strong business case for the measure’s relevance and necessity in improving health care outcomes for pediatric hemodialysis patients.
- Existing Measures: The proposed measure addresses a healthcare need not sufficiently covered by existing measures, offering advantages in terms of addressing malnutrition in pediatric hemodialysis patients.
- Patient Input: Description of patient input supports the conclusion that the measured outcome is meaningful with at least moderate certainty. However, the developer notes that they lack feedback from patients on the perception of this measure because of the small number of pediatric patients, sensitivity to their privacy, and lack of literature. The measure is considered meaningful to patients because kidney dieticians in dialysis clinics help pediatric patients maintain adequate protein intake, which is critical for growth and achieving normal stature.
Limitations:
- Evidence: The evidence supporting this measure is fairly old. This is most likely due to the lack of updated guidelines.
- Performance gap: Although performance scores by decile range from 0.12 to 1.00, indicating variation in measure performance across facilities, the performance gap data is based on 23 facilities and 384 eligible patients. This low number of facilities and patients limits the generalizaibilty of the performance gap results.
Rationale:
- This measure meets all criteria for "Met" due to its robust, well-graded evidence base, clear business case, documented performance gap, significant anticipated impact, well-articulated logic model, and its superiority over existing measures, making it essential for addressing pediatric dietary nutrition in in-center hemodialysis patients.
Feasibility Acceptance
Strengths:
- Feasibility Assessment: A comprehensive feasibility assessment has been conducted. Testing data are derived from EQRS, with Medicare claims used as an additional source.
- Adjustments Based on Feasibility: There were no adjustments to the measure’s development from the feasibility assessment.
- Data Collection Strategy: Required data are routinely generated and used during care, are available in EQRS and Medicare claims, and the data collection strategy can be implemented effectively. Measures reported on Dialysis Facility Care Compare (DFCC) are reviewed regularly by dialysis facility providers for inaccurate or missing data.
- Licensing and Fees: This is not a proprietary measure and there are no proprietary components. There are no fees to use any aspect of the measure.
Limitations:
- None.
Rationale:
- This maintenance measure meets all criteria for 'Met' due to its well-documented feasibility assessment, clear and implementable data collection strategy, and transparent handling of licensing and fees, ensuring practical implementation within the health care system.
Scientific Acceptability
Strengths:
- Data Sources and Dates: Data used for testing were sourced from EQRS and Medicare claims data during the period 1/2022-12/2022. The entities included in the analysis were characterized by facilities with 11 or more eligible patients.
- Accountable Entity-Level Reliability: The developer conducted inter-unit reliability testing (IUR) at the accountable entity-level. A bootstrap approach was used to estimate within-entity variance. More than 70% of accountable entities meet the expected threshold of 0.6.
Limitations:
- None.
Rationale:
- The results demonstrate sufficient reliability at the accountable entity level.
Strengths:
- The developer provided person- or episode-level validity testing from 300 randomly selected facilities for 10 patients per facility (April-June 2023) for key data elements (date of birth, date regular dialysis began, admission and discharge date to facility, type of dialysis treatment and date of death. Quality measure data elements include: Kt/V for hemodialysis, date of Kt/V collection, method used to calculate Kt/V, and modality type). The results demonstrated high agreement and low missing values.
Limitations:
- The developer stated that accountable-entity level validity testing was not conducted due to small sample sizes for pediatric patients. In addition, face validity was not systematically assessed. Finally, the absence of material variation of an intermediate outcome measure among entities in the Importance Table (Table 1) also does not support a validity claim.
Rationale:
- The developer conducted person- or episode-level validity testing on key data elements from 300 facilities, showing high agreement and low missing values, but did not perform accountable-entity level validity testing due to small pediatric sample sizes and did not systematically assess face validity. The absence of material variation of an intermediate outcome measure among entities in the Importance Table (Table 1) also does not support a validity claim. Going forward, a more robust logic model substantiated with face validity from the TEP would provide some modest support for a validity claim.
Equity
The developer did not address this optional domain.
Use and Usability
Strengths:
- Use: The measure is currently used in Dialysis Facility Care Compare.
- Actions for Improvement: The developer provides a summary of how accountable entities can use the measure results to improve performance. Specifically, by increasing the collection and reporting of the nPCR value or the data elements necessary to calculate an nPCR value on a monthly basis, facilities can improve performance on this measure.
- Feedback Mechanism: Feedback and questions about the measure can be provided through the dialysisdata.org helpdesk. Additionally, specific preview periods allow facilities to review and comment on measure calculations and request a patient list. The developer noted that they received only a handful of clarification questions since the measure was added to DFCC, likely due to the very small number of facilities that receive a measure score.
- Measure Updates: The developer noted that the feedback received did not lead to any changes in the measure specifications.
- Performance Trends: The developer reports changes in performance from 2017 to 2022, in which the overall performance increased, which supports the argument that this measure is usable. Calendar year 2020 was not reported due to CMS's COVID Extraordinary Circumstances Exception (ECE) data policy that restricted the use of EQRS clinical data from a portion of that year.
- Unexpected Findings: The developer reports no unexpected findings or documented unintended impacts on patients as a result of measure implementation.
Limitations:
- Missing data due to CMS's COVID Extraordinary Circumstances Exception (ECE) data policy. While the developer provides an explanation for the omitted 2020 data, the implications of the missing data on trend analysis are not explicitly addressed.
- There is an increase in performance (CY 2017-2019, 2021) followed by a decline in CY 2022. Trends in improvement are based on a small number of facilities, which exhibits variability.
Rationale:
- For maintenance, the measure is actively used in at least one accountability application, with a clear feedback approach that allows for continuous updates based on stakeholder feedback. The measure also demonstrates a positive trend in performance results, affirming its ongoing usability. The developer reports no unexpected findings.
Committee Independent Review
support, with caveats as noted below
Importance
Met, but weaknesses include old evidence base and very limited number of patients available for testing and analysis. Also, rather than an outcome (eg, meeting a specified protein nutrition goal), this process measure only asks whether this protein intake measurement was done, which is not ideal
Feasibility Acceptance
agree with staff
Scientific Acceptability
agree with staff
small sample size, face validity issues
Equity
voluntary domain
Use and Usability
agree with staff
Summary
This measure is limited by being a process measure, and it provides little information about how facilities are actually doing with the nutritional status of their patients. This needs to be followed in the near future with a measure of actually protein intake info. The measure is also inherently limited by the small number of pediatric patients in dialysis facilities, which limits sample size
Summary
Importance
Agree with staff recommendations.
Feasibility Acceptance
Agree with staff recommendations.
Scientific Acceptability
Agree with staff recommendations.
Agree with staff recommendations.
Equity
Agree with staff recommendations.
Use and Usability
Agree with staff recommendations.
Summary
The validity testing is limited.
Support
Importance
Agree with staff
Feasibility Acceptance
Agree with staff
Scientific Acceptability
Agree with staff
Agree with staff
Equity
Agree with staff
Use and Usability
Agree with staff
Summary
evidence is older and limited
Nothing to comment.
Importance
Met.
Feasibility Acceptance
This was demonstrated.
Scientific Acceptability
Acceptability was met.
Conversation with and results from the patient and caregiver population would firm this finding.
Equity
This was skipped since it was optional.
Use and Usability
This is use/usability met.
Summary
Nothing to comment.
Some areas of need as identified above
Importance
Results of literature review should be summarized for review, not simply cited. Guideline statements are old but clear, and developer states no updated guidelines are available.
The rationale for not gathering patient input is not sufficient to me. It is unclear why the fact that there are few pediatric patients in this population would preclude the developer from attempting to contact advocacy groups and take other actions to appropriately engage with this population and understand their perspectives.
Do not find the indirect evidence provided by the developer valuable.
Feasibility Acceptance
There is no information on feasibility challenges or lack thereof in this section. Have feasibility issues been identified?
Scientific Acceptability
Need more information on bootstrap/resampling methodology to gauge findings. Sample sizes are very small.
Developer does not explain why small sample sizes at the facility precludes various approaches to establishing empirical validity, such as convergent validity (e.g., do high performing facilities for pediatric nPCR measurement also perform favorably on other likely correlated metrics, or on likely correlated outcomes?). No face validity.
Equity
No comment.
Use and Usability
No concerns.
Summary
Additionally, are value sets for data derived from Medicare claims provided?
Support
Importance
Agree with staff
Feasibility Acceptance
Agree with staff
Scientific Acceptability
Agree with staff
Agree with staff
Equity
Agree with staff
Use and Usability
Agree with staff
Summary
Agree with staff. We need this data and understand the sample size for pediatric patients is small.
Support
Importance
Important area of pediatric health deserving more attention
Feasibility Acceptance
Easy to collect and report
Scientific Acceptability
Agree with staff comments
Agree with staff assessment
Equity
But should be investigated
Use and Usability
Agree with staff comments
Summary
Agree with staff assessments
Synthesis
Importance
Main question is: Does relatively high documentation in EQRS lead to improved care processes and outcomes as proposed in logic model?
Also based on 2006 guidelines form National Kidney Foundation.
Given the complacency across the dialysis measures and likely opportunity to address, I was inclined be rate “Not met” for this round.
Adapted similar logic model as other pediatric dialysis measure. Assumes that monthly measurements of nPCR will be associated with care processes related to improved detection of indicator of malnutrition, patient education and consideration of nutritional supplements. Proposed outcome is reduced risk of malnutrition with conceptual leap to hospitalizations and death. The results are very broadly defined and not operationally defined (improved quality of care, increased patient quality of life).
Lit review in 2014 yielded four papers (2002-2014), and measure developer reports no additional publications when searched for Fall 2024 cycle. Really?
Measure impact admits “we never collected patient level data on the perception of the measure”
Performance gap is wide ranging from .119 to .976 by deciles, mean=.873. 875% had documented nPCR.
This measure is contingent on documentation.
Feasibility Acceptance
Data collection is accomplished via EQRS, a web-based and electronic batch submission platform maintained and operated by CMS contractors.
Non-proprietary
Scientific Acceptability
Inter-unit reliability: IUR=0.952 with little differences by deciles (i.e., 95% of variation attributable to differences between facilities)
Validity testing at accountable entity level not done.
Instead examined extend of match between chart and EQRS data elements. This is more an indicator of the quality of data collection, not validity of the measure.
No risk adjustment likely due to limitations in data source.
Equity
not done
Use and Usability
Same issue, used in publicly reporting and link helps patient find a facility.
Trends in documentation suggest relatively high documentation in EQRS in 2029, 2021 and 2022 (ranging from 90.24% to 87.29%) Small samples so difficult to assess if significantly different. Is this also topped off?
Summary
outdated guidelines, assumptions in logic model that have no data, no data to support clinical validity, possibly topped off—recent adherence rates suggest better documentation in EQRS
Public Comments
ASPN Comments on CBE #1425
This measure is described as a percentage of patient months of pediatric (< 18 years old) in-center hemodialysis patients (irrespective of frequency of dialysis) with documented monthly nPCR measurements. ASPN believes that the nPCR measure is reasonable as a reporting measure as a start for a pediatric assessment of nutrition. Currently, there is only outcome data for adolescents with nPCR greater than 1. Therefore, ASPN supports the endorsement of this measure.
Measurement of nPCR for Pediatric Hemodialysis Patients
ASN believes that it is important to incorporate a pediatric-specific growth or nutrition measure in the ESRD QIP. While the CBE #1425: Measurement of nPCR for Pediatric Hemodialysis Patients may not be perfect, it is an important step in the right direction. Thus, ASN supports its endorsement. While the underlying data supporting specific values are linked only to adolescent patients, this process measure (if adopted) would ensure that facilities monitor all pediatric patients with the most appropriate measurement currently available.
ASN again thanks you for the opportunity to comment on these measures. For questions, please contact David White, Senior Regulatory and Quality Officer, at dwhite@asn-online.org .
Comment on CBE #1425: Measurement of nPCR for Pediatric HD Patie
Kidney Care Partners (KCP) appreciates the opportunity to comment on four of the measures that are part of the Partnership for Quality Measurement’s Fall 2024 Measure Cycle. KCP is a coalition of members of the kidney care community that includes the full spectrum of stakeholders related to dialysis care—patient advocates, healthcare professionals, dialysis providers, researchers, and manufacturers and suppliers—organized to advance policies that improve the quality of care for individuals with chronic kidney disease and end stage renal disease (ESRD). We greatly appreciate the PQM undertaking this important work and offer the following comments addressing the ESRD facility-level measures under review.
CBE #1425: Measurement of nPCR for Pediatric Hemodialysis Patients
KCP believes that it is important to incorporate a pediatric-specific growth or nutrition measure in the ESRD QIP. While the CBE #1425: Measurement of nPCR for Pediatric Hemodialysis Patients may not be perfect, it is an important step in the right direction. Thus, KCP supports its endorsement. While the underlying data supporting specific values are linked only to adolescent patients, this process measure (if adopted) would ensure that facilities are monitoring all pediatric patients with the most appropriate measurement currently available.
KCP again thanks you for the opportunity to comment on this these measures. If you have any questions, please do not hesitate to contact Kathy Lester, JD, MPH.