Evidence map›Paper›PMID 27335126›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2016

Ultrafiltration Rates and the Quality Incentive Program: Proposed Measure Definitions and Their Potential Dialysis Facility Implications.

Jennifer E Flythe, Magdalene M Assimon, Julia B Wenger, Lily Wang

Abstract read
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Observational
  3. Article
  4. Epidemiology of nursing home dialysis patients-A hidden population.Hemodialysis international. International Symposium on Home Hemodialysis · 2021
    Article
  5. Article
  6. Article
  7. Individualization of Ultrafiltration in Hemodialysis.IEEE transactions on bio-medical engineering · 2019
    Article
  8. Observational
  9. Article
  10. Review
  11. Article
  12. Fluid First or Not So Fast: Ultrafiltration Rate and the ESRD Quality Incentive Program.Clinical journal of the American Society of Nephrology : CJASN · 2016
    Article
  13. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jennifer E FlytheUniversity of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
Magdalene M AssimonUniversity of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
Julia B WengerUniversity of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
Lily WangCecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, North Carolina; and.

Funding

RENAL EPIDEMIOLOGY TRAINING PROGRAMT32DK007750 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FALK, RONALD J · 1999 to 2022
$5.5M
NIDDK NIH HHS T32 DK007750
6 · The paper itself

Abstract

BACKGROUND AND

objectivesRapid ultrafiltration rates are associated with adverse outcomes among patients on hemodialysis. The Centers for Medicare and Medicaid Services is considering an ultrafiltration rate quality measure for the ESRD Quality Incentive Program. Two measure developers proposed ultrafiltration rate measures with different selection criteria and specifications. We aimed to compare the proposed ultrafiltration rate measures and quantify dialysis facility operational burden if treatment times were extended to lower ultrafiltration rates. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Data were taken from the 2012 database of a large dialysis organization. Analyses of the Centers for Medicare and Medicaid Services measure considered 148,950 patients on hemodialysis, and analyses of the Kidney Care Quality Alliance measure considered 151,937 patients. We described monthly patient and facility ultrafiltration rates and examined differences in patient characteristics across ultrafiltration rate thresholds and differences in facilities across ultrafiltration rate measure scores. We computed the additional treatment time required to lower ultrafiltration rates <13 ml/h per kilogram.

resultsUltrafiltration rates peaked in winter and nadired in summer. Patients with higher ultrafiltration rates were younger; more likely to be women, nonblack, Hispanic, and lighter in weight; and more likely to have histories of heart failure compared with patients with lower ultrafiltration rates. Facilities had, on average, 20.8%±10.3% (July) to 22.8%±10.6% (February) of patients with ultrafiltration rates >13 ml/h per kilogram by the Centers for Medicare and Medicaid Services monthly measure. Facilities had, on average, 15.8%±8.2% of patients with ultrafiltration rates ≥13 ml/h per kilogram by the Kidney Care Quality Alliance annual measure. Larger facilities (>100 patients) would require, on average, 33 additional treatment hours per week to lower all facility ultrafiltration rates <13 ml/h per kilogram when total treatment time is capped at 4 hours.

conclusionsUltrafiltration rates vary seasonally and across clinical subgroups. Extension of treatment time as a strategy to lower ultrafiltration rates may pose facility operational challenges. Prospective studies of ultrafiltration rate threshold implementation are needed.

Indexed as

Quality Indicators, Health CareAdultAgedAge FactorsAmbulatory Care FacilitiesBlack or African AmericanBody WeightCenters for Medicare and Medicaid Services, U.S.HemodiafiltrationHispanic or LatinoHumansMiddle AgedQuality Assurance, Health CareSeasonsSex FactorsTime FactorsEpidemiology and outcomesheart failurehemodialysisHumansKidney Failure, ChronicMedicaidMedicareProspective Studiesrenal dialysisultrafiltration

Identifiers

PMID27335126
PMCPMC4974895

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.