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Identification, Coding, and Reimbursement of Pediatric Malnutrition at an Urban Academic Medical Center

Overview of attention for article published in Nutrition in Clinical Practice, March 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Article details
Title
Identification, Coding, and Reimbursement of Pediatric Malnutrition at an Urban Academic Medical Center
Published in
Nutrition in Clinical Practice, March 2018
DOI 10.1002/ncp.10064
Pubmed ID
Authors

Sabrina M. Bierman, Sarah J. Peterson, Yimin Chen

Abstract

The American Academy of Nutrition and Dietetics and the American Society of Parenteral and Enteral Nutrition released a pediatric malnutrition consensus statement in 2014 recommending the use of z-scores as indicators for identification and documentation of malnutrition. A shift in focus is needed on standardizing pediatric malnutrition language at institutions nationwide to make study data comparable. With this standardized language, establishment of institutional baselines for identification, coding, and reimbursement of pediatric malnutrition is crucial to measure process improvements. The objectives of this study were to determine the prevalence of malnutrition among pediatric patients at an urban academic medical center, the frequency of malnutrition codes used, and the reimbursement impact of coding for malnutrition. Electronic medical records of pediatric patients admitted from January 2013 to December 2015 were reviewed. Malnutrition was identified based on registered dietitian identification and z-score. Patients given a malnutrition-related International Classification of Diseases code upon discharge were identified. A reimbursement calculation was performed: the malnutrition-related International Classification of Diseases code was removed to determine the difference in reimbursement with vs without the code. Of the 1,532 admissions included in this study, 464 (30%) were identified as malnourished. A total of 152 (33%) malnourished patients were given a malnutrition-related secondary diagnosis. The calculation revealed that coding for malnutrition resulted in an additional $27,665.70 to the medical center. Malnutrition coding may have a significant financial impact and processes improvement efforts can be made to improve malnutrition coding.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 8 16%
Researcher 7 14%
Student > Bachelor 6 12%
Other 3 6%
Professor 3 6%
Other 4 8%
Unknown 18 37%
Readers by discipline
Readers by discipline Count As %
Nursing and Health Professions 11 22%
Medicine and Dentistry 8 16%
Computer Science 3 6%
Agricultural and Biological Sciences 2 4%
Social Sciences 2 4%
Other 6 12%
Unknown 17 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2018.
All research outputs
#7,822,893
of 24,458,924 outputs
Outputs from Nutrition in Clinical Practice
#651
of 1,481 outputs
Outputs of similar age
#129,737
of 337,203 outputs
Outputs of similar age from Nutrition in Clinical Practice
#9
of 37 outputs
Altmetric has tracked 24,458,924 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,481 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,203 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.