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How do primary care doctors in England and Wales code and manage people with chronic kidney disease? Results from the National Chronic Kidney Disease Audit

Overview of attention for article published in Nephrology Dialysis Transplantation, October 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

twitter
5 tweeters
facebook
1 Facebook page

Citations

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14 Dimensions

Readers on

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39 Mendeley
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Title
How do primary care doctors in England and Wales code and manage people with chronic kidney disease? Results from the National Chronic Kidney Disease Audit
Published in
Nephrology Dialysis Transplantation, October 2017
DOI 10.1093/ndt/gfx280
Pubmed ID
Authors

Lois G Kim, Faye Cleary, David C Wheeler, Ben Caplin, Dorothea Nitsch, Sally A Hull

Abstract

In the UK, primary care records are electronic and require doctors to ascribe disease codes to direct care plans and facilitate safe prescribing. We investigated factors associated with coding of chronic kidney disease (CKD) in patients with reduced kidney function and the impact this has on patient management. We identified patients meeting biochemical criteria for CKD (two estimated glomerular filtration rates <60 mL/min/1.73 m2 taken >90 days apart) from 1039 general practitioner (GP) practices in a UK audit. Clustered logistic regression was used to identify factors associated with coding for CKD and improvement in coding as a result of the audit process. We investigated the relationship between coding and five interventions recommended for CKD: achieving blood pressure targets, proteinuria testing, statin prescription and flu and pneumococcal vaccination. Of 256 000 patients with biochemical CKD, 30% did not have a GP CKD code. Males, older patients, those with more severe CKD, diabetes or hypertension or those prescribed statins were more likely to have a CKD code. Among those with continued biochemical CKD following audit, these same characteristics increased the odds of improved coding. Patients without any kidney diagnosis were less likely to receive optimal care than those coded for CKD [e.g. odds ratio for meeting blood pressure target 0.78 (95% confidence interval 0.76-0.79)]. Older age, male sex, diabetes and hypertension are associated with coding for those with biochemical CKD. CKD coding is associated with receiving key primary care interventions recommended for CKD. Increased efforts to incentivize CKD coding may improve outcomes for CKD patients.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 31%
Researcher 9 23%
Student > Doctoral Student 3 8%
Student > Bachelor 3 8%
Student > Master 2 5%
Other 3 8%
Unknown 7 18%
Readers by discipline Count As %
Medicine and Dentistry 13 33%
Nursing and Health Professions 13 33%
Psychology 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 0 0%
Unknown 9 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 April 2019.
All research outputs
#7,574,815
of 14,602,028 outputs
Outputs from Nephrology Dialysis Transplantation
#2,767
of 4,479 outputs
Outputs of similar age
#128,884
of 317,526 outputs
Outputs of similar age from Nephrology Dialysis Transplantation
#39
of 55 outputs
Altmetric has tracked 14,602,028 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,479 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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 317,526 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 58% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.