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The accuracy of diagnostic coding for acute kidney injury in England – a single centre study
BACKGROUND: Acute kidney injury (AKI) is an independent risk factor for mortality and is responsible for a significant burden of healthcare expenditure, so accurate measurement of its incidence is important. Administrative coding data has been used for assessing AKI incidence, and shows an increasin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599863/ https://www.ncbi.nlm.nih.gov/pubmed/23496869 http://dx.doi.org/10.1186/1471-2369-14-58 |
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author | Tomlinson, Laurie A Riding, Alex M Payne, Rupert A Abel, Gary A Tomson, Charles R Wilkinson, Ian B Roland, Martin O Chaudhry, Afzal N |
author_facet | Tomlinson, Laurie A Riding, Alex M Payne, Rupert A Abel, Gary A Tomson, Charles R Wilkinson, Ian B Roland, Martin O Chaudhry, Afzal N |
author_sort | Tomlinson, Laurie A |
collection | PubMed |
description | BACKGROUND: Acute kidney injury (AKI) is an independent risk factor for mortality and is responsible for a significant burden of healthcare expenditure, so accurate measurement of its incidence is important. Administrative coding data has been used for assessing AKI incidence, and shows an increasing proportion of hospital bed days attributable to AKI. However, the accuracy of coding for AKI and changes in coding over time have not been studied in England. METHODS: We studied a random sample of admissions from 2005 and 2010 where ICD-10 code N17 (acute renal failure) was recorded in the administrative coding data at one acute NHS Foundation Trust in England. Using the medical notes and computerised records we examined the demographic and clinical details of these admissions. RESULTS: Against a 6.3% (95% CI 4.8-7.9%) increase in all non-elective admissions, we found a 64% increase in acute renal failure admissions (95% CI 41%-92%, p < 0.001) in 2010 compared to 2005. Median age was 78 years (IQR 72–87), 11-25% had a relevant pre-admission co-morbidity and 64% (55-73%) were taking drugs known to be associated with AKI. Over both years, 95% (91-99%) of cases examined met the Kidney Disease: Improving Global Outcomes criteria for AKI. CONCLUSIONS: Patients with hospital admissions where AKI has been coded are elderly with multiple co-morbidities. Our results demonstrate a high positive predictive value of coding data for a clinical diagnosis of AKI, with no suggestion of marked changes in coding of AKI between 2005 and 2010. |
format | Online Article Text |
id | pubmed-3599863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35998632013-03-17 The accuracy of diagnostic coding for acute kidney injury in England – a single centre study Tomlinson, Laurie A Riding, Alex M Payne, Rupert A Abel, Gary A Tomson, Charles R Wilkinson, Ian B Roland, Martin O Chaudhry, Afzal N BMC Nephrol Research Article BACKGROUND: Acute kidney injury (AKI) is an independent risk factor for mortality and is responsible for a significant burden of healthcare expenditure, so accurate measurement of its incidence is important. Administrative coding data has been used for assessing AKI incidence, and shows an increasing proportion of hospital bed days attributable to AKI. However, the accuracy of coding for AKI and changes in coding over time have not been studied in England. METHODS: We studied a random sample of admissions from 2005 and 2010 where ICD-10 code N17 (acute renal failure) was recorded in the administrative coding data at one acute NHS Foundation Trust in England. Using the medical notes and computerised records we examined the demographic and clinical details of these admissions. RESULTS: Against a 6.3% (95% CI 4.8-7.9%) increase in all non-elective admissions, we found a 64% increase in acute renal failure admissions (95% CI 41%-92%, p < 0.001) in 2010 compared to 2005. Median age was 78 years (IQR 72–87), 11-25% had a relevant pre-admission co-morbidity and 64% (55-73%) were taking drugs known to be associated with AKI. Over both years, 95% (91-99%) of cases examined met the Kidney Disease: Improving Global Outcomes criteria for AKI. CONCLUSIONS: Patients with hospital admissions where AKI has been coded are elderly with multiple co-morbidities. Our results demonstrate a high positive predictive value of coding data for a clinical diagnosis of AKI, with no suggestion of marked changes in coding of AKI between 2005 and 2010. BioMed Central 2013-03-13 /pmc/articles/PMC3599863/ /pubmed/23496869 http://dx.doi.org/10.1186/1471-2369-14-58 Text en Copyright ©2013 Tomlinson et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Tomlinson, Laurie A Riding, Alex M Payne, Rupert A Abel, Gary A Tomson, Charles R Wilkinson, Ian B Roland, Martin O Chaudhry, Afzal N The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title | The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title_full | The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title_fullStr | The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title_full_unstemmed | The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title_short | The accuracy of diagnostic coding for acute kidney injury in England – a single centre study |
title_sort | accuracy of diagnostic coding for acute kidney injury in england – a single centre study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599863/ https://www.ncbi.nlm.nih.gov/pubmed/23496869 http://dx.doi.org/10.1186/1471-2369-14-58 |
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