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Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data
INTRODUCTION: The excessive consumption of alcohol is detrimental to long term health and increases the likelihood of hospital admission. However, definitions of alcohol-related hospital admission vary, giving rise to uncertainty in the effect of alcohol on alcohol-related health care utilization. O...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Swansea University
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103565/ https://www.ncbi.nlm.nih.gov/pubmed/34007894 http://dx.doi.org/10.23889/ijpds.v6i1.1373 |
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author | Trefan, Laszl Akbari, Ashley Morgan, Jennifer Siân Farewell, Daniel Mark Fone, David Lyons, Ronan A Jones Hywel, Merfyn Moore, Simon C |
author_facet | Trefan, Laszl Akbari, Ashley Morgan, Jennifer Siân Farewell, Daniel Mark Fone, David Lyons, Ronan A Jones Hywel, Merfyn Moore, Simon C |
author_sort | Trefan, Laszl |
collection | PubMed |
description | INTRODUCTION: The excessive consumption of alcohol is detrimental to long term health and increases the likelihood of hospital admission. However, definitions of alcohol-related hospital admission vary, giving rise to uncertainty in the effect of alcohol on alcohol-related health care utilization. OBJECTIVES: To compare diagnostic codes on hospital admission and discharge and to determine the ideal combination of codes necessary for an accurate determination of alcohol-related hospital admission. METHODS: Routine population-linked e-cohort data were extracted from the Secure Anonymised Information Linkage (SAIL) Databank containing all alcohol-related hospital admissions (n,= 92,553) from 2006 to 2011 in Wales, United Kingdom. The distributions of the diagnostic codes recorded at admission and discharge were compared. By calculating a misclassification rate (sensitivity-like measure) the appropriate number of coding fields to examine for alcohol-codes was established. RESULTS: There was agreement between admission and discharge codes. When more than ten coding fields were used the misclassification rate was less than 1%. CONCLUSION: With the data at present and alcohol-related codes used, codes recorded at admission and discharge can be used equivalently to identify alcohol-related admissions. The appropriate number of coding fields to examine was established: fewer than ten is likely to lead to under-reporting of alcohol-related admissions. The methods developed here can be applied to other medical conditions that can be described using a certain set of diagnostic codes, each of which can be a known sole cause of the condition and recorded in multiple positions in e-cohort data. |
format | Online Article Text |
id | pubmed-8103565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Swansea University |
record_format | MEDLINE/PubMed |
spelling | pubmed-81035652021-05-17 Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data Trefan, Laszl Akbari, Ashley Morgan, Jennifer Siân Farewell, Daniel Mark Fone, David Lyons, Ronan A Jones Hywel, Merfyn Moore, Simon C Int J Popul Data Sci Population Data Science INTRODUCTION: The excessive consumption of alcohol is detrimental to long term health and increases the likelihood of hospital admission. However, definitions of alcohol-related hospital admission vary, giving rise to uncertainty in the effect of alcohol on alcohol-related health care utilization. OBJECTIVES: To compare diagnostic codes on hospital admission and discharge and to determine the ideal combination of codes necessary for an accurate determination of alcohol-related hospital admission. METHODS: Routine population-linked e-cohort data were extracted from the Secure Anonymised Information Linkage (SAIL) Databank containing all alcohol-related hospital admissions (n,= 92,553) from 2006 to 2011 in Wales, United Kingdom. The distributions of the diagnostic codes recorded at admission and discharge were compared. By calculating a misclassification rate (sensitivity-like measure) the appropriate number of coding fields to examine for alcohol-codes was established. RESULTS: There was agreement between admission and discharge codes. When more than ten coding fields were used the misclassification rate was less than 1%. CONCLUSION: With the data at present and alcohol-related codes used, codes recorded at admission and discharge can be used equivalently to identify alcohol-related admissions. The appropriate number of coding fields to examine was established: fewer than ten is likely to lead to under-reporting of alcohol-related admissions. The methods developed here can be applied to other medical conditions that can be described using a certain set of diagnostic codes, each of which can be a known sole cause of the condition and recorded in multiple positions in e-cohort data. Swansea University 2021-03-24 /pmc/articles/PMC8103565/ /pubmed/34007894 http://dx.doi.org/10.23889/ijpds.v6i1.1373 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Population Data Science Trefan, Laszl Akbari, Ashley Morgan, Jennifer Siân Farewell, Daniel Mark Fone, David Lyons, Ronan A Jones Hywel, Merfyn Moore, Simon C Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title | Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title_full | Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title_fullStr | Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title_full_unstemmed | Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title_short | Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data |
title_sort | visualisation and optimisation of alcohol-related hospital admissions icd-10 codes in welsh e-cohort data |
topic | Population Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103565/ https://www.ncbi.nlm.nih.gov/pubmed/34007894 http://dx.doi.org/10.23889/ijpds.v6i1.1373 |
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