Visualisation and optimisation of alcohol-related hospital admission ICD-10 codes in Welsh e-cohort data

Trefan, Laszlo ORCID: https://orcid.org/0000-0001-9750-7112, Akbari, Ashley, Morgan, Jennifer Sian, Farewell, Daniel Mark ORCID: https://orcid.org/0000-0002-8871-1653, Fone, David ORCID: https://orcid.org/0000-0002-6476-4881, Lyons, Ronan A., Jones, Hywel Merfyn ORCID: https://orcid.org/0000-0001-8308-2002 and Moore, Simon C. ORCID: https://orcid.org/0000-0001-5495-4705 2021. Visualisation and optimisation of alcohol-related hospital admission ICD-10 codes in Welsh e-cohort data. International Journal of Population Data Science 6 (1) , 09. 10.23889/ijpds.v6i1.1373

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Abstract

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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Dentistry Schools > Medicine
Additional Information:	Open Access under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en)
Publisher:	Swansea University
ISSN:	2399-4908
Funders:	ESRC
Date of First Compliant Deposit:	24 March 2021
Date of Acceptance:	11 January 2021
Last Modified:	06 Jan 2024 05:48
URI:	https://orca.cardiff.ac.uk/id/eprint/140070

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