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001-es BibID:	BIBFORM112203
035-os BibID:	(WOS)000894823500025 (cikkazonosító)1373 (Scopus)85104890786
Első szerző:	Trefán László (biostatisztikus, bioinformatikus)
Cím:	Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data / Laszlo Trefan, Ashley Akbari, Jennifer Siân Morgan, Daniel Mark Farewell, David Fone, Ronan A. Lyons, Hywel Merfyn Jones, Simon Moore
Dátum:	2021
ISSN:	2399-4908
Megjegyzések:	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.
Tárgyszavak:	Orvostudományok Egészségtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	International Journal of Population Data Science. - 6 : 1 (2021), p. 1-12. -
További szerzők:	Akbari, Ashley Morgan, Jennifer Farewell, Daniel Fone, David Lyons, Ronan Anthony Jones, Hywel Merfyn Moore, Simon
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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