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


Journal

International journal of population data science
ISSN: 2399-4908
Titre abrégé: Int J Popul Data Sci
Pays: Wales
ID NLM: 101737740

Informations de publication

Date de publication:
24 Mar 2021
Historique:
entrez: 19 5 2021
pubmed: 20 5 2021
medline: 20 5 2021
Statut: epublish

Résumé

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. 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. 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. There was agreement between admission and discharge codes. When more than ten coding fields were used the misclassification rate was less than 1%. 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.

Identifiants

pubmed: 34007894
doi: 10.23889/ijpds.v6i1.1373
pii: S2399490821013732
pmc: PMC8103565
doi:

Substances chimiques

Ethanol 3K9958V90M

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Pagination

1373

Déclaration de conflit d'intérêts

Conflict of interests: The authors declare that they do not have any conflict of interest.

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Auteurs

Laszl Trefan (L)

Honorary Research Associate, Division of Population Medicine, School of Medicine, Cardiff University, Cardiff CF14 4YS.

Ashley Akbari (A)

Senior Research Manager and Data Scientist, Health Data Research UK Wales and Northern Ireland, Swansea University Medical School, Institute of Life Science 2, Sketty, Swansea SA2 8QA.

Jennifer Siân Morgan (JS)

Performance Analysis Manager, NHS Wales Delivery Unit, Pencoed, Bridgend CF35 5LJ.

Daniel Mark Farewell (DM)

Senior Lecturer, Division of Population Medicine, School of Medicine, Cardiff University, Cardiff CF14 4YS.

David Fone (D)

Retired professor, Division of Population Medicine, School of Medicine, Cardiff University, Cardiff CF14 4YS.

Ronan A Lyons (RA)

Professor, Health Data Research UK Wales and Northern Ireland, Swansea University Medical School, Institute of Life Science 2, Sketty, Swansea SA2 8QA.

Merfyn Jones Hywel (M)

Research Associate / Statistician, Division of Population Medicine, Cardiff University, Cardiff CF14 4YS.

Simon C Moore (SC)

Professor of Public Health Research, Crime and Security Research Institute and School of Dentistry, Cardiff University, Cardiff CF14 4XY.

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