Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data - Trefan, Laszlo; Akbari, Ashley; Morgan, Jennifer Siân; Farewell, Daniel Mark; Fone, David; Lyons, Ronan A; Jones, Hywel Merfyn; Moore, Simon (International Journal of Population Data Science, 2021)
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.