麻豆传媒AV

Citation

Dhanda A, Bodger K, Hood S, Henn C, Allison M, Amasiatu C, Burton R, Cramp M, Forrest E, Khetani M, MacGilchrist A, Masson S, Parker R, Sheron N & Simpson K (2023) The Liverpool alcohol-related liver disease algorithm identifies twice as many emergency admissions compared to standard methods when applied to Hospital Episode Statistics for England. Alimentary Pharmacology & Therapeutics, 57 (4), pp. 368-377. https://doi.org/10.1111/apt.17307

Abstract
Background: Emergency admissions in England for alcohol-related liver disease(ArLD) have increased steadily for decades. Statistics based on administrative datatypically focus on the ArLD-specific code as the primary diagnosis and are thereforeat risk of excluding ArLD admissions defined by other coding combinations.Aim: To deploy the Liverpool ArLD Algorithm (LAA), which accounts for alternativecoding patterns (e.g., ArLD secondary diagnosis with alcohol/liver-related primarydiagnosis), to national and local datasets in the context of studying trends in ArLDadmissions before and during the COVID-19 pandemic.Methods: We applied the standard approach and LAA to Hospital Episode Statisticsfor England (2013–21). The algorithm was also deployed at 28 hospitals to dischargecoding for emergency admissions during a common 7-day period in 2019 and 2020,in which eligible patient records were reviewed manually to verify the diagnosis andextract data.Results: Nationally, LAA identified approximately 100% more monthly emergencyadmissions from 2013 to 2021 than the standard method. The annual number ofArLD-specific admissions increased by 30.4%. Of 39,667 admissions in 2020/21, only19,949 were identified with standard approach, an estimated admission cost of ?70million in under-recorded cases. Within 28 local hospital datasets, 233 admissions were identified using the standard approach and a further 250 locally verified cases Background: Emergency admissions in England for alcohol-related liver disease(ArLD) have increased steadily for decades. Statistics based on administrative data typically focus on the ArLD-specific code as the primary diagnosis and are therefore at risk of excluding ArLD admissions defined by other coding combinations.Aim: To deploy the Liverpool ArLD Algorithm (LAA), which accounts for alternativecoding patterns (e.g., ArLD secondary diagnosis with alcohol/liver-related primary diagnosis), to national and local datasets in the context of studying trends in ArLDadmissions before and during the COVID-19 pandemic.Methods: We applied the standard approach and LAA to Hospital Episode Statistics for England (2013–21). The algorithm was also deployed at 28 hospitals to discharge coding for emergency admissions during a common 7-day period in 2019 and 2020,in which eligible patient records were reviewed manually to verify the diagnosis and extract data.Results: Nationally, LAA identified approximately 100% more monthly emergency admissions from 2013 to 2021 than the standard method. The annual number f ArLD-specific admissions increased by 30.4%. Of 39,667 admissions in 2020/21, only19,949 were identified with standard approach, an estimated admission cost of ?70million in under-recorded cases. Within 28 local hospital datasets, 233 admissions were identified using the standard approach and a further 250 locally verified cases

Journal
Alimentary Pharmacology & Therapeutics: Volume 57, Issue 4

• Aliment Pharmacol Ther - 2022 - Dhanda - The Liverpool Alcohol ? Related Liver Disease Algorithm Identifies Twice As Many