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.

Autor:	Dhanda A; University of Plymouth, Plymouth, UK.; South West Liver Unit, University Hospitals Plymouth NHS Trust, Plymouth, UK., Bodger K; University of Liverpool, Liverpool, UK.; Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK., Hood S; Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK., Henn C; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK., Allison M; Cambridge Liver Unit, Cambridge NIHR Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK., Amasiatu C; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK., Burton R; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK., Cramp M; University of Plymouth, Plymouth, UK.; South West Liver Unit, University Hospitals Plymouth NHS Trust, Plymouth, UK., Forrest E; Glasgow Royal Infirmary, Glasgow, UK., Khetani M; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK., MacGilchrist A; Liver Unit, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK., Masson S; Liver Unit, Newcastle Hospitals NHS Trust, Newcastle, UK., Parker R; Leeds Liver Unit, Leeds Teaching Hospitals NHS Trust, Leeds, UK., Sheron N; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK., Simpson K; Liver Unit, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK., Vergis N; Imperial College London, London, UK.; Research and Development, GlaxoSmithKline (GSK), Hertfordshire, UK., White M; Addiction and Inclusion Directorate, Office for Health Improvement and Disparities, Department for Health and Social Care, London, UK.
Jazyk:	angličtina
Zdroj:	Alimentary pharmacology & therapeutics [Aliment Pharmacol Ther] 2023 Feb; Vol. 57 (4), pp. 368-377. Date of Electronic Publication: 2022 Nov 17.
DOI:	10.1111/apt.17307
Abstrakt:	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 alternative coding patterns (e.g., ArLD secondary diagnosis with alcohol/liver-related primary diagnosis), to national and local datasets in the context of studying trends in ArLD admissions 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 of ArLD-specific admissions increased by 30.4%. Of 39,667 admissions in 2020/21, only 19,949 were identified with standard approach, an estimated admission cost of £70 million in under-recorded cases. Within 28 local hospital datasets, 233 admissions were identified using the standard approach and a further 250 locally verified cases using the LAA (107% uplift). There was an 18% absolute increase in ArLD admissions in the seven-day evaluation period in 2020 versus 2019. There were no differences in disease severity or mortality, or in the proportion of admissions with decompensation of cirrhosis or alcoholic hepatitis. Conclusions: The LAA can be applied successfully to local and national datasets. It consistently identifies approximately 100% more cases than the standard coding approach. The algorithm has revealed the true extent of ArLD admissions. The pandemic has compounded a long-term rise in ArLD admissions and mortality. (© 2022 The Authors. Alimentary Pharmacology & Therapeutics published by John Wiley & Sons Ltd.)
Databáze:	MEDLINE
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