Author information

¹Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA.

²Division of Gastroenterology, University of Michigan Health System, 3912 Taubman, SPC 5362, 1500 E Medical Center Dr, Ann Arbor, MI, 48109, USA. etapper@med.umich.edu.

Abstract

It remains challenging to identify covert hepatic encephalopathy and predict progression to overt hepatic encephalopathy. Psychometric testing is a widely used diagnostic modality, but it is often inaccurate and difficult to implement in diverse populations, making it a less than ideal assessment. Alternatively, by using easily accessible data from the electronic health record, simple clinical assessment tools, and patient-reported outcomes, we may be better able to predict hepatic encephalopathy across multiple populations. Furthermore, incorporation of patient-reported outcomes into our diagnostic toolset not only aids detection of covert hepatic encephalopathy and prediction of overt hepatic encephalopathy, but also allows us to target therapies and track their impact. Herein, we outline a potential algorithm based on these easily integrated tools to promote patient risk-stratification and early therapeutic intervention.