P126 Improving patient outcomes in decompensated liver disease through remote monitoring: a real-world experience

<h3>Introduction</h3> The rate of deaths from liver disease has gone up 40% from 2001 to 2022.<sup>1</sup> The COVID-19 pandemic in 2020 accelerated the mortality rate in patients with cirrhosis by 3.5-fold and has led to increased number of patients admitted with decompensated liver disease. Digital remote monitoring of patients with cirrhosis has been trialled and deemed to be safe and effective. The aim of this study was to demonstrate the impact of real-world remote monitoring of patients with decompensated cirrhosis. <h3>Methods</h3> Patients with decompensated cirrhosis with ascites were remotely monitored for six weeks post-discharge via DOCCLA’s digital platform. The patients reported data such as weight, temperature, pulse rate, blood pressure, and symptoms through a digital application. The study included 43 patients from May to December 2023 and compared the results with a control group of 39 patients from the same period in 2022. Statistical analyses included Pearson’s Chi-squared test, Fisher’s exact test, and a 2-sample test for equality of proportions, with relevant post-hoc tests. <h3>Results</h3> No significant differences were observed between the study and control groups in terms of ethnicity, aetiology, age, Child-Pugh score, and MELD score. However, the study group had a higher proportion of males (65% vs 41%). A total of 10% of patients failed the onboarding process, but all who completed it finished their six-week study period. The implementation of the virtual platform resulted in a 6% reduction in clinic follow-ups. The study group had a higher number of planned Large Volume Paracentesis (LVPs) (65% vs 15%, p&lt;0.001) and fewer emergency admissions (12% vs 28%, p&lt;0.001) compared to the control group. At the 30-day mark, the study group had fewer decompensated patients than the control group (58% vs 87%, p&lt;0.05). By 90 days, the study group had a higher number of recompensated patients (26% vs 6%, p&lt;0.05), fewer decompensated patients (47% vs 72%, p&lt;0.05), and fewer liver-related deaths (5% vs 10%, p&lt;0.05) than the control group <h3>Discussion</h3> This is the first real world study of remote monitoring of decompensated cirrhotic patients in the UK. This has demonstrated a significant reduction in emergency hospital readmissions and improved 30-day and 90-day clinical outcome. Remote monitoring services can be embedded in the NHS to reduce the burden of inpatient care of liver disease and to improve patient outcomes by better patient engagement and monitoring. <h3>Reference</h3> https://www.gov.uk/government/statistics/liver-disease-profile-april-2024-update

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Published
2024-10-01
DOI
https://doi.org/10.1136/gutjnl-2024-basl.129
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Artificial Intelligence in Healthcare
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article
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article

P126 Improving patient outcomes in decompensated liver disease through remote monitoring: a real-world experience

Julia Crone, Aravind Sunderavel Kumaravel Kanagavelu, Vikram Sharma, Katie Ballesteros et al.
Artificial Intelligence in Healthcare
article

P126 Improving patient outcomes in decompensated liver disease through remote monitoring: a real-world experience

Julia Crone, Aravind Sunderavel Kumaravel Kanagavelu, Vikram Sharma, Katie Ballesteros, Raha Abdul Rahman, Arturo Schlitzer
article en

Abstract

<h3>Introduction</h3> The rate of deaths from liver disease has gone up 40% from 2001 to 2022.<sup>1</sup> The COVID-19 pandemic in 2020 accelerated the mortality rate in patients with cirrhosis by 3.5-fold and has led to increased number of patients admitted with decompensated liver disease. Digital remote monitoring of patients with cirrhosis has been trialled and deemed to be safe and effective. The aim of this study was to demonstrate the impact of real-world remote monitoring of patients with decompensated cirrhosis. <h3>Methods</h3> Patients with decompensated cirrhosis with ascites were remotely monitored for six weeks post-discharge via DOCCLA’s digital platform. The patients reported data such as weight, temperature, pulse rate, blood pressure, and symptoms through a digital application. The study included 43 patients from May to December 2023 and compared the results with a control group of 39 patients from the same period in 2022. Statistical analyses included Pearson’s Chi-squared test, Fisher’s exact test, and a 2-sample test for equality of proportions, with relevant post-hoc tests. <h3>Results</h3> No significant differences were observed between the study and control groups in terms of ethnicity, aetiology, age, Child-Pugh score, and MELD score. However, the study group had a higher proportion of males (65% vs 41%). A total of 10% of patients failed the onboarding process, but all who completed it finished their six-week study period. The implementation of the virtual platform resulted in a 6% reduction in clinic follow-ups. The study group had a higher number of planned Large Volume Paracentesis (LVPs) (65% vs 15%, p&lt;0.001) and fewer emergency admissions (12% vs 28%, p&lt;0.001) compared to the control group. At the 30-day mark, the study group had fewer decompensated patients than the control group (58% vs 87%, p&lt;0.05). By 90 days, the study group had a higher number of recompensated patients (26% vs 6%, p&lt;0.05), fewer decompensated patients (47% vs 72%, p&lt;0.05), and fewer liver-related deaths (5% vs 10%, p&lt;0.05) than the control group <h3>Discussion</h3> This is the first real world study of remote monitoring of decompensated cirrhotic patients in the UK. This has demonstrated a significant reduction in emergency hospital readmissions and improved 30-day and 90-day clinical outcome. Remote monitoring services can be embedded in the NHS to reduce the burden of inpatient care of liver disease and to improve patient outcomes by better patient engagement and monitoring. <h3>Reference</h3> https://www.gov.uk/government/statistics/liver-disease-profile-april-2024-update

Barts Health NHS Trust (GB), Royal London Hospital (GB), Virtual High School (US)
Openalex Percentile: Top 76%
Artificial Intelligence in Healthcare
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