# Impact of the COVID-19 pandemic on patient outcomes, telehealth care delivery, and treatment for unhealthy alcohol use in vulnerable patients with advanced liver disease across two healthcare systems

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $708,716

## Abstract

PROJECT SUMMARY
The COVID-19 pandemic has had a significant adverse impact on vulnerable populations with serious comorbid
medical conditions. Individuals with advanced chronic liver disease (CLD) are among those most strongly
affected by disruptions in care and are also highly susceptible to poor outcomes associated with SARS-CoV-2
infection. It is critical to understand how to effectively manage these patients during the course of the pandemic.
The rising prevalence of cirrhosis, an end-stage of CLD, is a significant contributor to morbidity and mortality in
the United States and alcohol use is a major risk factor. Thus, effective intervention for alcohol cessation is a
high-priority need. In addition, high quality advanced CLD with adherence to known quality indicators is
associated with positive patient outcomes, critical to enhanced survival, and quality of life. Vulnerable populations
including veterans and those receiving care in safety net systems are at significant risk for liver and COVID-19
related health disparities. They also have known barriers to healthcare access and are at high risk for
disengagement from care. The COVID-19 pandemic has significantly disrupted the traditional health care
delivery models, but the impact on outcomes of vulnerable patients with advanced CLD is currently unknown.
Moreover, the widespread use of telemedicine as a mitigation strategy within these health systems due to
COVID-19 has provided an unprecedented opportunity for evaluation and innovation of care delivery models.
Better understanding of patients' experience with telemedicine and impact on their outcomes is urgently needed
to establish processes and polices that ensure equity in access, sustainability, and high-quality care delivery.
To address these critical issues, we propose to evaluate the care of patients with advanced CLD during the
pandemic within hepatology practices in two generalizable health systems serving vulnerable populations, a
public safety net system and Veterans Affairs healthcare systems. Furthermore, we will examine the efficacy of
a stepped care intervention (i.e., motivational interviewing and addiction physician management) via
telemedicine to treat alcohol use as an adjunct to usual hepatology care. We will also examine COVID-19
outcomes. We propose the following aims: 1) Evaluate the impact of the COVID-19 pandemic on clinical
outcomes of vulnerable patients with advanced CLD receiving care in hepatology practices, in a natural
experiment; 2) Evaluate patient-reported experiences with use of telemedicine in response to the pandemic to
deliver hepatology specialty care in those with advanced CLD; and 3) Conduct a randomized controlled trial
evaluating the efficacy and feasibility of a stepped alcohol treatment using telemedicine on unhealthy alcohol
use in patients with alcohol-related CLD receiving care in hepatology practices, compared with usual care. We
hypothesize that we will observe an increase in adverse patient...

## Key facts

- **NIH application ID:** 10249625
- **Project number:** 1R01AA029312-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Mandana Khalili
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $708,716
- **Award type:** 1
- **Project period:** 2021-06-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10249625

## Citation

> US National Institutes of Health, RePORTER application 10249625, Impact of the COVID-19 pandemic on patient outcomes, telehealth care delivery, and treatment for unhealthy alcohol use in vulnerable patients with advanced liver disease across two healthcare systems (1R01AA029312-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10249625. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*