MedML: Fusing medical knowledge and machine learning models for early pediatric COVID-19 hospitalization and severity prediction.

The COVID-19 pandemic has caused devastating economic and social disruption. This has led to a nationwide call for models to predict hospitalization and severe illness in patients with COVID-19 to inform the distribution of limited healthcare resources. To address this challenge, we propose a machine learning model, MedML, to conduct the hospitalization and severity prediction for the pediatric population using electronic health records.

Designing mental health promotion campaigns: segmenting U.S. Veteran audiences to address public stigma.

Background: Public stigma is a significant deterrent to mental health service use for U.S. veterans.

Trends in comorbid opioid and stimulant use disorders among Veterans receiving care from the Veterans Health Administration, 2005-2019.

Background: Identifying solutions to the continued rise in overdose deaths is a public health priority. However, there is evidence of change in recent substance type associated with morbidity and mortality. To better understand the continued rise in overdose deaths, in particular those attributed to opioid and stimulant use disorders, increased knowledge of patterns of use is needed.

Causes of death among U.S. Veterans with a prior nonfatal opioid overdose.

Background: For over a decade, there has been a surge in opioid-related morbidity and mortality among Veterans. To better understand the impact of the growing epidemic, it is important to identify the cause-specific mortality rates among Veterans with a prior nonfatal opioid overdose.

Methods: We followed 8370 Veterans who received medical care for a nonfatal opioid overdose between 2011 through 2015.

The next wave? Mental health comorbidities and patients with substance use disorders in under-resourced and rural areas.

The rapid spread of the coronavirus disease (COVID-19) has impacted the lives of millions around the globe. The COVID-19 pandemic has caused increasing concern among treatment professionals about mental health and risky substance use, especially among those who are struggling with a substance use disorder (SUD). The pandemic's impact on those with an SUD may be heightened in vulnerable communities, such as those living in under-resourced and rural areas.

Opioid-Related Outcomes in West Virginia, 2008-2016.

Objectives: To examine opioid-related outcomes by using hospitalization and mortality data as an indicator of the current opioid crisis in West Virginia.

Methods: We used data from the West Virginia University Medicine health care system to examine the trend in opioid overdoses and percentage of patients with a repeat overdose from 2008 to 2016. We obtained the opioid overdose death rate for the state from Centers for Disease Control and Prevention WONDER (Wide-ranging ONline Data for Epidemiologic Research) mortality data for 2008 to 2016.