Lab News

April 2022

There is always something to celebrate at the Boussard Lab. Today we celebrate many successes: qualifying examinations, Masters thesis project, birthdays and home ownership. Congratulations to all!

November 2022

Read the Healthcare IT news article that featured the Boussard Lab team that studied the link between first opioid prescription and dependency. The study applied machine learning algorithms to a unique database of millions of de-identified claims.

November 2022

Join Dr. Hernandez-Boussard in the Prescription Drug Monitoring Porgram Training and Technical Assistance Center webinar on November 3, 2022. The webinar will cover the methods and results for the reearch study on predicting the progression from acute to chronic opioid use.

Recent Publications

Artificial Intelligence–Enabled Analysis of Statin-Related Topics and Sentiments on Social Media

In this qualitative study of 10,233 unique statin-related discussions, an AI pipeline was developed to analyze these discussions, which were automatically categorized into 100 topics and 6 thematic groups. Sentiment analysis of these discussions showed that most of them had a neutral or negative sentiment. Findings from this study suggest that AI-enabled analysis of social media data may generate insights into public perceptions and help guide strategies for addressing barriers to statin use and adherence.

Predictors of Incident Heart Failure Diagnosis Setting: Insights From the Veterans Affairs Healthcare System

Heart failure (HF) mortality exceeds 20% in the first year after diagnosis.1 Although medical treatment decreases mortality and increases quality of life, particularly among those with reduced ejection fraction (EF), these improvements are enhanced with timely diagnosis and therapy initiation. Early recognition of heart failure (HF) can reduce morbidity, yet HF is often diagnosed only after symptoms require urgent treatment. In this paper, we sought to describe predictors of HF diagnosis in the acute care vs outpatient setting within the Veterans Health Administration (VHA).