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The coronavirus disease 2019 (COVID-19) pandemic impacts not only patients but also healthcare providers. This study seeks to investigate whether a telemedicine system reduces physical contact in addressing the COVID-19 pandemic and mitigates nurses' distress and depression.

Evaluate an initiative to distribute video-enabled tablets and cell phones to individuals enrolled in Veterans Health Affairs supportive housing program during the COVID-19 pandemic.

Opioid Overdose Network is an effort to generalize and adapt an existing research data network, the Accrual to Clinical Trials (ACT) Network, to support design of trials for survivors of opioid overdoses presenting to emergency departments (ED). Four institutions (Medical University of South Carolina [MUSC], Dartmouth Medical School [DMS], University of Kentucky [UK], and University of California San Diego [UCSD]) worked to adapt the ACT network. The approach that was [...]

The purpose of this project was to improve ease and speed of physician comprehension when interpreting daily laboratory data for patients admitted within the Military Healthcare System (MHS).

Machine learning has the potential to improve identification of patients for appropriate diagnostic testing and treatment, including those who have rare diseases for which effective treatments are available, such as acute hepatic porphyria (AHP). We trained a machine learning model on 205 571 complete electronic health records from a single medical center based on 30 known cases to identify 22 patients with classic symptoms of AHP that had neither been diagnosed [...]

Tobacco use/smoking for epidemiologic studies is often derived from electronic health record (EHR) data, which may be inaccurate. We previously compared smoking from the United States Veterans Health Administration (VHA) EHR clinical reminder data with survey data and found excellent agreement. However, the smoking clinical reminder items changed October 1, 2018. We sought to use the biomarker salivary cotinine (cotinine ≥30) to validate current smoking from multiple sources.

To improve timely access to quality HIV research data, the Rakai Health Sciences Program (RHSP) Data Mart was developed to store cohort study data from a legacy database platform in a modernized system using standard data management processes. The RHSP Data Mart was developed on a Microsoft SQL Server platform using Microsoft SQL Server Integration Services with custom data mappings and queries. The data mart stores 20+ years of longitudinal [...]

Clinical evidence logic statements (CELS) are shareable knowledge artifacts in a semistructured "If-Then" format that can be used for clinical decision support systems. This project aimed to assess factors facilitating CELS representation.

To implement a dynamic data management and control framework that meets the multiple demands of high data quality, rigorous information technology security, and flexibility to continuously incorporate new methodology for a large disease registry.

Physician burnout is at epidemic proportions, impacts clinical outcomes, and is very costly. Although there is emerging data about effective interventions, most physicians at risk of burnout do not seek help. Survey-based measures exist which can quantify burnout within populations, but these are usually only administered episodically. We hypothesized that a novel modality for real-time measurement of happiness and stressors would be acceptable, scalable, and could provide new actionable insights.