Description
The purpose of this study is to evaluate and rank-order generic substitution rates by therapeutic class, as well as examine factors associated with higher or lower rates of generic substitution.
PI is Jodi B. Segal, MD, MPH, Johns Hopkins School of Medicine.
PI is Jodi B. Segal, MD, MPH, Johns Hopkins School of Medicine.
Principal Investigator
External PI, Principal Investigator
Funder
U.S. Food and Drug Administration
Related Studies
The Impact of Smoking, Comorbidities, and Race/Ethnicity on COVID-19 Infection and Disease Severity
Using EHR from a large healthcare system in Northern CA, we will study the impact of smoking, comorbidities, race on COVID-19 infection and disease severity.
Investigator: Jiang Li, Ph.D., MPH
COVID-19 Universal Registry for Vital Evaluations (CURVE) Project
To create a COVID-19 Universal Registry for Vital Evaluations (CURVE) database, a semi-real-time registry of Sutter Health patients with COVID-19 infection.
Investigator: Jiang Li, Ph.D., MPH
Statin Use and Risk Prediction of Atherosclerotic Cardiovascular Disease in Minority Subgroups (SURPASS) Study
Overall goal of this study is to address gaps in knowledge about CVD prediction and treatment in understudied racial/ethnic minority populations.
Investigators: External PI, Principal Investigator, Jiang Li, Ph.D., MPH
Pilot Project in Applied Artificial Intelligence: Using Machine Learning to Improve the Safety of Hospital Care
Develop and test predictive model identifying emerging sepsis using artificial intelligence, and translate learnings into improved operational criteria.
Investigator: Sylvia Sudat, PhD
Quantifying 2D and 3D MRI Imaging For Improving MS Diagnosis, Treatment, And Clinical Care
Create a longitudinal proof-of-concept MS research database (MSClinQ) that can support clinical queries, and can be updated with new tx, dx tools, care options
Investigators: J.B. Jones, PhD, MBA, Xiaowei (Sherry) Yan, PhD, MS
Improving Cancer Care
Project will provide information about referrals to palliative care and way to enhance goals of care discussions for patients diagnosed with stage IV cancer.
Investigator: Su-Ying Liang, Ph.D.
Using Mobile Technology and Analytics to Track Outcomes in MS Patients
Develop an app to collect and transform pt-reported outcomes in MS for health care providers to improve care and support shared decision making.
Investigators: J.B. Jones, PhD, MBA, Xiaowei (Sherry) Yan, PhD, MS
Randomized study of EHR Defaults and Using social Comparison feedback to effectively decrease opioid prescription pill burden (REDUCE).
Randomized trial to explore two behavioral economic intervention--changing opioid Rx default and providing social comparison feedback to MDs on opioid pills Rx.
Investigator: Xiaowei (Sherry) Yan, PhD, MS
Major Depressive Disorder
Purpose is to use EHR to understand the management of major depressive disorder in a large healthcare system, to incorporate pt-reported data in care workflow.
Investigator: Kristen M.J. Azar, R.N., BSN, MSN/MPH
Interpretable Deep Learning Model for Longitudinal Electronic Health Record and Applications to Heart Failure Prediction
Develop advanced deep learning model to predict early onset heart failure using EHRs, including structured and unstructured data.
Investigators: Xiaowei (Sherry) Yan, PhD, MS, External PI, Principal Investigator