Clinical Research Informatics, EHR data extraction, Registry and Population Management, Data Analytics, IT Project Management
Senior Project Manager
Arielle M. Fisher, Timothy M. Mtonga, Jeremy U. Espino, Lauren J. Jonkman, Sharon E. Connor, Nickie K. Cappella and Gerald P. Douglas. User-centered design and usability testing of RxMAGIC: a prescription management and general inventory control system for free clinic dispensaries. BMC Health Services Research 2018 18:703.
The PaTH Clinical Data Research Network (CDRN), funded by the Patient-Centered Outcomes Research Institute (PCORI), is a collaboration between the University of Pittsburgh, UPMC, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Lewis Katz School of Medicine at Temple University, Temple Health, Johns Hopkins University, Johns Hopkins Health System, Geisinger Health System, and University of Utah Heath Care. The network’s combined resources follow a longitudinal cohort of approximately 10 million diverse individuals across a variety of health care settings to maximize the ability to conduct meaningful patient-centered outcomes research and develop a learning health system to which patients and providers jointly contribute. PaTH uses clinical data from electronic health records (EHR) and patient reported outcomes (PRO) to answer questions of clinical importance to patients, providers, and other stakeholders. Expected outcomes of the CDRN are to conduct patient-centered observational studies on weight across the multiple institutions, and to answer patient-centered research questions regarding recruitment techniques, patients’ weight management strategies, and how health care providers contribute to their weight management approaches.
The National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH) transforms the translational science process for more efficient patient access to healthcare innovations. NCATS’ mission “strives to develop innovations to reduce, remove, or bypass costly and time-consuming bottlenecks in the translational research pipeline in an effort to speed the delivery of new drugs, diagnostics and medical devices to patients,” and provides funding support for the University of Pittsburgh’s CTSA program. The Biomedical Informatics Core provides informatics support and, in particular, supports maintenance of the Accrual of patients to Clinical Trials (ACT) data repository network that enables cohort identification for clinical trial accrual across 21 CTSA sites.
The Center for Causal Discovery (CCD), funded by the Big Data to Knowledge (BD2K) initiative of the NIH, is led by Drs. Gregory Cooper, Ivet Bahar, Jeremy Berg, and Clark Glymour and represents a partnership among data scientists from the University of Pittsburgh (Pitt), Carnegie Mellon University (CMU), and the Pittsburgh Supercomputing Center (PSC) to develop the algorithms, software, and system architecture needed by biomedical scientists seeking to discover causal relationships in large biomedical data sets. The Consortium component of the CCD, led by Dr. Michael Becich, disseminates CCD products and data- and software-sharing best practices to the Consortium and data science community while developing partnerships with other BD2K Centers. The Consortium encompasses the Scientific and Technical Catalyst programs. Our Scientific Catalyst act as hub persons at partner sites who then broadcast our activities to other investigators so that they can utilize training opportunities, software tools and other useful artifacts coming out of the center. Technical Catalysts periodically visit each BD2K Center of Excellence and prepare a technical report discussing opportunities for enhancing interoperability between CCD and the site visited as well as potential collaborative projects. Together, these two programs propagate and oversee the CCD standards based metadata implementation and promote novel methods to analyze Big Data.
Pitt Data Commons:
Led by Dr. Michael Becich (Biomedical Informatics), and Dr. Liz Lyons (Information Science), the goal of the Pitt Data Commons initiative is to create a partnership with many of the computational and information entities across the University of Pittsburgh to develop a “data commons” that will serve teaching, research and library needs for information (data/data science) and informatics expertise/methods/tools in the greater Pittsburgh region.
The National Mesothelioma Virtual Bank (NMVB) is a virtual biospecimen registry designed to support and facilitate basic science, clinical, and translational research that will advance understanding of mesothelioma pathophysiology with the goal of expediting the discovery of preventive measures, novel therapeutic interventions, and ultimately, cures for mesothelioma. Funding for the NMVB is provided by The National Institute for Occupational Safety and Health (NIOSH) at the Centers for Disease Control and Prevention (CDC).