UC San Diego and Verizon Team to Improve Tuberculosis Care

Verizon Foundation to provide grant and in-kind technology solutions to scale up novel approach to monitoring adherence to TB treatment

As part of an innovative philanthropic health care program targeting reduction of health care disparities in diverse communities around the United States, the Verizon Foundation has provided the University of California, San Diego School of Medicine with a $300,000 grant, as well as important in-kind health information technology solutions.

The support from Verizon will allow researchers from the University to more quickly scale-up a mobile phone-based solution that they developed to overcome the high cost and other barriers to monitoring tuberculosis patients throughout their treatment…. Read the full story from the UCSD Newsroom


Dr. Richard GarfeinLeading the program is Richard Garfein, PhD, MPH, left, professor of medicine in the Division of Global Public Health. Dr. Garfein, an infectious disease epidemiologist, joined the UC San Diego faculty from the Centers for Disease Control and Prevention in 2005.

He is conducting the project in collaboration with the California Institute for Telecommunications and Information Technology (Calit2).

Demonstration of "video directly observed therapy"At right, Dr. Garfein’s daughter demonstrates a smartphone video app that makes it possible for a distant clinician to confirm that a patient has taken a dose of tuberculosis medication.

The approach is called “video directly observed therapy” (VDOT). Dr. Garfein and collaborators have demonstrated the feasibility, acceptability and potential efficacy of VDOT in an NIH-funded pilot study in San Diego and Tijuana. Their mHealth Summit Meeting abstract for the project is published in the Journal of Mobile Technology in Medicine.

In the next six months, with the Verizon Foundation’s assistance, they will expand the VDOT smartphone app for broader use.

Dr. Steffanie Strathdee“This is a new and exciting direction and a new funding source for UCSD,” said Steffanie Strathdee, PhD, Associate Dean of Global Health Sciences and Harold Simon Professor and Chief of the UC San Diego Division of Global Public Health.

She directs the UC San Diego Global Health Initiative and is founding co-director of the UC Global Health Institute’s Center for Migration and Health.

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DELPHI Project Foretells Future of Personalized Population Health

NSF awards $2 million over four years to UC San Diego computer scientists and physicians

Imagine a new type of healthcare app that does it all – it helps you understand your current health status, assists you in making changes in your life to improve your health, and takes into account the perspective of your entire life history, others in your age group–and perhaps even your neighborhood– who share similar characteristics.

That’s the vision put forward by a team of physicians and computer scientists at the University of California, San Diego who are collaborating on a new digital resource that would take advantage of advances in databases, cyberinfrastructure and machine learning to usher in a new era of health and health care…. Read the full story from the UCSD Newsroom


Dr. Lucila Ohno-MachadoLucila Ohno-Machado, MD, PhD, FACMI, is an investigator on the project, whose title is “Data E-platform Leveraged for Patient Empowerment and Population Health Improvement (DELPHI).”

Dr. Ohno-Machado is professor of medicine and founding chief of the Division of Biomedical Informatics. She directs, among other projects, another UCSD biomedical cyberinfrastructure, the Integrating Data for Analysis, Anonymizing and Sharing (iDASH) project. IDASH is a National Center for Biomedical Computing under the auspices of the NIH Roadmap for Bioinformatics and Computational Biology. Under AHRQ funding, she directs the related project Scalable National Network for Effectiveness Research (SCANNER).

Dr. Ohno-Machado’s research specialty is predictive modeling with an emphasis on calibration methods that combine phenotype and genotype/gene expression data for personalized medicine.

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