Population health and precision medicine seem like such polar opposites standing 180 degrees apart. But the path to fully realizing the benefits of precision medicine stands to reap rewards for population health along the way. That was the takeaway from an interview with India Hook-Barnard, the director of research strategy and associate director of Precision Medicine at the University of California San Francisco School of Medicine. She talked about the balance between the two areas of healthcare in an interview in Boston after she spoke at the HIMSS Precision Medicine Summit this week.
Hook-Barnard called attention to a list of projects related to precision medicine. They included the Cell Cancer Map Initiative to discover molecular networks of cancer, the University of California Data Warehouse to connect 15 million electronic health records across the University of California health system, a Biobank that seeks to simplify the informed consent process and the Scalable Precision Open Knowledge Engine.
“All of these projects are helping to advance precision medicine in different ways. They will enable us to more quickly make discoveries, provide better care, but also make better decisions in public health.”
She called attention to some of the work of her colleagues. Atul Butte is the first director for the Institute of Computational Health Sciences. Among his many roles, he is one of the leaders of the University of California Data Warehouse. Among their tasks are to address privacy and security issues for making data from those records accessible across health systems plugged into the University of California network.
“They’re looking at being able to repurpose drugs, what will really provide better outcomes. It will be really huge being able to connect that kind of data and use it in a healthcare space and research space.”
The San Francisco Cancer Initiative, is about sharing information for what works and what doesn’t work for five types of cancer with the highest cost burden: prostate, breast, liver, colorectal and tobacco-related cancers. Each will be assigned a taskforce, Hook-Barnard said. The public-private partnership launched last year with a $3 million investment from a donor to the UCSF Helen Diller Family Comprehensive Cancer Center. The initiative is led by Dr. Robert Hiatt, the chair of the Department of Epidemiology and Biostatistics at UCSF. He authored a report on health disparities for cancer treatment outcomes.
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Hook-Barnard described what the program seeks to accomplish using tobacco-related cancer as an example, and highlighted some of the questions the initiative seeks to address in this area. Social determinants of health will also come into play.
“We know the dangers of smoking and the impact of it, yet there are certain communities…that are still developing lung cancer at much higher rate than others. Why is that? Is the messaging on prevention not resonating? Are cessation efforts not tailored enough to be effective? Is access to early screening for detection in certain neighborhoods [the problem]? Being able to tailor those kinds of preventive messaging, early screenings, diagnostics and access, could improve earlier access to treatment.”
The Molecular Oncology initiative led by Michael Korn of UCSF is yet another initiative. The website offers this description of the UCSF500 gene panel assay the laboratory conducts.
…a cutting-edge sequencing test that, in contrast with commercial cancer gene panel tests, sequences tumor DNA and the patient’s germline (inherited) DNA. This unique component of the UCSF500 molecular diagnostic test enables identification of genetic changes (mutations) in the DNA of a patient’s cancer, which helps oncologists improve treatment by identifying targeted therapies, or appropriate clinical trials, or in some cases clarify the exact type of cancer a patient has.
Although it is about using genomics in the clinic to get a more precise diagnosis, the goal of the initiative is to solve some of the wider questions that often go unanswered and to make sure that data isn’t locked in a silo somewhere. What treatment(s) worked and why?
“How do we capture that information to make sure that is shared and duplicated? We want to make sure those lessons, those findings…once you have that piece of knowledge, how do you make sure it is shared with other medical centers? For precision medicine to work, it is about these different kinds of data and acquiring knowledge we need to enable data sharing.”
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