A recently concluded conference on precision medicine at
UCSF pitched a number of promising ideas in the areas of data collection, data
storage, data analysis and technology development, and data use. The mapping of
the human genome sequences, the advent of Big Data Analytics, and the new
mantra of prevention with the citizen as a healthcare stakeholderhas made
possible the field of precision medicine,
the wave of the future. The conference made amply clear "precision medicine as the future of medicine" defining it as the "practice of harnessing technology, science,
and medical records to better understand the roots of disease, develop targeted
therapies, and ultimately save lives."
The ideas coalesced around critical issues of big data
quality, transparency, and portability to realizing the full potential of
precision medicine built around a more granular new taxonomy of diseases involving specific molecular/pathogenic
pathways rather than amorphous "signs and symptoms." Disparate diseases might
share the same molecular/ genetic disruptions in their pathway which opens up
treatment options and improves effectiveness.
With genomic sequencing at its disposal medical science can also chart
out risk probabilities within families and facilitate prevention.
Such specific taxonomies can build on the traditional ICD
classifications which serve clinical and statistical purposes but are either
too static or inadequate in describing the genetic pathways or driver mutations
of diseases. The interlinking of data
from clinical, environmental, behavioral, and socio-economic indexes derived
from comprehensive Electronic Health Records with genomic parameters can form an
Information Commons, i.e., a data
ecosystem derived from millions of patients individualized data from which
pilot studies and large cohort studies can be launched by bio-tech, drug
researchers,clinicians, and every healthcare stakeholder to contribute towards a
Knowledge Network which can be used
to classify diseases on a molecular level, discover disease mechanisms, detect
diseases early and establish accurate diagnosis, measure disease
predisposition, target treatments, develop drugs, and reduce health
disparities. The results from these studies are used to update the Knowledge
Network and validate the disease taxonomy towards a dynamic, sustainable, precise,
and economic healthcare delivery model.
The USA spends approximately 18% of its GDP on healthcare, the costliest in the world, and two times more than the OECD spends but ranks 46th out of 48 countries in healthcare efficiency just ahead of Serbia and Brazil as per a recent Bloomberg study. The challenge is controlling healthcare costs while delivering high-quality care and increasing medical coverage amongst the uninsured.
As David Houle and Jonathan Fleece in the New Health Age
reveal, this is to be achieved by transforming the citizen into a stakeholder in their healthcare
as it revamps from a sickness to a wellness model, creates awareness and understanding, and horizontally integrates. A new generation of informed citizen scientists armed with portable monitoring devices which measure vital signs ranging from blood pressure to oxygen saturation rates collected, analyzed, and uploaded to offsite doctor's offices when red flagged. Citizens receive credits for remaining healthy and in turn, the industry is developing reimbursement codes for keeping them that way to incentivize clinicians. As we saw in the previous blog post
, companies have already jumpstarted the billions of dollars personal health and fitness business with their devices that measure calories, sleep, and impart wellness advice. Such devices make the goal of an Information Commons attainable.
The citizen scientist theme echoed at the conference in such ideas as Me For You
, a social media campaign to raise awareness of precision medicine and targeted therapies by encouraging users to become advocates and share health data and empower patients to advance the field of precision medicine. Data Donor Drive
or D3 envisions a grassroots campaign collecting 1 million genetic data sets from volunteers to develop a database as a launching pad for precision medicine's Knowledge Network. In another citizen scientist endeavor: stool samples, a key health indicator could be collected and analyzed at home under the Smart Toilet initiative thus generating insights into diets, personal genomes, and microbiomes. The "lab into your toilet" could be used to monitor the family's well-being and in addition, help identify prevailing infectious diseases before they reach epidemic proportions.
A citizen stakeholder adds yet another layer to an already multilayered stakeholder landscape in healthcare. This is a welcome development but brings with it the potential for ridiculously high volumes of both high velocity and variety of data which will swallow every conceivable size measure in a matter of seconds.
For e.g., pharmaceutical companies see big data as invaluable in early stage drug discovery, understanding the market, and personalized medicine. While concerns storing and managing data abates, it is data curation to make it meaningful to various stakeholders that is a priority with the next generation tools still nascent. The mission of a well-meaning data scientist is to ensure data provenance and high quality analysis which can unlock a treasure trove of insights that brings us closer to predictability, prevention, and precision and achieves the Knowledge Network's goals as enumerated above.