How one project is closing the loop of health data to transform the future of medicine.
Are you healthy? It’s a simple, yet difficult question to answer. In 1948, the World Health Organization defined ‘health’ as a “state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.” Nearly 70 years later, we still are trying to define what is a baseline state of “health,” as primary care continues to reactively address medical issues.
“We continue as a global community to think about health primarily only after becoming ill,” said Sanjiv Sam Gambhir, MD, PhD, professor and chair of radiology at Stanford. “To understand health and illness effectively, we have to have a better understanding of what ‘normal’ or ‘healthy’ really means at the biochemical level.”
Project Baseline is trying to answer this question. Led by Duke University, Stanford Medicine, and Verily (formerly Google Life Sciences), the project is amassing massive amounts of data over a longitudinal, observational study of 10,000 participants during a four-year period to better understand health and disease. What makes this study unique: it’s closing the loop of health data in a continuous feedback system. Participants are constantly sharing information with researchers through self-reported behavior, onsite visits, and sensor technology that monitors their heart rates, movements, sweat levels, and sleeping habits — long after they’ve left the doctors offices.
This study is yet another chapter in a paradigm shift in health care: moving away from reactive medicine towards a proactive approach that uses a patient’s holistic health data to prevent disease before it starts. The implications of this study’s use of big data goes beyond just preventative measures for a patient’s health; according to Stanford’s first health trend report, the information generally can fuel drug discovery, make research more efficient, optimize patient experiences, and enable doctors to build better patient profiles and predictive models.
“The building blocks of a digital revolution in medicine have already happened,” says Joshua McKenty, vice president of global ecosystem engineering at Pivotal. “We already have the use of smartphones as sensors and medical devices for collecting medical data in telemedicine, we have the early signs that wearables and Fitbit and contact lenses and all these things are commercially acceptable, both to medical professionals and to consumers.”
But while the breakthrough data may be available to transform medicine, an organizational shift is necessary to ingest, utilize, and secure that data.
“Maximizing the potential of big data in health care will require two things — a data literate workforce that can understand how to work with and interpret complex data, and organizational investments in infrastructure, analytical tools and data governance solutions,” said Dr. Lloyd B. Minor, Dean of the Stanford University School of Medicine.
Operationalizing Health Care of the Future
If healthcare providers continue to manage their traditional input systems with paper records, while also trying to capture data using digital tools — they will have no time to gain value through analysis of the new data captured, argues McKenty.
If these news data streams are fully embraced through tools and analysis, McKenty believes the health industry can be optimized much in the same way Lyft and Uber optimized the cab industry. Drivers waste less time because routes are optimized, they don’t have to clear rides with dispatch, track how far they went, collect money, and so forth. One Medical, a venture-capital backed primary care provider, is already simplifying their operational processes, creating a flexible care experiences that leverages telemedicine, online booking systems, and other tools.
“This has always been the goal of medical clinics — to have the doctor spend most of their time on diagnosis, recommendations and treatment, and consultation with the patient — not updating charts and booking appointments or calling to confirm, cancel, or request prescriptions.”
But to close this feedback loop of health data, simplifying operations — which in turn frees up resources to analyze the influx of new patient data — requires that the medical industry incorporate new skillsets. Stanford’s Department of Biomedical Data Science (DBDS) is trying to do just that: teaching doctors and researchers how to utilize medical data in practical ways.
“The healthcare sector is collecting vast amounts of data, but we can’t draw meaningful insights if we lack technical expertise and proper tools,” said Minor. “Improving skills and literacy in computing and analytics, data management and assessment, information processing, and software and technology infrastructure development will be vital if the medical profession is to take advantage of the benefits of big data.”
There still also remain hurdles around interoperability and policy. According to the Health Trend Report, there’s popular sentiment towards policy interventions to address many of the legislative challenges faced by health care.
“Policy often does not move fast enough to keep up with innovation, so legislative bodies will need to work to address issues like data privacy and interoperability while maintaining a regulatory environment that encourages innovation and research,” said Minor. “We must eliminate potential roadblocks that prevent effective data sharing, while still prioritizing the protection of privacy and security of patient data.”
Security and privacy remain primary concerns, especially in light of this year’s recent WannaCry ransomware attacks. While experts are aiming for more collaborative data sharing across the industry, a critical obstacle to overcome is ensuring patients’ data stays secure and private.
Though questions remain around security and policy, to answer the question of what is “healthy” it seems clear that we’ll need to find ways to close the information loop by tapping, accessing, utilizing, and sharing data continuously.
If you’re interested, you can apply to be part of Project Baseline’s study.
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