2014 was the most exciting year in digital health since 2000, when the human genome was cloned. In February 2001, The Human Genome Project and Craig Venter’s Celera Genomics published the hallmark event. What followed was over a decade of glimmers of the potential for personalized medicine and new insights into disease, but also realistic mitigations in expectations, as is wont to happen in health care.
There is every indication that the next decade will be different — there will be an acceleration in innovation and development of devices to assess our healthy and ailing selves. What happened in 2014? A huge increase in funding and corporate investment in digital health technology (e.g., mobile, social media, genetics and big data), and massive growth in the accessible population, and the amount of open data:
Funding in digital health startups, tracked by an accelerator Rock Health since 2011, has grown steadily at double digit growth until this past year, when records were shattered with $4.1B in funding, more than double the 2013 amount.
Almost every major consumer technology company announced a large health initiative, notably Google, Apple, and Samsung.
Electronic health record and sensors were positioned to join or actually entered the “Internet of Things”. The partnership between Apple and Epic alone could reach 20 percent of patients entering a health care system in the U.S. An estimated 10M activity monitor units were sold in 2014 and phones became personal health monitors with the release of Apple’s HealthKit and Google’s Google Fit.
Lastly, the number of large data sets that opened in health care and the tools to analyze them came of age in 2014. For example, the FDA launched openFDA in June 2014, which made it easier to analyze data about adverse events, drug and medical device recalls, prescription and over the counter product labeling, and to access open source code for analyzing this data.
What does this mean for our health? Funding will help drive innovation, and greater connectivity between patients and the people and systems that deliver their care will help drive efficiencies. Both of these will enable developers to more easily amass huge data sets to advance personalized diagnosis and treatment, and support efforts to prevent disease.
Innovation. The last five years have been a “wild west” of digital health startups with greatly varying business rationales and user adoption. We are now beginning to see some sound inventions that make economic sense and will be used by patients, providers, and systems. Activity monitors will go stealth, such as the contact lens being developed by Google and Novartis that detects blood glucose levels. Quantification of conditions will advance so that we have a better understanding of the level and type of disease we are dealing with, such as Oculogica’s brain injury detection system for concussion and other brain afflictions. (Disclosure: The author is a consultant to Oculogica.)
Efficiencies. One of the most needed, but most difficult to realize, implications of health care systems partnering with technology companies, are changes that reduce time and costs for health care systems and patients — from the simple check in at a clinic or hospital, to the number and nature of tests ordered, to smarter follow-up. For example, the first Epic Apple integration at Ochsner Health System in Louisiana estimated a 40 percent decrease in readmissions based on a pilot study with 100 heart failure patients.
Personalization and outcomes. 2014 won’t be the end of guidelines and recommendations based on the general population, but we are at a turning point to eventually achieve ubiquitous genomic assessments of individuals and prediction for optimal treatment. The interim step will be larger data sets — ideally from clinical records and recorded from sensors — which will allow segmentation of patients by age, gender, stage of disease, and other factors. This enables providers to tailor care based on individuals or small segments, rather than large swaths of the population.
Prevention. Prevention is the holy grail in health care with significant impact on health and cost. Programs have been difficult to implement because adoption has been too onerous. Return on investment is difficult to quantify and is often not realized by one hospital or payer. Less obtrusive sensors and more connected systems lower or even remove barriers to adoption. Return on investment will be more quantifiable as individuals, rather than health systems, are followed and quantified.
What do we need in health care? Fewer people who get ill in the first place. When they do, they should receive better care, tailored to who they are and the specifics of their disease, delivered at a lower cost. The challenges notwithstanding, we moved a step closer to this fantastic vision for health care in 2014.