June 25, 2018 – Delivery of healthcare, by definition, is a continuum that leverages the leading technologies available at that point in time. As new technologies evolve, as lifestyles change, as population ebbs and flows, migrations happen, and healthcare infrastructure morphs – health and healthcare are impacted. Historically, healthcare delivery has been a very reactive, symptom-driven process. The advent of technology, however, has ushered in an era of consumerization, and a data-driven, quantified-self approach to personal health. With increasing healthcare costs, owning and pro-actively managing one’s health will not only be a “nice to have”, it will be a “must have”, an imperative that will be implemented through a series of carrots and sticks by employers, insurers and providers. Let’s walk through the various waves or phases of modern healthcare deliver – past, present and future.
The traditional/historical healthcare delivery model was relatively straight forward, made up of regular check-ups and incident based care, as and when symptoms surfaced. We call it the Reactive Healthcare phase. At that time, the intervention ranged from “take two of these and call me in the morning” to “triage” depending on the severity of the condition. The old model did not necessarily rely on a lot of real-time data that could help predict or detect the onset of a particular condition. The norm was a standard set of physiological tests to understand the underlying condition with the notion of usually prescribing more of a “one size fits all” approach to treatment. The idea of personalized or predictive medicine was pure fantasy, and not something that was in the normal medical repertoire. Having said that, the concept of a family doctor was fairly common (with doctors making house calls, albeit without a mobile app). The physician did rely on the analog patient/family history for curated treatment.
Next, the internet, and especially the mobile internet revolution drove the Pre-emptive Healthcare phase. Consumers started taking control of their own health through real time monitoring of vitals, physical activity and nutrition, using connected devices and mobile applications (collectively referred to as the “quantified self” movement). That, along with access to online research, enabled consumers/patients to get ahead of an impending medical condition. Patients were now armed with both data and information when approaching medical professionals, asking in-depth questions, seeking second opinions online and having a better understanding of diagnoses, remedies and risks associated with various treatment options. Sites like WebMD and Health Tap exemplify that wave. Additionally, community sites like Café Mom and Patients Like Me are forums not only for information and support, but for consumers and patients to seek customized crowdsourced advice around medical conditions, health, wellness and overall lifestyle modifications. Doctors on Demand and apps like Heal, Careplus help consumers take the next step of remote real time access to specialists.
The advent of affordable genomic testing and artificial intelligence can now lead to assessment of pre-dispositions to certain conditions and consequent curated therapies based on one’s genomic make-up. Physicians and patients can now predict the onset of physiological symptoms, and intervene, in many cases, well before the underlying conditions become chronic, irreversible or catastrophic. Data being generated across clinical, genomic, physical and physiological domains of one’s life is the “what”. Analytics, leveraging the powerful combination of AI, Machine Learning and Deep Learning is leading to the “so what” – actionable insights and analytics. We are at the cusp of the Predictive Healthcare phase. There is considerable work being done in this arena using the combination of structured and unstructured data to provide more accurate diagnoses and treatments with optimal outcomes, minimized side effects and hospital readmissions. There is a broader mandate towards outcome based reimbursement by insurers/payers and value based care. Proliferation of self-insured employers is creating additional forcing function driven by economics, to get ahead of chronic, expensive medical conditions, rather than waiting for those conditions to proliferate. As a result, understanding the likelihood of the onset of a particular condition, especially chronic condition, is crucial not only for improving an individual’s quality of life, but also bringing the out-of-control healthcare costs somewhat under control. Companies like Collective Health, Limeade, and Grand Rounds are leading the charge in terms of leveraging customer data across the various silos and engaging members and employees to deliver lasting outcomes. Only with this data-led unified view can one layer analytics that combine the historical with the current data sets to continuously glean actionable insights.
The holy grail of Personalized Medicine which, until recently, was only a dream, is showing signs of becoming reality. The combination of genomic and phenotypical data, together with other data sources mentioned earlier are leading to truly personalized therapies. One of the most significant advances being made is in the area of Immuno-therapy, essentially getting an individuals’ own body to attack the disease or intrusive agent from within. The first immuno-therapy drug was approved by the FDA last year, marking a significant milestone for personalized health science. The pipeline of such therapies that leverage an individual’s own DNA is extremely encouraging for conditions previously considered irreversible and terminal. The reduction in cost for an entire genomic analysis has dropped by several orders of magnitude. Significant acquisitions in the space such as Flatiron (a data driven immuno oncology platform) by Roche is validation of not only the importance of this trend, but the potential business impact on the incumbents – who will either embrace this disruption or be obsolesced by it.
But, there is a long way to go still. Here is a strange fact – Only 2 percent of cancer studies and less than 5 percent of pulmonary studies have included enough minorities to provide useful information, according to a study conducted by UCSF (minorities make up 40% of the US population). In the US, minorities account for less than 10% of all clinical trials. As a result, molecules that are approved based on clinical trials of particular demographic cohort often are ineffective or less effective on a different segment of the population. This anomaly is causing some to do a mindset shift when it comes to the entire drug development process, and a framework that pro-actively recruits from diverse population sets for clinical trials.
Bottom line: Consumerization of healthcare, along with significant advances in machine learning, AI and genomics are ushering in a new era of innovation in personalized medicine. And much of that information will literally be in the palm of our hands (or on our wrist, body, clothing or other form factors of the future). Medicine is putting the consumer at the center of healthcare with personal data driven inputs leading to bespoke outputs. Overall healthcare continues the journey from the legacy of reactive medicine to the brink of truly personalized medicine. Devices and data are becoming ubiquitious and truly personal, driven in part by the reduction in cost of generating and capturing the data. Analytics, driven by the new wave of machine and deep learning are providing near real time actionable insights. Layering on top, the proliferation of genomics (again driven by cost reduction in DNA analysis and genome-editing technologies like CRISPR), is resulting in increasingly targeted therapies. This wave of mobile devices, applications and big data analytics is juxtaposing technology giants next to traditional pharmaceutical companies. Roche’s acquisition of Flatiron mentioned earlier, and companies like Google, Apple and Amazon getting into the healthcare game, will lead to significant consolidation in the industry with a combination of sizable companies merging to fend off the new technology-led threat, but also to vertically integrate and bring data input and analytics capabilities in-house. The biggest challenge, perhaps, for the medical and entrepreneurial community is not only to continue the journey towards predictive, personalized treatment, but to make it ubiquitous and affordable. In this journey, the consumer will also have to take ownership and responsibility of their own health and wellbeing. The tools are only portion of the equation – education and mindset shift on the part of the consumer are the other.