From disease management to wellness
A range of technologies are needed to move us down the path to lifelong wellness. Ongoing efforts to understand the human genome will be further enhanced by combining genetic data with a range of other data types:
- Traditional clinical laboratory results
- So-called “multi-omics” analyses that quantify collections of biological molecules
- Real-time data generated by wearables and mobile technologies
- Behavioral data gleaned from social media sites and advocacy organizations
Accelerating this shift to precision health are a range of enabling tools that include third-party clouds for data sharing and artificial intelligence. Software can now be used to identify patterns in extremely large data sets, revealing potential links between specific genes or proteins and disease more rapidly than human counterparts could find them.
The ability to shrink, and sync, sensors and electronics is also important. Embedding technology into consumers’ lives in such a fundamental way should reduce the wearable-tech fatigue that can limit lasting behavior change.
The ‘P-medicine’ mindset
The pivot from disease management to precision health intersects with another larger trend redefining health care: P-medicine, care that is personalized, precise, preventative, predictive, pharmaco-therapeutic and participatory.
At its heart, P-medicine represents a new mindset that emphasizes prevention and greater collaboration between physicians, consumers and other stakeholders in pre-empting and solving health challenges.
By capturing biological, clinical and behavioral outputs, this new approach could refine how providers educate individuals about both disease risk and illness so that behavioral prompts are delivered to the right patient, at the right time, to achieve maximal health.
Shifting business models
As our understanding of the drivers of age-related diseases grows, the demarcation between disease management and disease prevention will blur, leading to earlier disease interception. This means broadening the definition of disease to include susceptibility based on the relationship between biological markers and the development of full-blown symptoms. Driven by new technologies, this shift to prediction and pre-emption will necessitate changes in health care delivery and biopharma business models.
Currently, when attention is given to prevention, it is largely ad hoc and episodic. In a consumer-empowered future, providers will personalize care, moving away from reliance on population-based metrics to individualized risk assessments. In the near term, the greatest opportunity is the development of simple concierge services that either coordinate care or support wellness by integrating insights from big data with high-touch behavioral tools.