Laptop-attached ultrasound units that produce startlingly clear internal images for five dollars in the field. Organs that re-generate inside scaffolds.  Drugs tailored to an individual’s biology. Micro-images of cancerous cells lit up by bio-chemical markers. Decision support tools that scan the physiological values in electronic health records for patterns too complex to be detected by an unaided clinician.

 

The advances available from dramatic improvements in computational capabilities were a recurring theme at the Aspen Health Forum, with experts from each discipline describing where the technology was leading us. I attended two sessions featuring Star Trek clips that predicted realities now within at least theoretical reach. (Prescient and corny, audiences nodded nostalgically.) Sessions on biotechnology, imaging, electronic health records (EHRs) and the hospital of the future highlighted the power that is being leveraged to improve care.

 

The deeper point is that biological mechanisms are built on incredibly complex metabolic webs. The information we depend on has also become overwhelming in scope but fragmented. We’re only now beginning to have the computational power required to model, integrate and manage the many processes contained in each of these arenas. The power we access through digital analytics allows us to extend and broaden our reach.

 

A simple example was the argument, made long ago by David Eddy, a pioneering giant in the application of information technology to care, that the explosion of new knowledge has outrun the capacity of even the best human minds to appreciate and incorporate it. Tens of thousands of new articles are added to the medical literature every month, far more than any professional can evaluate and absorb. But information technology can store all that updated knowledge in formats available at moments of decisions, when we need it most.

 

Dr. Eddy described the promise of cognitive processing, in which software routines would scan and compare dozens or hundreds of physiologic measures within a patient’s health record for patterns a clinician could never identify. A quick analysis might show, for instance, that when 19 of the variables present appear in combination with the values detected, there’s a 62 percent probability of a particular condition. The tool would then describe possible next steps in the care pathway.

 

The horizon is receding across technologies. In a session on the future of diagnostic imaging, GE Healthcare’s Medical Director Robert Honigberg thrilled the audience by showing decade-old and new ultrasound images. He then ticked off ways that, combined with broader advances in information technology, greater macro- and micro-imaging clarity would improve our abilities to effectively address issues: screening for stroke, Alzheimers and cancer; strengthening the power of primary care physicians in rural settings; virtual identification of pathologies; global disease registries; image-guided radiation treatments; and on and on.

 

Finding ways to help patients, clinicians and purchasers leverage the vastness of health information for their own purposes falls into the larger realm of Health 2.0. Still in its formative stages but gathering steam quickly, this sector of health informatics could create the pricing/performance transparencies and decision support that can positively improve clinical quality and finally make health care markets work, lowering cost. But one of Health 2.0’s real appeals is its business model which, as Google has learned, leverages the utility of information to create communities and markets that have commercial value. That, in turn, makes it low cost to the end user, and therefore highly accessible.

 

Some developments offer more accessible (i.e., lower cost) value propositions than others. In an everyday context, those, like Health 2.0, that depend almost strictly on data analysis and reformulation into decision-support will likely be far less costly, with far greater potential for population-level impact than, say, those that involve biologics. That relationship might be reversed, though, in situations like pandemics, when the biologics are the only recourse for populations. How does one work through these dilemmas?

 

It is difficult to not be dazzled by these possibilities. Who wouldn’t long for progress that can replace a child’s defective heart or kidney or eye, and make a compromised life whole again? But as with virtually all progress, developments raise profound conflicts between what we want and what we can afford. In a system being crushed by cost – while the average American family’s health care costs $14,500 in 2007, one third of households make less than $35,000 – where do we invest and how should investors be rewarded? Is there a reasonable limit to the price of even great progress?

 

One thing was clear. The advances that have made these miracles possible will continue to accelerate and become less expensive, making the technologies that are now available but out of reach accessible as well.

 

So the promise is breathtaking. Only our resources, our imaginations and our judgment will limit us.