Aspiring healthcare entrepreneurs could be forgiven for assuming our most significant challenge is the need to reduce the cost of care. Investors and policy wonks alike seem to agree on the overriding need to focus on innovations that will improve efficiency and take costs out of the system.
The appeal of this approach is easy to understand: rising healthcare costs are a real problem, and business process improvement feels like something we already know how to do. Large companies like GE and Oracle are thrilled by the opportunity to apply their process methodologies to healthcare. Management journals love the idea of improving healthcare through operational excellence. An increasing number of foundations have also joined the fray, focused explicitly on supporting innovations that reduce the cost of care.
Yet, as much as operational improvements are urgently needed, they should not represent the primary goal of healthcare innovation.
If we’re truly interested in high value healthcare, we’d do well to keep in mind that for many, if not most serious or chronic diseases, at least in the absolute sense, high value care simply isn’t an option. We have embarrassingly few therapeutic approaches that can really do much to restore the lives of these patients. Sufferers afflicted with Alzheimers Disease, pancreatic cancer, brain tumors, and so many other conditions desperately require transformative breakthroughs, not the mucking around the edges that passes for treatment today.
Make no mistake: it’s critical we do the very best we can to providecompassionate, evidence-driven care for patients who are sick right now, and innovations that contribute to the identification and humanistic delivery of the best available care are vitally important.
But we must also acknowledge that for many conditions, even the very best options are often tragically limited. We shouldn’t become so obsessed with optimizing these relatively poor choices that we lose sight of the urgent need and opportunity to think about how emerging technologies can be brought to bear to yield truly transformative change, the sort of advances we’ve witnessed in the treatment of diseases like polio and diptheria, hepatitis C and testicular cancer.
While healthcare stakeholders universally profess an interest in improving the quality of care, this ambition seems almost universally understood as an effort to reduce bad and ineffective care, rather than improve upon our potential to do good. It’s as if we’ve focused so much on improving the average health of populations we’ve lost sight of the need to improve upon the very best care we can offer to each individual.
Quality improvement shouldn’t only consist of removing the negative, and eliminating what clearly doesn’t work in healthcare; excellence in quality should also require us to continuously ask how we can use emerging technologies to advance the frontiers of knowledge, especially in areas where the very best evidence based-care is clearly not good enough.
There is a silver lining here: even if the initial applications of new healthcare technology seem rather limited, they may yet provide the foundation for more substantive future advances.
Consider, for instance, the proliferation of mobile technologies. While activity trackers, for example, are essentially an entertaining consumer product today, mobile technologies and sophisticated sensors also provide the means toexpand our conceptualization of medicine in time and space, and move care beyond the four walls of a hospital and yearly physician visits. Health is continuous and everywhere, and new technologies provide the opportunity for researchers, working in partnership with patients, to develop more nuanced understanding of patients’ longitudinal, real-world experiences and needs.
Ensuring the data from mobile devices actually contribute to our personal medical records is a second challenge. The health information ecosystem is absurdly fragmented; record systems struggle not only with remote data, but also with data from core hospital devices like infusion pumps and ventilators. As Johns Hopkins quality expert Peter Pronovost, recently wrote in JAMA, “None of these technologies communicate and share data.”
This is starting to change, however, amidst the recognition that improved interoperability could save lives. The hope is that efforts to enhance data integration will not only reduce medical mistakes, but will also generatedense, comprehensive databases that will enable researchers to extract novel insights about the causes of disease, and glean empirical clues into potential therapeutic strategies.
A third opportunity lies in the area of sophisticated analytics — computer programs that search healthcare data for meaning. Much of the initial effort here has focused on “descriptive” analytics – algorithms that review datasets to figure out who’s not following established protocols: Has every patient evaluated for a suspected heart attack received an aspirin? Has each diabetic patient been sent for an eye test?
As useful as these approaches are for enhancing patient care and improving clinical decision-making, the real excitement will be the use of sophisticated analytics to yield fundamental disease insights, and ultimately, we hope, point the way to radically new treatments.
Medical scientists have been chastened by our disappointing experience with human genomics. Curing disease is a lot harder than it looks. Yet unless we keep this worthy aspiration in sight, we risk settling for low value medicine — served with marvelous efficiency.