Considering your own medical data, try answering a few questions:
- What was your blood pressure this morning?
- Which hospital in your area has a) the lowest cost for emergency visits, b) the best safety record, c) the highest rating for customer service, d) the most experience in cancer, heart disease, etc.?
- Are you genetically at risk for breast or testicular cancer?
- How many calories have you burned in the last week?
Within the next several years, answers to those types of questions will be easily available. New streams of information, from personal genomes to exercise gadgets, like the Fitbit, will be creating vast new pools of data, both for personal information and research. Eventually, tracking information on our own bodies and the health care choices we face will be as intuitive as clicking through the stocks in our 401k.
But data in health care means a lot more than answers to simple questions. Data will change our understanding of health. Instead of a handful of test results and a smattering of annual measurements in a folder, health data will increasingly be something that we generate passively, day by day, almost the way we produce CO2 or garbage. This data will flow, creating patterns and, if we choose, triggering alerts. The bigger change, however, is much of the data will be generated, shared, and consumed outside of the medical establishment. It will be ours. We will use it to manage our own lives, and we will choose doctors and other professionals to guide us in this endeavor.
It’s easy to get distracted by visions of data in health care and to ignore its first big job, which is to run a business efficiently. It involves scheduling customers, getting them the treatment they need, and getting reimbursed. This is primordial. If an enterprise can quickly find the right information for each encounter, it can optimize resources, run more efficiently and get paid. This much has been true since Babylonian accountants scratched out their records on clay tablets. What’s different now is that once a business is up and running with modern digital data, those trickles of data turn into torrents. Then all kinds of exciting possibilities emerge along with, yes, serious questions about privacy.
The way I see it, we can expect three data revolutions in health care. The first wave helps medical practices and hospitals run their businesses efficiently. The data lets them see (often for the first time) what they’re doing. It spotlights where they’re wasting time, energy and money. This process alone, while it sounds simple, promises to bring astounding efficiency gains to health care. The second stage uses data to help with diagnoses and treatment, and to manage the health of a population. It backs up the doctor’s informed gut intuition, which is still valuable, with science. This should result in immense qualitative gains.
In the third stage, we move from Big Dumb Medicine to Small Smart Medicine. For this, we look at all of society as a vast laboratory. What are people doing? How are they eating and exercising? For the first time, we have the wherewithal to carry out research on how people live in the real world. How are the different medicines working? Maybe one medication works far better in hot climates, or for non-smokers, or only for heavy drinkers. While historically we have approved only the medicines and therapies that are safe and work for all of us, as if we were farm animals, we now have a chance to figure out the right medicines, diet, and therapy for each individual. The opportunities are near limitless.
The impact of these three revolutions on health care will be enormous, so big in fact that it’s ridiculous for government officials and corporate accountants to be drawing up projections of health care spending in 2025 or 2030. These inevitably feature terrifying graphs showing the expanding health industry consuming our entire economy. Such scary predictions are akin to using revenue numbers from the Yellow Pages in 1998 to predict the future of commercial search—this at a time when Google was already on the rise.
If you think about it, doctors, in one way or another, have always been in the data business. They’ve long kept records on height and weight, illnesses and medicines prescribed. Further, a big part of a doctor’s job is to pick up data the old-fashioned way—to see, touch, smell, hear and talk—and then to incorporate these learnings with formal knowledge. Even today, when a family doctor sticks in a tongue depressor and gazes down a person’s gullet, he or she is gathering visual data, and matching it to images of strep throat and tonsillitis archived in memory. When it comes to analyzing the diverse signals coming from a patient, there is still no computer or data analysis that can match a human mind endowed with the knowledge and experience of a doctor.
Yet even the best doctors could use some help from data. The prime encounter can and should still feature the doctor meeting with the patient the old-fashioned way, using all of those human attributes that machines cannot match. But the doctor, at the same time, can benefit from the knowledge gathered by thousands of other doctors facing similar cases. That comes from digital data. And in the best of cases, that wealth of knowledge will be distilled into a few simple and incisive pointers and questions.
It is true that disaster awaits us if we resist all change and turn our backs on the three data revolutions. But we cannot afford to, and we won’t. The only question in my mind is how many delays and how much pain we’ll endure, and how many trillions of dollars we’ll waste, before we let innovation flower in this field. Sooner or later, health care will be a changed industry with utterly different dynamics and pricing, and it will revolve around data.