Big Data and the art of medicine


Life is short, and the Art long to learn.


If you are anything like us, you still hold firmly to the notion that medicine, at its core, is an art. Sure, medicine is informed by cutting-edge sciences, such as biochemistry and molecular biology. But one can’t capture the nuances of the patient interaction by studying the Krebs cycle, nor define the motivating forces driving physicians by looking through a microscope. On the contrary, physicians are artists, much like musicians, sculptors, or dancers. And, like any of these artists, it would seem that a physician’s craft should improve through "practice," not by studying data or using a computer. So how do we reconcile this in the era of "Big Data"? How can the "ones and zeros" living deep in the "guts" of our electronic health records (EHRs) promise to revolutionize an art that has relied solely on the judgment – or gut sense – of physicians for centuries? Here we will attempt to answer these questions and ponder whether or not we really can improve the art of medicine with the help of data.

It’s more than the ‘ones and zeros’

With the right information and the proper tools to analyze it, it is possible to conceive of an improvement in our ability to care for patients. Take, for example, the prevention of malignancies. Currently, early detection of cancer relies heavily on a physician’s knowledge of – and compliance with – current cancer screening guidelines. Success also depends on a patient’s willingness to come in for annual visits to receive the instruction. If the patient doesn’t show up for a physical, or if the provider neglects to mention the need for a colonoscopy when the patient does appear, the test may go unordered (much to the patient’s relief, perhaps!). But the right tools and analytics won’t let that happen. Instead, the technology will identify the highest-risk populations with ever-improving accuracy and notify both physician and patient of the need for action. With enough data, we may even be able to make observations in trends of cancer inheritance never before possible and predict cancer long before it might be detected by conventional screening protocols.

It pays to care about the data

Physicians may not realize it, but data can have a significant financial advantage, by improving reimbursement and decreasing the overall cost of care. This can be achieved in two ways. The first way is by using the data to paint a more accurate picture of patient complexity. Medicare assigns a risk-adjusted score to patient cohorts based on the severity of their diagnoses and reimburses Medicare Advantage plans based on that score: the higher the score, the better the reimbursement. Occasionally, those additional dollars are passed along to the treating physicians. But all too often physicians do not use ICD-9 codes properly on their claims, making their patients appear less complicated and thereby receiving lower reimbursement. Through emerging data collection tools, improper coding can be identified and corrected, and missed opportunities can be discovered early enough to capture additional funds.

The second way these tools can be used leads to direct benefit to the health care system in general, through improved medical cost management. By interfacing with insurers and analyzing claims, the software can identify patients who are high utilizers and can show trends in medical costs across a community or health system. This allows providers to target certain patients or disease states around which to build cost-containment strategies and create win-win scenarios that decrease hospital readmissions, limit cost, and improve patient quality of life.

We recently learned of a great example of this. Using a population management data tool, a community health system was able to identify a geographic area in their region with a large uninsured population. This group had a disproportionately high utilization of emergency medical services and very low care quality markers (such as diabetes control, vaccination rates, etc.). Through targeted outreach based on these data, the system was able to direct individuals into low-cost, high-quality primary care sites and reduce emergency service utilization to levels below the surrounding neighborhoods. Simultaneously, the health of the community improved through better disease management and care coordination. Finally, data analytics tools uncovered additional opportunities for savings by identifying expensive brand-name drug prescriptions that could be replaced with generic drug alternatives.

A reluctant revolution

As we have lamented on previous occasions, the adoption of health care information technology is often driven by artificial external forces, such as stimulus programs or regulatory requirements. The government has routinely used incentive payments and reimbursement adjustments in order to spur widespread acceptance of EHRs. Most infamously, the Meaningful Use Regulations program has become the poster child for government involvement in direct patient care. Through the use of annual payments over a 5-year period (combined with the threat of penalties for lack of compliance), Meaningful Use has almost single-handedly enabled the Big Data revolution in health care by requiring physicians to purchase electronic health records systems and use them for population management. While seemingly a good thing, most physicians would hardly regard these systems as "meaningful." In fact, many question if there is any value in having an electronic record at all.


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