Because episodes have, by definition, a finite duration, it is now relatively easy to mine data sets to identify which providers can solve specific medical problems more effectively and at a lower cost than other providers. Whether the category being considered is surgeons who perform hip replacements, oncologists who treat prostate cancer, or hospitals that take care of stroke patients, the goal of this approach is to reward providers for delivering a patient’s desired outcome (say, walking, remission, or hospital discharge without readmission) with as few complications as possible and for providing the best experience at the lowest possible cost. Focusing on episodes of care makes it easier to compare performance across providers and encourages productive competition among them. We believe that more than $2 trillion of US annual spending on health care, which currently totals about $2.7 trillion, could be paid through an episode-focused approach.
McKinsey folks think very highly of themselves. I have always resented that.
In this case, Latkovic appears to be comparing the existing compensation system with a system that would not be gamed. That is unrealistic. Instead, ask yourself how doctors would game an outcomes-based compensation system.
1. Over-diagnose. That is, report that the patient has a condition that is worse than it is.
2. Under-treat. Suppose that 10 percent of the variation in outcomes is due to doctor actions, and 90 percent is due to other random variables. Then the profit-maximizing strategy is to pocket the payment for the “episode,” do nothing, and hope for the best. In fact, you should avoid patients where the routine action produces cure with certainty, because the profit margin is likely to be low.
3. Select only patients with high conscientiousness, because they will have much better outcomes than patients with similar ailments and low conscientiousness.
etc.