In physician profiling initiatives, risk adjustment is often employed as part of the profiling process. The use of a risk adjuster can adjust for some of the effects of patient characteristics that may vary across providers. Using a risk adjuster can be a helpful advantage when reviewing and presenting data to physicians in a meaningful, credible manner. In most risk adjustment tools, the models offered present two perspectives. There is a concurrent model and a prospective model. Each offer different advantages and their use will vary based on the business question or need to be addressed. This post will look take a brief look at the use of concurrent model results in calculating a provider efficiency score.
The concurrent model describes the health status of a physician’s panel of patients based on the patients’ claim and enrollment experience during an assessment period. The assessment period is often the most recent 12 months. The concurrent model is particularly helpful in provider profiling when evaluating patterns or outcomes of practice.
In the following table, the populations enrolled with three hypothetical physician panels were compared to calculate efficiency scores; this process addresses a common provider concern that “my patients are sicker.” Efficiency scores are typically calculated as a ratio of physicians’ actual allowed claim costs and the expected allowed claim costs based on the concurrent risk scores of the population for which a physician is responsible.
Without risk adjustment, one may draw incorrect conclusions, because the physician practice or panel that appears to have the worst outcomes may simply have the sickest patients. In the example above, while Provider B has the lowest concurrent risk score and lowest actual PMPM cost, their efficiency score is the highest at 1.09 or 9% higher than the average for the total population.
Depending on your decision support tools and risk adjustment tools, risk scores are also available by service breakouts, such as inpatient, outpatient, and pharmacy. In this example, a further drill to the service categories to monitor the distribution of the costs across the service categories would provide additional insight. For example, a comparison of providers’ efficiency in managing inpatient costs by comparing a population’s actual inpatient costs to the costs predicted by the concurrent inpatient risk score.
Stay tuned for upcoming physician profiling blogs.