Removing very low-performing therapists: A simulation of performance-based retention in psychotherapy

Therapists can impact the likelihood a given patient will benefit from psychotherapy. However, therapists are rarely held accountable for their patients' outcomes. As a result, low-performing providers likely continue to practice alongside providers with high response rates. In the current study, we conducted a Monte Carlo simulation to illustrate a thought experiment-what happens to patient outcomes if therapists with the worst outcomes were removed from practice? We drew initial samples of 50 therapists from 3 simulated populations of 1,000 therapists with a mean patient response rate of 50% and different effect sizes for therapist variability in outcomes. We simulated 30 patient outcomes for each therapist, with outcome defined as response to treatment versus no response. We removed therapists with response rates in the bottom 5% and replaced them with a random sample of therapists from the population. Over 10 years, the difference in responses between the lowest and highest performing therapists was substantial (between 697 and 997 additional responses to treatment). After repeatedly removing the lowest performing providers 40 times (simulating a 10-year time span), response rates increased substantially. The cumulative number of patient responses (i.e., summing the total number of responses across 10 years) increased by 4,266, 6,404, and 9,307 when therapists accounted for 5%, 10%, or 20% of the patient outcome variance, respectively. These findings indicate that performance-based retention of therapists could improve the quality of psychotherapy in health systems by improving the average response rate and decreasing the probability that a patient will be treated by a therapist who consistently has poor outcomes.