Effect of age-based left-digit bias on stroke diagnosis: Regression discontinuity design

Background: Little is known about how left-digit bias- where humans tend to discretely categorize their decisions based on the left-most digit of the continuous variables-based on patients' age affects the initial diagnosis of stroke patients. The aim of this study is to examine whether there is a discontinuous change in the ordering of imaging tests for stroke at the age threshold of 40 years old, which is indicative of left-digit bias, and whether the effect varies by patient sex. Methods: We conducted a cohort study by regression discontinuity design (RDD). We analyzed the claims database from a nationwide working-age health insurance plan in Japan. Patients who had after-hours hospital visits from January 2014 through December 2019 were included in our analysis. The exposure is patients' age, and the primary outcome was physicians' ordering imaging tests (CT or MRI) to diagnose stroke during the index visit. Results: Of 293,390 total visits, 48,598 visits within data-driven optimal bandwidths of 6.0 years from the cut-off of 40 years were included for the RDD analysis (mean age 40.8 years [standard deviation 3.4], female 50.5%). The baseline probability of receiving imaging tests for stroke diagnosis was 0.9%. Physicians had a higher likelihood of ordering imaging tests when patients' age was above 40 years compared with when patients' age was just below 40 years (adjusted difference, +0.51 percentage points [pp], 95%CI, +0.13 to +1.07 pp; P = 0.01). We found a significant discontinuous change in the ordering of imaging tests for stroke at 40 years for male patients (+0.84 pp, 95%CI, +0.24 to +1.69 pp; P = 0.009) but not for female patients. Conclusions: Physicians have a cognitive bias in estimating stroke risk and, consistent with a left-digit bias, treat male patients aged 40 and just below differently. This pattern was observed only among male patients.