P068 IDENTIFYING THRESHOLD BIAS IN RECORDED BLOOD PRESSURE

Background and Objective: Even when blood pressure (BP) is measured accurately, BP may be misrecorded. “Threshold bias” occurs when BP measurements are intentionally or unintentionally recorded at values just below BP control goals and may occur due to incentives to improve BP control or to avoid medication titration. Our objectives were to 1) examine the potential for threshold bias in datasets with and without a BP control goal from two countries and 2) propose a method for detecting threshold bias. Methods: We examined the distribution of recorded BP measurements among individuals taking antihypertensive medication in clinical practice or trials with a BP goal <140/90 mmHg and population-based surveillance studies without a BP goal from Bangladesh and the US. Then, we explored whether surveillance data could be used as a reference to evaluate the likelihood of threshold bias in clinical data. We calculated the ratio of BP measurements recorded 10 mmHg below versus above thresholds of interest (i.e., the “threshold ratio,” or number of systolic BP [SBP] measurements 130-139 mmHg over 140-149 mmHg) and used bootstrapping to determine the probability of observing ratios that may indicate threshold bias. We compared the “threshold ratio” from clinical data to the probabilities determined from surveillance data. Results: Visually, we observed a cluster of measurements below SBP 140 mmHg in the clinical but not the surveillance datasets from Bangladesh and the US (Figure). Based on 10,000 random draws of 100 observations in the Bangladesh surveillance dataset, the probability of observing a “threshold ratio” of 3.56 in the clinical dataset was <2%, indicating a high probability of threshold bias. Using the same procedure in the US surveillance dataset, the probability of observing a “threshold ratio” of 2.26 in the clinical dataset was <10%, indicating potential concern. Conclusions: Threshold bias may be an underrecognized but common problem in clinical settings with a BP goal. Our proposed approach to detecting threshold bias should be tested in other settings.