Trade-offs Between Accuracy and Health Outcomes in Algorithms for Home Blood Pressure Monitoring Devices

Abstract

Objectives Home blood pressure monitoring (HBPM) is crucial for managing hypertension, but there is a potential trade-off between measurement accuracy and health/economic outcomes due to asymmetric costs associated with misclassifying an individual as having hypertension or not. We assessed whether adjustments to device readings that increased overall accuracy produced net health and economic benefits. Methods We analyzed data from N  =  89 Alaska Native individuals who used 2 HBPM devices and a standard aneroid sphygmomanometer. We modeled changes in expected costs associated with individuals being misclassified as hypertensive or not under 3 different models of adjusting HBPM device readings. Results The gains in accuracy produced by adjusting HBPM readings decreased the overall rate of hypertension misclassification but increased the rate of false-negative readings. Adjusting readings led to a net increase in expected health and economic costs. Discussion Ignoring asymmetric costs of misclassification can escalate overall costs and worsen uncontrolled hypertension. Home blood pressure monitoring algorithms must be cautiously designed, considering both false negatives and positives. Greater transparency in HBPM algorithms is needed for effective coordination among manufacturers, clinicians, and patients.