Precision Nudging for Hypertension Management: Observational Study
Data-driven Personalization for Inclusive Outreach and Equitable Outcomes in a Digital Health Intervention for Hypertension Management: A Prospective Observational Study
Lirio
12,000 participants
May 1, 2024
OBSERVATIONAL
Conditions
Summary
The purpose of the proposed observational study is to explore the relations between data-driven personalization and equitable health outcomes in a digital health intervention (DHI) for hypertension management. In the current intervention, behavioral reinforcement learning is applied to personalize intervention content to maximize the behavioral outcomes of three target behaviors critical for effective hypertension management: clinical encounters, medication adherence, and self-monitoring of blood pressure (SMBP).
Eligibility
Inclusion Criteria3
- Patient of Cone Health.
- Hypertension condition considered "uncontrolled" (signaled by an eligibility indicator).
- Most recent blood pressure reading is at or higher than 160/90 (lowered to 140/90 in April 2025 in accordance with approved protocol)
Exclusion Criteria4
- Non-English speaking.
- Globally unsubscribed.
- Locally unsubscribed.
- Deceased.
Interventions
The hypertension digital health intervention under study combines behavioral science theory with a type of machine learning called reinforcement learning to enable precision nudging: the selection, assembly, and delivery of behavioral science-based messages created to address barriers to, and promote, management of hypertension. The behavioral design process used for the hypertension DHI intentionally includes research on traditionally underserved populations, such as racial and ethnic minorities and people with lower incomes or educational attainment. By including the right ingredients to meet a diverse set of needs and by effectively personalizing the content each individual sees based on their own reactions, the intervention aims to improve health equity by matching each individual to the right behavioral approach.
Locations(1)
View Full Details on ClinicalTrials.gov
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NCT06354192