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Trends and Gaps in Digital Precision Hypertension Management: Scoping Review.

Namuun Clifford1, Rachel Tunis2, Adetimilehin Ariyo1

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Digital precision health tools show promise for hypertension (HTN) management, but most studies focus on personalized interventions. Gaps exist in data diversity, reporting, and interdisciplinary collaboration for effective digital health strategies.

Keywords:
algorithmsdigital healthhypertensionmachine learningmobile appsmobile healthpersonalizationphenotypingprecision healthprediction models

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Area of Science:

  • Digital Health
  • Precision Medicine
  • Cardiovascular Disease Research

Background:

  • Hypertension (HTN) is a leading global cause of cardiovascular disease, with many patients lacking blood pressure control despite available treatments.
  • Precision health strategies leveraging digital tools offer potential for enhanced predictive, preventive, and personalized hypertension management.

Purpose of the Study:

  • To conduct a scoping review identifying the current landscape of precision health research using digital tools for adult hypertension management.
  • To address a research gap concerning the application and effectiveness of digital precision health in hypertension care.

Main Methods:

  • Systematic literature search across 5 databases (2013-2023) using a scoping review framework.
  • Thematic analysis of 46 included articles focusing on personalized interventions, prediction models, and phenotyping.
  • Data extraction on study characteristics, digital health technologies, and personalization approaches.

Main Results:

  • Personalized digital interventions dominated (74%), followed by prediction models (17%) and phenotyping (9%).
  • Most studies originated from North America/Europe, with limited diversity in data sources (e.g., social determinants of health, physical environment).
  • Significant gaps were noted in reporting race/ethnicity data (45%) and underutilization of wearable devices.

Conclusions:

  • Personalized digital interventions are prevalent, but definitions of personalization require refinement for better intervention tailoring and health equity.
  • Increased interdisciplinary collaboration and diverse data integration are crucial for advancing digital precision health in hypertension management.
  • Addressing data reporting gaps, particularly for race and ethnicity, is essential for equitable precision health outcomes.