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Background <p>Hypertension is a leading cause of morbidity and mortality, affecting 48% of US adults, with nearly three quarters of them remaining uncontrolled. Despite evidence-based guidelines for the management of hypertension, gaps persist in their clinical application. The aim of this study was to improve blood pressure control rates among nonpregnant adult patients in primary care.</p> Methods <p>We applied the Agile Implementation process to address barriers to guideline implementation. Using an iterative quality improvement approach, we implemented the AI process in a clinic serving minority and underserved populations from January 2023 to December 2023.</p> Results <p>The AI process increased hypertension control rates from 43 to 58%, using a target blood pressure below 140/90 mmHg.</p> Conclusions <p>The AI process effectively improved hypertension control rates in an underserved primary care setting, offering a scalable approach for enhancing outcomes in similar populations.</p>

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Agile implementation for hypertension control in primary care

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

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  • Diana Summanwar,
  • Paul T. Mingo,
  • Tanya K. D. Wilson,
  • Celia Menke,
  • Andrew Van Velsor,
  • Malaz Boustani

摘要

Background

Hypertension is a leading cause of morbidity and mortality, affecting 48% of US adults, with nearly three quarters of them remaining uncontrolled. Despite evidence-based guidelines for the management of hypertension, gaps persist in their clinical application. The aim of this study was to improve blood pressure control rates among nonpregnant adult patients in primary care.

Methods

We applied the Agile Implementation process to address barriers to guideline implementation. Using an iterative quality improvement approach, we implemented the AI process in a clinic serving minority and underserved populations from January 2023 to December 2023.

Results

The AI process increased hypertension control rates from 43 to 58%, using a target blood pressure below 140/90 mmHg.

Conclusions

The AI process effectively improved hypertension control rates in an underserved primary care setting, offering a scalable approach for enhancing outcomes in similar populations.