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Scalable treatment algorithm focused on hypertension management for the University of California
Sandeep P Kishore1, Heather E Martin2, Nicki Friedberg3
1Department of Medicine, University of California San Francisco, San Francisco, California, USA sandeep.kishore@ucsf.edu.
Insights
The UC Way Hypertension Medication Algorithm standardized care for over 90,000 patients, improving hypertension control. This evidence-based protocol prioritized affordable, combination therapies, addressing health disparities in underserved populations.
Area of Science:
- Health Services Research
- Clinical Pharmacy
- Cardiology
Background:
- Uncontrolled hypertension significantly contributes to morbidity and mortality, especially in underserved communities.
- Variability in hypertension treatment and associated disparities necessitate standardized care approaches.
Purpose of the Study:
- To describe the development and implementation of the UC Way Hypertension Medication Algorithm.
- To evaluate the algorithm's impact on hypertension control and health equity.
- To share lessons learned for scaling chronic disease management in decentralized health systems.
Main Methods:
- Co-development of an evidence-based protocol by multidisciplinary experts.
- Emphasis on medication affordability and first-line two-drug fixed-dose combinations.
- Implementation through stakeholder engagement, clinician education, and EHR integration.
Main Results:
- The algorithm now guides treatment for over 90,000 hypertension patients.
- Associated with improvements in hypertension control.
- Facilitated standardization and clinician uptake across six academic health centers.
Conclusions:
- The UC Way Hypertension Medication Algorithm offers a scalable model for optimizing chronic disease management.
- Standardized, evidence-based protocols can improve hypertension control and promote health equity.
- Lessons learned are applicable to other decentralized health systems facing similar challenges.
Abstract:
Uncontrolled hypertension remains a leading contributor to morbidity and mortality, particularly among underserved populations. To address care variability and disparities in treatment, the University of California Health system developed and implemented the UC Way Hypertension Medication Algorithm across six academic health centres. This standardised, evidence-based protocol was co-developed by a team of multidisciplinary experts in pharmacy, cardiology, primary care and data science, with an emphasis on medication affordability and the use of two-drug fixed dose combinations as first-line therapy. Implementation strategies included stakeholder engagement, clinician education and integration into electronic health records and routine workflows. The algorithm now informs treatment decisions for over 90000 patients with hypertension and has been associated with improvements in hypertension control. The manuscript focuses on the process of algorithm development, adaptation within a complex multi-payer environment and lessons learned in promoting standardisation, clinician uptake and health equity at scale. This model may inform similar efforts across other decentralised health systems seeking to optimise chronic disease management.
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