AI Article Synopsis

  • Excessive fluctuations in blood pressure are linked to higher risks of serious health issues like cardiovascular mortality and stroke, possibly due to patients not consistently following medical advice.
  • A new trial uses an algorithm to track blood pressure variability in patients' electronic health records (EHR) and offers remote interventions to improve adherence to treatment.
  • The study aims to identify patients with high variability and evaluate the impact of the intervention on their blood pressure, while also ensuring a fair allocation of healthcare resources.

Article Abstract

It has recently been shown that excessive fluctuation in blood pressure readings for an individual over time is closely associated with poor outcomes, including increased risk of cardiovascular mortality, coronary heart disease and stroke. Fluctuations may be associated with inconsistent adherence to medical recommendations. This new marker of risk has not yet been incorporated into a monitoring and intervention strategy that seeks to reduce cardiovascular risk by identifying patients through an algorithm tied to their electronic health record (EHR). We describe the methods used in an innovative "proof of concept" trial using CP&R (Cardiovascular Precision Medicine and Remote Intervention). A blood pressure variability index is calculated for clinic patients via an EHR review. Consenting patients with excessive variability are offered a remote intervention aimed at improving adherence to medical recommendations. The outcomes include the ability to identify and engage the identified patients and the effects of the intervention on blood pressure variability using a pre-post comparison design without parallel controls. Our innovative approach uses a recently identified marker based on reviewing and manipulating EHR data tied to a remote intervention. This design reduces patient burden and supports equitable and targeted resource allocation, utilizing an objective criterion for behavioral risk. This study is registered under ClinicalTrials.gov Identifier: NCT05814562.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11509108PMC
http://dx.doi.org/10.3390/jcm13206274DOI Listing

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