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Rationale, design and prerandomization data for a cluster randomized trial to assess the effect of a digitally enabled quality improvement intervention on LDL-C control in established atherosclerotic cardiovascular disease patients: The SAPPHIRE-LDL trial.

作者信息

Machline-Carrion M Julia, Girotto Alysson Nathan, Raupp Priscila, Marton Pereira Pedro, Monfardini Frederico, Santos Raul D, Santo Karla, Ray Kausik, Cannon Christopher P, Berwanger Otávio

机构信息

epHealth UK, Scale Space, Imperial College White City Campus, London, United Kingdom.

epHealth UK, Scale Space, Imperial College White City Campus, London, United Kingdom.

出版信息

Am Heart J. 2025 Jun;284:1-10. doi: 10.1016/j.ahj.2025.01.019. Epub 2025 Feb 3.

DOI:10.1016/j.ahj.2025.01.019
PMID:39909341
Abstract

BACKGROUND

Translating evidence into clinical practice in the management of established atherosclerotic cardiovascular disease patients is challenging. Few quality improvement interventions have successfully improved patient care.

OBJECTIVES

The main objectives are to evaluate the impact of a digitally enabled multifaceted quality improvement (QI) intervention on the control of LDL-cholesterol (LDL-C) in atherosclerotic cardiovascular disease (ASCVD).

DESIGN

We designed a pragmatic 2-arm cluster randomized trial involving 28 clusters (outpatient clinics from public or private hospitals or private practices). Clusters are randomized to receive a digitally enabled multifaceted QI intervention or to routine practice (control). The QI intervention includes reminders, electronic clinical decision support algorithms, audit and feedback reports, and distribution of educational materials to health care providers, as well as electronic educational materials and app-based tools for drug adherence control, lipid profile control, and communication to participants. The primary endpoint is the LDL-C at 06 months after the intervention period. All analyses are performed following the intention-to-treat principle and take the cluster design into consideration by using individual-level regression modeling (generalized estimating equations-GEE).

SUMMARY

If proven effective, this low-cost, digitally enabled multifaceted QI intervention would be highly useful in promoting optimal LDL-C control in ASCVD patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05622929.

摘要

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