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A randomized clinical trial assessing the effect of automated medication-targeted alerts on acute kidney injury outcomes

Author

Listed:
  • F. Perry Wilson

    (Yale School of Medicine)

  • Yu Yamamoto

    (Yale School of Medicine)

  • Melissa Martin

    (Yale School of Medicine)

  • Claudia Coronel-Moreno

    (Yale School of Medicine
    Joint Data Analytics Team. Yale New Haven Health System)

  • Fan Li

    (Yale School of Public Health)

  • Chao Cheng

    (Yale School of Public Health)

  • Abinet Aklilu

    (Yale School of Medicine)

  • Lama Ghazi

    (Yale School of Medicine
    University of Alabama School of Public Health)

  • Jason H. Greenberg

    (Yale School of Medicine)

  • Stephen Latham

    (Yale University)

  • Hannah Melchinger

    (Yale School of Medicine)

  • Sherry G. Mansour

    (Yale School of Medicine)

  • Dennis G. Moledina

    (Yale School of Medicine)

  • Chirag R. Parikh

    (Johns Hopkins School of Medicine)

  • Caitlin Partridge

    (Joint Data Analytics Team. Yale New Haven Health System)

  • Jeffrey M. Testani

    (Yale School of Medicine)

  • Ugochukwu Ugwuowo

    (Yale School of Medicine)

Abstract

Acute kidney injury is common among hospitalized individuals, particularly those exposed to certain medications, and is associated with substantial morbidity and mortality. In a pragmatic, open-label, National Institutes of Health-funded, parallel group randomized controlled trial (clinicaltrials.gov NCT02771977), we investigate whether an automated clinical decision support system affects discontinuation rates of potentially nephrotoxic medications and improves outcomes in patients with AKI. Participants included 5060 hospitalized adults with AKI and an active order for any of three classes of medications of interest: non-steroidal anti-inflammatory drugs, renin-angiotensin-aldosterone system inhibitors, or proton pump inhibitors. Within 24 hours of randomization, a medication of interest was discontinued in 61.1% of the alert group versus 55.9% of the usual care group (relative risk 1.08, 1.04 – 1.14, p = 0.0003). The primary outcome – a composite of progression of acute kidney injury, dialysis, or death within 14 days - occurred in 585 (23.1%) of individuals in the alert group and 639 (25.3%) of patients in the usual care group (RR 0.92, 0.83 – 1.01, p = 0.09). Trial Registration Clinicaltrials.gov NCT02771977.

Suggested Citation

  • F. Perry Wilson & Yu Yamamoto & Melissa Martin & Claudia Coronel-Moreno & Fan Li & Chao Cheng & Abinet Aklilu & Lama Ghazi & Jason H. Greenberg & Stephen Latham & Hannah Melchinger & Sherry G. Mansour, 2023. "A randomized clinical trial assessing the effect of automated medication-targeted alerts on acute kidney injury outcomes," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38532-3
    DOI: 10.1038/s41467-023-38532-3
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