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Kidney Week

Abstract: PO0187

Artificial Intelligence in AKI: Goals of an AKI!Now Workgroup

Session Information

Category: Acute Kidney Injury

  • 101 AKI: Epidemiology, Risk Factors, and Prevention

Authors

  • Neyra, Javier A., University of Kentucky Medical Center, Lexington, Kentucky, United States
  • Koyner, Jay L., University of Chicago Pritzker School of Medicine, Chicago, Illinois, United States
  • Goldstein, Stuart, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States
  • Pannu, Neesh I., University of Alberta, Edmonton, Alberta, Canada
  • Kashani, Kianoush, Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Singh, Karandeep, University of Michigan, Ann Arbor, Michigan, United States
  • Menon, Shina, Seattle Children's Hospital, Seattle, Washington, United States
  • Soranno, Danielle, Children's Hospital Colorado, Aurora, Colorado, United States
  • Nadkarni, Girish N., Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Bihorac, Azra, University of Florida, University of Florida, Gainesville, FL, US, academic, Gainesville, Florida, United States
Background

In 2019, the American Society of Nephrology established AKI!Now, a collaborative initiative to promote excellence in the prevention, diagnosis, and treatment of Acute Kidney Injury (AKI). Here, we describe the ongoing efforts of the AKI!Now workgroup focused on Artificial Intelligence (AI) to improve the quality, accessibility, affordability, and equity of AKI care.

Methods

The workgroup has outlined objectives in 3 key domains:
1. Patients. Input in designing and implementing fair and equitable AI tools and identifying clinical scenarios based on personal and caregiver experience that could be improved with AI
2. Clinicians. Input in the design, value, and implementation of fair and equitable AI tools and identifying clinical uncertainties that may benefit from new AI tools
3. Researchers. Evaluation of current AI tools, with a focus on removing implicit bias; development of novel, feasible, and effective AI tools to address gaps identified by patients and clinicians; and development and implementation of AI methods along with novel sensors for more sensitive assessment of kidney function and injury to advance the science of AKI

Results

This project, with involvement from a multi-disciplinary group of stakeholders, will yield efficient and effective use of AI for quality improvement in AKI care. Specific deliverables include 1) Risk-stratification and prediction tools; 2) Intelligent alert tools; 3) Decision support for bundled care compliance; 4) Decision support for implementing pragmatic clinical trials, among others. Importantly, this work will fill gaps in validating available AI tools and develop many desired AI tools that do not exist. These coordinated efforts are expected to deliver highly useful AI tools that could improve AKI care, research and reduce associated costs.

Conclusion

The AKI!Now workgroup on AI is committed to improving value care in AKI and encourages engagement and collaboration with patient, provider, researcher, and industry stakeholders. We seek to improve the care provided to the growing and susceptible AKI population, along the entire lifespan.