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Six-month mortality risk estimation from electronic medical record

Technology #2019-355

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Categories
Researchers
Gyorgy Simon, PhD
https://healthinformatics.umn.edu/bio/ihi-faculty-staff/gyorgy-simon
Roshan Tourani, PhD
https://healthinformatics.umn.edu/bio/ihi-faculty-staff/roshan-tourani
Nishant Sahni, MD, MS
https://www.mhealth.org/providers/sahninishant-700856649
Managed By
Andrew Morrow
Technology Licensing Officer
Patent Protection

Provisional Patent Application Filed

Applications

  • In-hospital predictive algorithms
  • Electronic health/medical records

Mini Serious Illness Algorithm (minSIA) to predict 6-month mortality risk

Researchers at the University of Minnesota have developed a lightweight algorithm using machine learning for predicting the risk of 6-month mortality at the time of hospital admission. Using just 8 different variables collected during the first 48 hours of hospitalization, this algorithm predicted death within 6-months with an AUC of 0.92. The discriminative ability of this algorithm has been shown to be significantly better than historical estimates of clinician performance. This algorithm can be a critical tool in supporting clinical decision-making at admission and in evaluating suitable options such as transfer to tertiary referral center, serious illness care-conversations in high-risk patients, patient/family counseling, and palliative care utilization.

Phase of Development

TRL: 3-4
Algorithm developed. Currently being validated.

Desired Partnerships

This technology is now available for:

  • License
  • Sponsored research
  • Co-development
Please contact Andrew Morrow to share your business’ needs and learn more.

Publications

  • min-SIA: a Lightweight Algorithm to Predict the Risk of 6-Month Mortality at the Time of Hospital Admission. Journal of general internal medicine (2020): 1-6.