Discharge recommendation based on a novel technique of homeostatic analysis

J Am Med Inform Assoc. 2017 Jan;24(1):24-29. doi: 10.1093/jamia/ocw014. Epub 2016 Mar 28.


Objective: We propose a computational framework for integrating diverse patient measurements into an aggregate health score and applying it to patient stability prediction.

Materials and methods: We mapped retrospective patient data from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II clinical database into a discrete multidimensional space, which was searched for measurement combinations and trends relevant to patient outcomes of interest. Patient trajectories through this space were then used to make outcome predictions. As a case study, we built AutoTriage, a patient stability prediction tool to be used for discharge recommendation.

Results: AutoTriage correctly identified 3 times as many stabilizing patients as existing tools and achieved an accuracy of 92.9% (95% CI: 91.6-93.9%), while maintaining 94.5% specificity. Analysis of AutoTriage parameters revealed that interdependencies between risk factors comprised the majority of each patient stability score.

Discussion: AutoTriage demonstrated an improvement in the sensitivity of existing stability prediction tools, while considering patient safety upon discharge. The relative contributions of risk factors indicated that time-series trends and measurement interdependencies are most important to stability prediction.

Conclusion: Our results motivate the application of multidimensional analysis to other clinical problems and highlight the importance of risk factor trends and interdependencies in outcome prediction.

Keywords: clinical decision support systems; computer-assisted diagnosis; length of stay; medical informatics; patient discharge.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Datasets as Topic
  • Decision Making, Computer-Assisted*
  • Decision Support Systems, Clinical
  • Humans
  • Intensive Care Units
  • Length of Stay
  • Patient Discharge*
  • Prognosis
  • ROC Curve
  • Retrospective Studies
  • Risk Assessment / methods
  • Risk Factors
  • Triage / methods