Given the strain on hospital resources caused by the pandemic, many informaticists have focused on the ability to try and predict patient populations. In January, researchers at the Regenstrief Institute and Indiana University found that machine learning models trained using statewide health information exchange data can actually predict a patient's likelihood of being hospitalized with COVID-19.
Joining Healthcare IT News Senior Editor Kat Jericch to discuss the study's implications are two of its lead authors, Dr. Shaun Grannis and Suranga Kasturi.
Talking points:
More about this episode:
Regenstrief launches initiative to disseminate SDOH data
HIE-trained AI models can forecast individual COVID-19 hospitalization
Data from 175K COVID-19 patients fuels predictive severity model
Predicting COVID-19 hotspots: Kaiser Permanente tool uses EHR data to forecast surges
Even innocuous-seeming data can reproduce bias in AI