Job Shiach

Graduate Trainee, University of California, San Diego

1 active project

MED264_AKI_Readmission_Group

We'd like to study what features (including social determinants of health) contribute to readmission in patients with acute kidney injury (AKI). Understanding these features is important since the ability to proactively identify readmission risk could lead to improved consultation &…

Scientific Questions Being Studied

We'd like to study what features (including social determinants of health) contribute to readmission in patients with acute kidney injury (AKI). Understanding these features is important since the ability to proactively identify readmission risk could lead to improved consultation & follow-up for high-risk patients.

Project Purpose(s)

  • Disease Focused Research (Acute Kidney Injury)
  • Educational

Scientific Approaches

We'll be analyzing subsequent visits and looking at a range of features including vital signs, laboratory measurements, and survey responses. We anticipate we'll be using the PERSON, VISIT_OCCURRENCE, MEASUREMENT, and OBSERVATION tables. From these features we'll apply logistic regression and deep learning to build a predictive model for readmission risk. We'll identify the corresponding importance of features using odd-ratios or SHAP values.

Anticipated Findings

We anticipate that we'll be able to achieve a performant predictive model for the readmission of patients with AKI. To our knowledge this is the first such study conducted on All of Us.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Job Shiach - Graduate Trainee, University of California, San Diego
  • Aaron Boussina - Graduate Trainee, University of California, San Diego
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