CASE STUDY July 5, 2023
A major Californian Healthcare Provider created an analytics solution to forecast patient readmission risk and Length of Stay (LOS). The goal was to reduce penalties, potentially amounting to millions, imposed by the Affordable Healthcare Act for hospitals with high readmission rates.
Our solution, featuring Logistic Regression for Readmission Risk and Linear Regression for LOS, delivered significant value. We pinpointed crucial disease trend lines, earning appreciation from doctors. The solution identified 25% of readmissions, flagging 5% of patients. LOS predictions were highly accurate, within ±1 day for 60% and ±2 days for 80% of patients.
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