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Personalizing Patient Care in Kerala
Case Study

Personalizing Patient Care in Kerala

30% reduction in readmission rates

The Challenge

A major hospital network in Kerala struggled with high patient readmission rates for chronic conditions. They needed a way to identify at-risk patients post-discharge and intervene with proactive care before their conditions worsened.

The Solution

We built a predictive machine learning model using historical patient data (EHRs), demographics, and clinical notes. The model identifies patients with a high probability of readmission within 30 days. This enabled the care team to provide targeted follow-ups, personalized health plans, and remote monitoring for high-risk individuals. The model was carefully designed to mitigate biases and ensure fairness across different patient demographics.

Key Results

30%

Reduction in 30-day readmission rates

25%

Improvement in care plan adherence

85%

Accuracy in predicting high-risk patients

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