UAC Care Pipeline Analysis

Care Transition Efficiency & Placement Outcome Analytics

Organization: U.S. Department of Health and Human Services (HHS) — Unified Mentor Program

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📌 Project Overview

This project reframes the UAC (Unaccompanied Alien Children) dataset from a capacity monitoring lens to a process efficiency and outcome evaluation lens.

By analyzing how effectively children move through the care pipeline, it provides actionable insights for improving reunification timelines, reducing delays, and strengthening child welfare outcomes.

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🔄 Care Pipeline Stages

Apprehension → CBP Custody → HHS Care → Sponsor Placement (Discharge)

Stage	Description
CBP Custody	Initial holding after apprehension
HHS Care	Medical screening, sheltering, case management
Sponsor Placement	Discharge and reunification with vetted sponsor

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📁 Project Structure

uac-care-pipeline/
│
├── data/
│   └── HHS_Unaccompanied_Alien_Children_Program.csv
│
├── notebooks/
│   └── uac_care_pipeline_analysis.ipynb
│
├── app/
│   └── app.py                  ← Streamlit Dashboard
│
├── reports/
│   └── report.md               ← Research Paper / EDA Report
│
├── requirements.txt
└── README.md

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📊 KPIs Analyzed

KPI	Formula	Description
Transfer Efficiency Ratio	Transfers ÷ CBP Custody	CBP → HHS speed
Discharge Effectiveness	Discharges ÷ HHS Care	Placement success rate
Pipeline Throughput Rate	Discharges ÷ Apprehensions	Overall system movement
Backlog Accumulation Rate	Apprehensions − Discharges	Delay severity
Outcome Stability Score	7-day Rolling Std Dev	Consistency of placements

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🚀 How to Run

1. Install Dependencies

pip install -r requirements.txt

2. Run Jupyter Notebook

jupyter notebook notebooks/uac_care_pipeline_analysis.ipynb

3. Run Streamlit Dashboard

streamlit run app/app.py

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🔍 Key Findings

• Transfer Efficiency (~69%) — Children move from CBP to HHS at a moderate rate
• Discharge Effectiveness (~2%) — Major bottleneck at HHS stage; very low placement rate
• 2025 Sharp Decline — Significant drop in both inflow and outflow suggesting systemic shift
• Weekend throughput slightly higher than weekday throughput
• Prolonged stagnation in 2025 — discharge effectiveness consistently low with no recovery

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📦 Deliverables

• ✅ Jupyter Notebook (EDA + KPI Analysis)
• ✅ Streamlit Dashboard (Live Analytics)
• ✅ Research Report (Insights + Recommendations)
• ✅ README (Project Documentation)
• ✅ Requirements.txt

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👤 Author

Jessica Suri