How aaminahmq/edwaittime works
The repository combines a notebook-based NHAMCS analysis with a Dash dashboard presenting nationally weighted ED wait-time findings. The documented workflow cleans and weights survey records, then branches into weighted EDA, bottleneck analysis, and predictive modeling; the dashboard presents results and methodology to hospital-oriented readers. Notebook source was not sampled, so pipeline links follow the README rather than inspected implementation; generated data and figures are documented outputs, not files present in the tree.
Main entry points: 01_data_prep.ipynb Prepare and clean · app4.py Dash application · analytics.py Analytics results · assets Analysis figures
Components 17
Survey inputs
- NHAMCS SAS files
Analysis pipeline
- Prepare and clean
notebooks/01_data_prep.ipynb - Weighted EDA
notebooks/02_weighted_eda.ipynb - Bottleneck analysis
notebooks/03_bottleneck_analysis.ipynb - Arrival modeling
notebooks/04_modeling.ipynb
Analysis outputs
- Cleaned EDA data
- Arrival model data
- Retrospective data
- Analysis figures
appengine/assets - Bottleneck results
- Model results
Dashboard
- Dash application
appengine/app4.py - Project overview
appengine/pages/home.py - Analytics results
appengine/pages/analytics.py - Methods page
appengine/pages/methods.py
Other components
- Project analyst
- Dashboard visitor
Connections 20
- Project analyst → Prepare and clean: runs workflow
- NHAMCS SAS files → Prepare and clean: loads survey data
- Prepare and clean → Cleaned EDA data: writes cleaned data
- Prepare and clean → Arrival model data: writes dataset
- Prepare and clean → Retrospective data: writes dataset
- Weighted EDA → Cleaned EDA data: reads data
- Weighted EDA → Analysis figures: writes plots
- Retrospective data → Bottleneck analysis: feeds analysis
- Bottleneck analysis → Bottleneck results: writes results
- Bottleneck analysis → Analysis figures: writes plots
- Arrival model data → Arrival modeling: feeds training
- Arrival modeling → Model results: writes evaluation
- Arrival modeling → Analysis figures: writes plots
- Dashboard visitor → Dash application: opens dashboard
- Dash application → Project overview: dispatches page
- Dash application → Analytics results: dispatches page
- Dash application → Methods page: dispatches page
- Analytics results → Analysis figures: displays plots
- Analytics results → Bottleneck results: presents findings
- Analytics results → Model results: presents metrics