I analyze large public health datasets, run statistical tests, and build dashboards that make population health patterns easier to explore.
Projects from a TruBridge externship, centered on large public health datasets, statistical analysis, and dashboarding to reveal population-level patterns.
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TruBridge · ✅ Verified by Extern · ⏱️ In progress
A TruBridge externship in healthcare data analytics focused on working with large public health datasets, statistical analysis, and dashboarding to examine population-level health patterns.
I analyze large public health datasets, run statistical tests, and build dashboards that make population health patterns easier to explore.
I am Christian Ibegbulem. I completed a TruBridge Healthcare Data Analytics externship where I worked with large public health datasets, applied statistical analysis, and built dashboards to examine population-level health patterns.
Externships
TruBridge Healthcare Data Analytics Externship
TruBridge
Education
Bronx Community College
Health Sciences · Class of 2027
Bronx Community College
CPR Certificate Program · Class of 2027
Bronx Community College
Mental Health First Aid · Class of 2027
Skills
✅ Verified by Extern · ⏱️ In progress
A TruBridge externship in healthcare data analytics focused on working with large public health datasets, statistical analysis, and dashboarding to examine population-level health patterns.
The work analyzed public health datasets to investigate links between socioeconomic variables and health outcomes. The project defined a neighborhood-level research question, selected CDC PLACES and BRFSS datasets, pre-processed and cleaned records, and ran descriptive and exploratory analyses. The analysis used Python to produce histograms, boxplots, and correlation matrices that revealed
I produced a neighborhood-level analysis using CDC PLACES and BRFSS data, cleaned and described over 120,000 BRFSS records, and generated visualizations and correlation analyses showing relationships among income, education, access, and self-reported health.
I defined a research question linking income, education, and healthcare access to health outcomes, searched public health sources, compared datasets, and selected the CDC PLACES dataset (via HealthData.gov) as the most suitable data source for neighborhood-level analysis.
I selected a public health dataset, refined my research question, mapped variables (income, education, insurance, access, health measures), and documented which fields could support disparity and EDA approaches for underserved communities.
I loaded the BRFSS dataset, inspected structure and missingness, computed descriptive statistics, plotted a histogram of general health, a BMI boxplot, and a correlation heatmap, and documented outliers and variables needing cleaning.
The project examined BRFSS 2024 data (120,293 records), cleaned variables, ran descriptive Python analyses, and produced histograms, boxplots, and a correlation matrix. Findings showed links between lower income, lower education, limited healthcare access, and poorer self-reported health.