Bridget Onyeije
Healthcare Data Analyst | Pharm D Candidate
"Turning healthcare data into decisions”
About Me
I’m Bridget, a Healthcare Data Analyst and PharmD student passionate about turning health data into clarity and actionable insights.I help hospitals, clinics, and healthcare teams make smarter, data-driven decisions using Power BI, Excel, and SQL.Let’s make your healthcare data work for you!
Skills & Tools
💻 Data Analytics Tools:
Power BI · Excel · MySQL · SQL Server📊 Data Skills:
Data Cleaning · Data Modeling · DAX · Power Query · Visualization · Dashboard Design · Data Storytelling🏥 Healthcare Knowledge:
Clinical Pharmacy · Healthcare Operations · Patient Data Analysis · Outcome Evaluation🧠 Soft Skills:
Analytical Thinking · Attention to Detail · Communication · Problem-Solving · Collaboration
My Projects
Tracking the Pandemic — CMS Nursing Home COVID-19 Dashboard
Overview:
Analyzed national nursing home COVID-19 data from the Centers for Medicare & Medicaid Services (CMS) to reveal trends in infections, staff vaccination, and facility quality.Using Excel (Power Query, DAX), I cleaned and visualized over 14,000 records, transforming raw public data into an interactive dashboard that highlights infection hotspots and reporting
What Patients Say — HCAHPS Patient Experience Dashboard
Overview:
Analyzed the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) dataset to evaluate how patients rated their hospital experiences across U.S. states and facility types.Using Power BI, I cleaned, modeled, and visualized survey data to identify key drivers of patient satisfaction — including communication, responsiveness, and overall hospital rating.
Behind the Numbers — SQL-Based Exploratory Data Analysis of Medical Insurance Costs
Overview:
Performed an in-depth exploratory data analysis (EDA) on medical insurance cost data using MySQL to identify key factors influencing healthcare spending.Through structured queries and aggregation techniques, I explored relationships between age, BMI, smoking status, and charges, revealing how lifestyle and demographics affect medical costs.