I'm a healthcare data analyst with a unique combination of pharmacy expertise and health informatics training.
My work spans the full data lifecycle—from wrangling EHR datasets and ensuring HIPAA compliance to deploying ML models that stratify patient risk. I'm equally comfortable writing SQL queries, building Power BI dashboards, and explaining technical findings to non-technical stakeholders.
🏥 Currently: Data Analyst at Purkayastha Lab for Health Innovation (Indiana University), leading NLP and predictive modeling projects on EHR, clinical and imaging datasets
🔬 Recent Win: Winner of Emory Health AI Datathon 2025 - developed a bias evaluation framework for medical imaging AI systems
📊 I work with:
- Analytics: SQL, Python, R, Machine Learning (Random Forest, SVM, Logistic Regression), SAS (Basic)
- Visualization: Tableau, Power BI, DHIS2
- Healthcare Standards: HL7/FHIR, ICD-9/10, SNOMED-CT, LOINC, RxNorm
- Specialization: Clinical NLP, EHR Systems (Epic, OpenMRS, OpenEMR, REDCap), Predictive Modeling
📝 Published Research: JMIR 2025 - Evaluating LLMs for medical coding and readmission risk prediction (85% accuracy on ICD-9 coding)
💡 Impact Highlights:
- Reduced data processing time by 60% through automated biomedical ontology pipelines
- Mapped ANC2 coverage gaps identifying 23 underserved areas requiring intervention across 16 districts
- Developed predictive models achieving 82% accuracy, enabling risk stratification for 3,200+ high-risk cardiovascular patients
- Reduced manual data reconciliation by 30% with reusable FHIR integration pipeline
- ✉️ You can contact me at raajithamuthyala@gmail.com
- 🧠 I'm learning Clinical NLP and exploring AI fairness in healthcare systems
- 🤝 Open to collaborating on healthcare analytics, clinical decision support, and health informatics projects
