Professional Summary
Dual-certified Health Data Analyst and medical coder (CHDA #287957 | CCS #271762) with a biochemistry and bioinformatics foundation and 10+ years of experience turning clinical and claims data into practical insights for quality, utilization, and financial performance. Strong hands-on experience with SQL, Python, and R for extracting, transforming, and analyzing health data across Medicare, Medicaid, Exchange, and Commercial lines of business.
Skilled in inpatient DRG/APR-DRG validation, risk adjustment (HCC), and quality measurement (HEDIS), as well as operational analytics including trend analysis, cohort building, forecasting, and root-cause investigation of gaps in care, cost drivers, and denial patterns. Brings a researcher's mindset to data validation and interpretation—comfortable working with EMR (Epic) and claims data, FHIR/LOINC/SNOMED, and cross-functional teams in Quality Improvement, Population Health, and Clinical Operations.
Selected Highlights
- Health data analytics: Build SQL/Python pipelines that analyze millions of claims and EMR records to identify quality gaps, coding errors, and utilization patterns - work that supports HEDIS reporting, audit readiness, and contract performance for multiple health plans.
- Payment integrity: Validate DRG/APR-DRG assignments and HCC risk scores through detailed medical record review - ensuring coding accuracy that directly impacts health plan revenue, audit compliance, and Stars ratings.
- Clinical data standards: work with LOINC, SNOMED CT, and FHIR to normalize and integrate EMR and claims data for analytics and quality reporting.
- Multilingual communicator: English, Spanish, Italian, and Portuguese, able to explain complex data findings clearly to clinicians, operations teams, and executives.
Experience
- Build SQL/Python analyses that help health plans identify coding accuracy issues, quality measure gaps, and utilization patterns across multiple lines of business, supporting HEDIS reporting, audit readiness, and contract performance.
- Validate medical records for DRG/APC assignment and HCC risk adjustment accuracy using ICD-10-CM/PCS, CPT, and HCPCS-II, work that ensures reliable analytics and supports health plan audit compliance.
- Serve as subject matter expert on inpatient DRG/APR-DRG validation and HCC risk adjustment, and support HEDIS measure analysis and reporting by translating technical specifications into SQL/Python/R logic and ensuring accurate denominator, numerator, and exclusion definitions.
- Create interactive dashboards (Flask, R Shiny, HTML/JavaScript) that make HEDIS performance, denial patterns, and readmission risk visible to clinical and executive teams, turning complex datasets into actionable insights.
- Collaborate with Quality Improvement, Population Health, Clinical Operations, and IT, as well as external vendors and auditors (HSAG, HCPF, CMS, NCQA), to coordinate medical record review, supplemental data integration, audit submissions, and annual requirements such as ROADMAP and IDSS.
- Automate data extraction and quality checks using Python, R, and Google Sheets API, reducing manual workflows, improving data accuracy, and supporting the transition to FHIR-based integrations.
- Analyze denial trends, billing patterns, and coding outcomes to build decision-support models and reports that guide appeals strategies, contract evaluations, and process improvements, and communicate findings clearly to diverse, multilingual audiences.
- Pharmaceutical & OTC Researcher — conducted product safety and efficacy studies, supporting regulatory submissions and product development.
- GMP Compliance Oversight — ensured FDA Good Manufacturing Practice adherence across formulation, testing, and labeling processes.
- Microbiology Data Research — managed laboratory data collection and analysis to validate microbial compliance of OTC skin care products.
- Quality Assurance — collaborated with cross-functional teams to implement corrective actions, maintain audit readiness, and document compliance.
- Cosmetic-grade Formulations — contributed to development of skin care products integrating pharmaceutical standards with consumer safety requirements.
- Applied ICD‑9/ICD‑10‑PCS, CPT, and HCPCS‑II codes while ensuring regulatory compliance.
- Maintained patient records and supported medical billing and payer communications.
- Resolved billing questions with insurers and patients; supported accurate documentation workflows.
- Utilized EHR/billing software to maintain complete, accurate records.
- Reviewed diagnosis coding for completeness and accuracy across assigned care centers.
Education
Certifications, Specializations & Coursework
- Biostatistics in Public Health (Johns Hopkins University) — study design, inference, regression, and interpretation for population-level decisions.
- Health Informatics (JHU) — EHR workflows, interoperability (HL7/FHIR), clinical data standards, privacy, and governance.
- Data Science: Statistics & Machine Learning (JHU) — supervised/unsupervised ML, model validation, regularization, and reproducible analysis.
- Data Science: Foundations using R (JHU) — data wrangling (tidyverse), EDA, reporting, and pipeline automation.
- Large-Scale Database Systems (JHU) — schema design, indexing, transactions, query optimization, and scalable SQL patterns.
- Johns Hopkins Medical Office Manager — clinic operations, scheduling and patient access, compliance, coding/billing workflows, and KPI tracking.
- Data Science (JHU) — end-to-end analytics lifecycle: acquisition → cleaning → modeling → visualization → communication.
- Patient Safety (JHU) — QI frameworks (PDSA), root cause analysis, human-factors principles, and risk mitigation.
Expanded coursework & certificates (optional)
- Taking Safety and Quality Improvement Work to the Next Level (Patient Safety VII)
- Designing for Sustainment: Keeping Improvement Work on Track (Patient Safety IV)
- Foundations of Distributed Database Systems
- Implementing a Patient Safety or Quality Improvement Project (Patient Safety V)
- Reliability, Cloud Computing and Machine Learning
- Measuring the Success of a Patient Safety or Quality Improvement Project (Patient Safety VI)
- Distributed Query Optimization and Security
- Advanced Reproducibility in Cancer Informatics
- Revenue Cycle, Billing, and Coding
- Quality and Safety in Ambulatory Healthcare Management
- Multiple Regression Analysis in Public Health
- Healthcare Delivery for Medical Practice Managers
- Data and Electronic Health Records
- Planning a Patient Safety or Quality Improvement Project (Patient Safety III)
- Hypothesis Testing in Public Health
- Human Resources Management Essentials
- Setting the Stage for Success: An Eye on Safety Culture and Teamwork (Patient Safety II)
- Patient Safety and Quality Improvement: Developing a Systems View (Patient Safety I)
- Simple Regression Analysis in Public Health
- Reproducible Research
- Culminating Project in Health Informatics
- Developing Data Products
- The Outcomes and Interventions of Health Informatics
- Data Science Capstone
- Introduction to Ambulatory Healthcare Management
- The Data Science of Health Informatics
- The Social and Technical Context of Health Informatics
- Leading Change in Health Informatics
- Practical Machine Learning
- Statistical Inference
- The Data Scientist’s Toolbox
- Exploratory Data Analysis
- Getting and Cleaning Data
- R Programming
- Summary Statistics in Public Health
- Regression Models
- Advanced Methods in Machine Learning Applications
- Applied Machine Learning: Techniques and Applications