Manisha Reddy
Summary
Health Data Analyst having 5 years of expertise in healthcare analytics, clinical data evaluation, and health informatics, with substantial practical knowledge in managing EHR, claims, pharmacy, and population health datasets to aid in care quality enhancement, utilization oversight, risk categorization, HEDIS metrics, and value-driven care projects. Has a solid foundation in utilizing statistical analysis, predictive modeling, and machine learning methods to determine high-risk patient groups, assess disease impact, and measure clinical and financial results, along with significant expertise in healthcare data standards and terminologies such as ICD-9/ICD-10, CPT, HCPCS, LOINC, RxNorm, SNOMED CT, DRG, and NDC codes. Skilled in mapping, validating, and normalizing clinical and pharmacy data from various source systems, conducting patient risk adjustment, comorbidity indexing, medication utilization assessments, chronic disease management, and medical cost and utilization evaluations, while working closely with clinicians, pharmacists, quality improvement teams, care coordinators, and operational leadership to convert complex analytical results into actionable insights that enhance patient outcomes, improve care delivery efficiency, and aid cost containment, while ensuring robust data governance, data quality, HIPAA compliance, and analytical precision.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Healthcare Data Analyst
Ascension Health Care
05.2024 - Current
- Implement, enhance, and manage extensive SQL queries across various healthcare datasets, such as EHR, claims, lab, and pharmacy information, while ensuring precision, effectiveness, and repeatability.
- Conduct Source-to-Target Mapping (STTM) to align raw health data with the OMOP Common Data Model (CDM), facilitating standardized analytics and interoperability.
- Utilize FHIR (Fast Healthcare Interoperability Resources) standards to facilitate smooth data transfer and integration among various healthcare systems.
- Work closely with Data Science, Product, and Clinical teams to assist with analytics projects, predictive modeling, dashboard creation, and improvements to product features.
- Create, record, and uphold data transformation workflows, guaranteeing adherence to healthcare data standards, regulatory mandates, and HIPAA regulations.
- Oversee and verify data quality, consistency, completeness, and integrity, recognizing discrepancies and applying corrective measures to uphold confidence in healthcare data.
- Create and execute ETL workflows, data standardization, and integration processes to guarantee dependable, reproducible datasets for research and operational purposes.
- Function autonomously to manage intricate data workflows, encompassing mapping, validation, and analysis, while offering suggestions for enhancements and automation.
- Create analytical datasets for managing population health, risk classification, clinical quality reporting (HEDIS, QPP), and real-world evidence (RWE) research.
- Assist in cloud-centered data storage and processing, with knowledge of Google Cloud Platform (GCP) offerings for expandable data solutions.
- Create and sustain metadata documentation, data dictionaries, and process manuals to assist internal teams and ensure audit preparedness.
- Aid in exploratory data analysis (EDA), cohort formation, and variable specification to support clinical and operational research efforts.
- Actively seek out chances to enhance processes, automate tasks, and improve tools in data mapping, quality assurance, and analytics procedures.
- Share findings, dashboards, and insights with cross-functional stakeholders, converting intricate clinical and operational data into practical recommendations for leadership and product teams.
Data Quality Analyst
Bridgeline Digital
07.2021 - 11.2023
- Managed and examined a collection of extensive EHR, claims, pharmacy, lab, and population health datasets (~millions of patient records) utilizing Python, SQL, and R to aid in population health management, enhance care quality, optimize clinical operations, manage utilization, and implement value-based care programs.
- Developed reproducible analytical results such as dashboards, benchmarks, cohort analyses, clinical quality metrics (HEDIS, QPP), and risk adjustment frameworks to assist health systems in enhancing patient outcomes, operational efficiency, and expense management.
- Created data processing pipelines for EHR, claims, lab, and pharmacy data, encompassing ingestion, cleaning, transformation, normalization, and validation, guaranteeing high-quality and audit-ready outputs that align with HIPAA and regulatory standards.
- Performed feasibility assessments for variable development, patient categorization, and comorbidity evaluation, utilizing insights to enhance data models, source choices, and analytical processes.
- Developed and implemented quality verification processes and resolution protocols to uphold data accuracy, thoroughness, and adherence to clinical and regulatory standards.
- Collaborated with clinical, quality, and operational leaders to share insights, conduct interactive demonstrations, and support data-informed decision-making through healthcare performance metrics and operational KPIs.
- Worked across functions to verify the quality of EHR, claims, lab, and pharmacy data, address issues, and assist in product improvements for real-world evidence (RWE) and population health analytics.
- Utilized AI, predictive modeling, and automation technologies to enhance analytics, validate hypotheses, and streamline workflow efficiency for healthcare decision-making and operational excellence.
Data Analyst Trainee
Bridgeline Digital
01.2021 - 06.2021
- Supported senior analysts with data extraction, cleaning, preprocessing, and integration of EHR, claims, lab, and pharmacy datasets utilizing Python and SQL.
- Assisted in creating analytical datasets, summary reports, dashboards, and calculations for clinical quality measures related to population health, utilization management, and operational performance projects.
- Acquired knowledge of internal coding, workflows, and documentation standards, guaranteeing reproducibility, precision, and compliance with data governance and HIPAA protocols.
- Acquired experience in healthcare data validation, quality assurance, and audit-ready methods, such as detecting data anomalies, addressing discrepancies, and assisting with cohort development.
- Engaged in exploratory data analysis (EDA) and fundamental statistical modeling to comprehend patient demographics, usage patterns, and clinical results.
- Aided in cohort creation, patient classification, and variable identification to facilitate risk adjustment and clinical reporting.
- Worked with cross-functional teams to grasp business and clinical needs and convert them into analytical processes.
- Acquired essential abilities in managing real-world data (RWD), conducting predictive analytics, measuring outcomes, and reporting to aid healthcare decision-making and population health initiatives.
Education
M.S. - Health Informatics
University of North Texas
Denton, Tx12-2025
Skills
- Programming & Analytics: Python (Pandas, NumPy, SciPy, Scikit-learn), R, SQL
- Databases & Querying: Relational Databases, Snowflake, EHR Systems, Claims Databases, Pharmacy and Lab Data, Data Warehousing, BigQuery (GCP)
- Healthcare Standards & Terminologies: HL7 FHIR, OMOP CDM, ICD-9/ICD-10, CPT, HCPCS, LOINC, RxNorm, SNOMED CT, DRG, NDC
- Data Processing & ETL: Data Cleaning, Transformation, Normalization, Ingestion, Quality Checks, STTM (Source-to-Target Mapping)
- Data Modeling & Analytics: Cohort Development, Risk Stratification, Predictive Modeling, Comorbidity Analysis, Clinical Quality Measures (HEDIS, QPP), Population Health Analytics
- Data Visualization & Reporting: Tableau, Power BI, Matplotlib, Seaborn, Dashboards, Benchmarks, KPI Reporting
- Cloud & Tools: Google Cloud Platform (GCP) basic, Git/GitHub, Excel, Data Dictionaries, Metadata Management
- Regulatory & Compliance: HIPAA, Data Governance, Audit-Ready Documentation, Clinical and Operational Data Compliance
- AI & Machine Learning: Predictive Analytics, Supervised & Unsupervised Learning, Workflow Automation, Process Optimization
Certification
Graduate Academic Certificate in Health Data Science
University of North Texas
Timeline
Healthcare Data Analyst
Ascension Health Care
05.2024 - Current
Data Quality Analyst
Bridgeline Digital
07.2021 - 11.2023
Data Analyst Trainee
Bridgeline Digital
01.2021 - 06.2021
M.S. - Health Informatics
University of North Texas