Data Analyst Healthcare

Hima Bindu Bagam

Healthcare Data Analyst

443-***-**** ****.*@************.*** Halethorpe, MD

Professional Summary

Around 5 years of experience as a Healthcare Data Analyst with expertise in healthcare data analysis, SAS programming, reporting, clinical data management, and regulatory compliance. Proϐicient in analyzing complex healthcare datasets to optimize operational efϐiciency through actionable data insights and predictive modeling.

Proϐicient in Data Analysis & Reporting, leveraging SQL, Python, R, and Excel to analyze large healthcare datasets, extract meaningful insights, and generate detailed reports to support business and clinical operations.

Adept at Developing Interactive Dashboards & Visualizations using Power BI, Tableau, and other BI tools to present complex data in a clear, actionable format, enabling stakeholders to make data-driven decisions efϐiciently.

Deep Understanding of Healthcare Regulations & Compliance, including HIPAA, ICH-GCP, CPT coding, HL7, and CMS guidelines, ensuring data privacy, security, and regulatory adherence in all healthcare data projects. Skills & Certiϐication

Languages: SAS (Base, Macros, SQL, ODS), Python (Pandas, NumPy, Matplotlib, SciPy, Seaborn), R, SQL

CDISC Standards: SDTM, ADaM, Pinnacle 21, SDRG, ADRG, MedDRA, WHO Drug Dictionary

Business Intelligence & ETL: SQL Server Integration Services (SSIS), Tableau, Power BI, SQL Server Management Studio (SSMS), SQL Server Analytical Services (SSAS), AWS Cloud

Healthcare Data tools and Skills: Electronic Health Records (EHR), Trial Master File (TMF), Healthcare Information Systems, ICSR Case Processing, AE/SAE reconciliation, eCRF annotation

Regulations & Guidelines: HIPAA, FDA, ICH-GCP, CFR Part 11

Databases and Tools: SQL Server, MySQL, MongoDB, Snowϐlake

Certiϐication: SAS Base Certiϐication

Education

Master’s in health information technology University of Maryland, Baltimore County, Baltimore, MD Doctor of Pharmacy Kakatiya University, Warangal, Telangana Work Experience

Amgen, MD Clinical Data Analyst Jun 2024 – Present

Developed SDTM datasets using SAS Macros and validated them using Pinnacle 21 to ensure FDA/CDISC compliance.

Developed Tableau dashboards and predictive models in Python/Power BI to reduce hospital readmission rates by 15% and enhance treatment efϐicacy by 20%.

Implemented QC framework for SDTM datasets; reduced validation errors by 40%.

Conducted quarterly HIPAA risk assessments, identifying and mitigating 95% of potential data threats.

Optimized SQL queries in SSMS, enhancing performance by 25% through indexing and tuning.

Automated EHR-based decision support systems to increase adherence to clinical guidelines by 10%.

Migrated healthcare data to AWS Cloud, lowering infrastructure costs by 25%.

Integrated healthcare APIs with Python to automate clinical data collection and improve analysis turnaround time.

Developed and validated derived datasets using PROC COMPARE and PROC SQL.

Created statistical reports using PROC MEANS, PROC FREQ, PROC UNIVARIATE, and PROC REPORT.

Worked on SAE reconciliation, ICSR processing, and adverse event analysis submitted to DSMBs.

Reviewed CRFs and clinical protocols; annotated CRFs and developed submission documents like SDRG and ADRG.

Applied survival analysis, descriptive statistics using SAS procedures like PROC MEANS, FREQ, UNIVARIATE, and PROC REPORT. Cognitive Healthcare, India Clinical Data Analyst Jan 2020 – Dec 2022

Integrated Power BI with electronic health records (EHRs) to develop real-time dashboards for monitoring patient vital signs, triggering critical alerts, and reducing patient mortality by 15%.

Designed predictive analytics models in Power BI to optimize resource allocation, leading to a 20% reduction in ER congestion.

Leveraged Power BI's collaboration features to support cross-functional decision-making and accelerate project timelines.

Developed and executed ETL pipelines using SSIS and Python (Pandas) to automate data extraction from APIs, EHRs, claims databases, and clinical trials, achieving a 30% reduction in manual processing time.

Built automated data cleaning routines using Python and SQL, enhancing data quality and analysis efϐiciency.

Performed advanced data wrangling (ϐiltering, merging, handling missing values) in Pandas to ensure accurate and clean datasets.

Created custom SQL reports and dashboards to deliver actionable insights to stakeholders, improving operational efϐiciency by 10%.

Extracted and analyzed patient demographics, diagnoses, procedures, and outcomes from EHRs using optimized SQL scripts, improving data accuracy and consistency.

Analyzed clinical trial data for evaluating treatment efϐicacy and safety, ensuring compliance with FDA standards.

Led QC validation of SDTM datasets using Pinnacle 21, ensuring compliance with CDISC and regulatory standards.

Developed and executed ADaM datasets and mapping specifications based on SAP and study protocols.

Developed automated SAS scripts for clinical data transformation and validation, reducing manual review time by 50%.

Utilized PROC SQL, PROC MEANS, and PROC FREQ for statistical analysis and regulatory reporting.

Conducted SAE reconciliation and reviewed ICSR cases, adhering to FDA, ICH-GCP, and global safety reporting regulations.

Annotated CRFs, supported eCRF development, and maintained data consistency standards.

Applied various imputation techniques (LOCF, BOCF, WOCF) for handling missing data in ADaM datasets.

Collaborated with cross-functional teams to implement SDTM mapping and dataset integration, increasing submission readiness.

Designed and executed validation plans for clinical trial datasets, ensuring data integrity and regulatory compliance.

Worked closely with stakeholders to establish and maintain data standards and naming conventions, facilitating effective data governance.

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