RWE Analyst (Real-World Evidence)
Profile Code: AL-HLT-05
- ₹6.5 LPA (Median Salary)
- Lecture Duration 2hrs
- Course Duration 16 Weeks
Skills You Learn: Real-World Evidence (RWE) Analytics | Healthcare Data Analysis | Epidemiology | Observational Research Methods | Statistical Modeling | SAS | R Programming | Python for Data Analysis | SQL | Data Visualization | Health Outcomes Research | Scientific & Medical Writing
Overview Video

About This Course
An RWE (Real-World Evidence) Analyst in the healthcare and life sciences industry focuses on analyzing real-world data from sources such as electronic health records, claims data, and patient registries to generate clinical and business insights. This course equips learners with the skills to clean, analyze, and interpret healthcare datasets to support research, treatment effectiveness studies, and policy decisions. Participants gain hands-on experience with tools like Excel, SQL, and BI dashboards, along with exposure to statistical analysis techniques. The program emphasizes real-world data analysis, outcomes research, and evidence generation in healthcare settings. Learners will understand how to evaluate treatment patterns, measure outcomes, and support data-driven decision-making for healthcare providers and organizations. By the end of the course, they are prepared for roles in healthcare analytics and research, with career progression into clinical analytics, health economics, and data science leadership positions.
Course Content
4 modules · 16 weeks · 2hrs/dayExcel Course
The **Excel Course** covers basic to advanced concepts for Real-World Evidence (RWE) Analysts in the Healthcare and Life Sciences industry, including workbook management, formulas, functions, data validation, sorting, filtering, conditional formatting, Pivot Tables, Pivot Charts, XLOOKUP, INDEX-MATCH, Power Query, Power Pivot, patient outcomes analysis, healthcare KPI reporting, cohort analysis, statistical functions, dashboards, What-If Analysis, Solver, VBA automation, trend analysis, reimbursement reporting, data visualization, research reporting, and interactive dashboards to analyze real-world healthcare data, generate evidence-based insights, and support clinical and business decision-making.
SQL Course
The **SQL Course** covers basic to advanced concepts for Real-World Evidence (RWE) Analysts in the Healthcare and Life Sciences industry, including database fundamentals, SELECT queries, filtering, sorting, joins, aggregate functions, GROUP BY, HAVING, subqueries, Common Table Expressions (CTEs), window functions, CASE statements, views, stored procedures, indexing, query optimization, transaction management, patient data extraction, claims data analysis, cohort identification, healthcare reporting, data validation, clinical research analytics, and large dataset management to retrieve, transform, and analyze real-world healthcare data for evidence generation and informed decision-making.
Power BI/Tableau Course
The **Power BI/Tableau Course** covers basic to advanced business intelligence concepts for Real-World Evidence (RWE) Analysts in the Healthcare and Life Sciences industry, including data integration, data transformation, data modeling, DAX or calculated fields, KPI development, dashboard creation, interactive visualizations, patient outcome dashboards, claims analytics, healthcare performance reporting, predictive analytics, drill-through reports, automated reporting, executive dashboards, compliance reporting, forecasting visualization, performance monitoring, data storytelling, and business intelligence techniques to transform real-world healthcare and clinical data into actionable insights for research, policy evaluation, and strategic decision-making.
HIS/Claims Data Course
The **HIS/Claims Data Course** covers basic to advanced concepts for Real-World Evidence (RWE) Analysts in the Healthcare and Life Sciences industry, including Hospital Information System (HIS) fundamentals, medical claims processing, patient record management, diagnosis and procedure coding, insurance claims analysis, reimbursement workflows, healthcare utilization analysis, longitudinal patient tracking, clinical data integration, data quality management, regulatory compliance, audit trails, reporting, data governance, interoperability standards, claims validation, operational analytics, and healthcare data management to support real-world evidence generation, patient outcome research, and evidence-based healthcare decision-making.
Key Responsibilities
- Analyze real-world healthcare data from claims, EHRs, and registries
- Design and execute observational studies
- Evaluate treatment effectiveness and patient outcomes
- Develop statistical models and evidence-generation frameworks
- Conduct comparative effectiveness and health outcomes research
- Clean, validate, and integrate healthcare datasets
- Prepare reports, dashboards, and scientific publications
- Support regulatory, market access, and commercial decisions
- Collaborate with clinical, epidemiology, and medical affairs teams
- Provide evidence-based insights to improve patient care and healthcare strategies
Growth Path
Tools Used
Perfect For
Life Sciences Graduates | Public Health Professionals | Biostatisticians | Epidemiologists | Clinical Research Professionals | Pharmacists | Healthcare Data Analysts | Medical Affairs Professionals | Biotechnology Graduates | Early-Career Healthcare Analytics Aspirants
Fee Structure
Mentor
Analytics Learners
Professional Analyst & Mentor
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