The RWE Statistical Programmer (US) is responsible for developing high-quality, analysis-ready datasets and statistical outputs using Real-World Data (RWD), with a strong focus on U.S. healthcare databases such as CMS Medicare and Medicaid claims. The role focuses on building analysis-ready datasets, producing high-quality statistical outputs (TLFs), and ensuring end-to-end traceability and quality control to support publications, regulatory submissions, label expansions and internal evidence generation.
Key Responsibilities
· Program and manage real-world evidence (RWE) datasets using U.S. claims, EHR/EMR, registry, and CMS data sources.
· Work extensively with CMS databases including Medicare, and Medicaid data, Beneficiary Summary Files, and CCW data.
· Implement retrospective observational study designs such as cohort, case-control, and cross-sectional studies.
· Develop cohort selection logic including inclusion/exclusion criteria, continuous enrollment, washout periods, index date, baseline, and follow-up windows.
· Derive drug exposure episodes using Medicare Part D (PDE) data, including adherence (PDC/MPR), persistence, switching, and discontinuation.
· Program claims-based outcome definitions using ICD-9/10, CPT/HCPCS, DRG, and NDC codes.
· Create covariates including demographics, comorbidities (Charlson/Elixhauser), CCW chronic condition flags, and healthcare utilization metrics.
· Support statistical analyses such as descriptive statistics, ANCOVA, regression models, time-to-event analyses, and comparative effectiveness studies.
· Prepare analysis datasets for propensity score methods including matching, stratification, and inverse probability weighting (IPTW).
· Generate Tables, Listings, and Figures (TLFs) for study reports, publications, HTA submissions, and payer dossiers.
· Develop patient attrition flow diagrams, treatment patterns, and real-world utilization summaries.
· Perform independent QC of datasets, programs, and outputs to ensure accuracy, traceability, and audit readiness.
· Maintain comprehensive programming documentation including specifications, QC logs, status trackers and version control.
· Ensure compliance with SOPs, data privacy requirements, and industry-established standards (CDISC, regulatory guidance, etc.).
· Collaborate closely with Biostatistics, Epidemiology, HEOR, Medical Affairs, Market Access and remote programming teams.
· Perform Programming Lead/Client Point of Contact responsibilities such as attending meetings, programming coordination, final delivery reviews, timelines and resource monitoring, as required,
Required Qualifications
· Bachelor’s or Master’s (preferred) degree in Epidemiology, Statistics, Mathematics, Economics, Biological or Data Sciences or related field.
· Overall, 8+ years of experience in statistical programming with 5 years of hands-on statistical programming experience in RWE or observational studies with CMS Data.
Key Skills
· Strong hands-on experience with U.S. CMS data (Medicare and/or Medicaid claims).
· Experience with other real-world data sources, such as claims, EHR/EMR, and/or registry data helpful.
· Good understanding of observational study design and real-world data limitations (bias, confounding, missingness) and their application to regulatory, safety, and scientific objectives.
· Strong SAS programming skills
· Experience in R programming (e.g., tidyverse, survival, MatchIt, tableone) is preferred.
· Hands-on experience with propensity score methods, survival analysis, and advanced regression models.
· Experience handling large datasets and performing complex derivations and cohort logic.
· Experience working with databases and cloud platforms (SQL, Snowflake, Databricks, AWS/Azure).
· Familiarity with CDISC standards (SDTM/ADaM) and/or RWE Custom Data Models (CDMs) such as OMOP, Sentinel, PCORnet or similar.
· Knowledge of healthcare coding systems such as ICD-9/ICD-10, CPT/HCPCS, NDC, LOINC, SNOMED (as applicable).
· Exposure to publication-ready output development and Regulatory/HTA submission deliverables.
· Good communication skills and ability to work in cross-functional teams.
CMS data is basically healthcare records in the US collected by Centres for Medicare & Medicaid Services.
It includes information like hospital visits, doctor appointments, medicines people take, and medical costs.
RWE (Real-World Evidence) means using this real-life data (not clinical trials) to understand:
· How patients are actually treated
· Which treatments work better in the real world
· How much healthcare costs
SAS, CMS Data, Medicare Claims, Medicaid Claims, Real-World Evidence (RWE), Observational Studies, Cohort Derivation, Claims Data Programming, Analysis-Ready Dataset Creation, ICD-9, ICD-10, CPT, HCPCS, NDC, TLFs, Propensity Score Matching, IPTW, Survival Analysis, Regression Models, QC, Large Dataset Handling