RWE Patient Data Analysis Services

Unlocking Real-World Evidence for Informed Clinical and Regulatory Decisions

In today’s rapidly evolving healthcare landscape, Real-World Evidence (RWE) has become a cornerstone for clinical decision-making, regulatory submissions, market access strategies, and post-market surveillance. At Clievi, we specialize in RWE Patient Data Analysis, leveraging advanced analytics, biostatistics, and machine learning to derive actionable insights from real-world patient datasets.

Our RWE Patient Data Analysis Services

1. Real-World Data (RWD) Acquisition and Integration

• Data Sourcing: Comprehensive extraction from Electronic Health Records (EHRs), insurance claims databases, patient registries, clinical trial datasets, and wearable health devices to ensure robust and diverse data collection.

• Data Cleaning & Curation: Standardization, de-identification, and transformation of patient-level data to comply with HIPAA, GDPR, and 21 CFR Part 11 regulations, ensuring high-quality, research-ready datasets.

• Interoperability & Integration: Aggregation and harmonization of structured and unstructured data sources using advanced data mapping techniques and industry standards like FHIR and OMOP Common Data Model to enable seamless analysis across multiple datasets.

2. Comparative Effectiveness Research (CER)

• Treatment Outcomes Analysis: Assessing real-world drug effectiveness and safety using observational data to supplement clinical trial findings and support regulatory decision-making.

• Longitudinal Studies: Evaluating disease progression, treatment adherence, healthcare utilization trends, and safety profiles over extended periods using time-series analysis.

• Propensity Score Matching (PSM) & Causal Inference Techniques: Reducing confounding in observational studies by applying statistical methods such as inverse probability weighting (IPW) and instrumental variable analysis (IVA) for unbiased treatment comparisons.

3. Patient-Centered Outcomes Research (PCOR)

• Patient-Reported Outcomes (PROs): Integrating quality-of-life (QoL) measures, symptom tracking, and treatment satisfaction surveys into real-world datasets to enhance patient-centered care.

• Health Economics & Outcomes Research (HEOR): Conducting cost-effectiveness, budget impact, and cost-utility analyses to inform payer and policymaker decisions.

• Subpopulation Analysis & Health Disparities Research: Identifying variations in treatment response across race, gender, socioeconomic status, and comorbidities to support personalized medicine initiatives.

4. AI-Driven Predictive Analytics

• Risk Stratification Models: Developing machine learning-based algorithms to predict disease progression, hospitalization risks, and adverse events, enabling proactive healthcare interventions.

• Deep Learning & NLP for Unstructured Data Analysis: Extracting valuable insights from clinical notes, radiology reports, pathology data, and social determinants of health (SDoH) to improve predictive modeling.

• Survival Analysis & Predictive Modeling: Applying Kaplan-Meier survival curves, Cox proportional hazards models, and Bayesian inference to evaluate treatment impact and forecast long-term outcomes.

5. Regulatory and Market Access Support

• FDA & EMA Compliance: Designing RWE studies that meet ICH E9(R1), ISPOR, and STaRT-RWE guidelines for regulatory submissions.

• Post-Marketing Surveillance (PMS) & Pharmacovigilance: Monitoring real-world drug performance, detecting adverse drug reactions (ADRs) and off-label usage trends through active surveillance.

• Health Technology Assessment (HTA) Reports & Reimbursement Strategy: Generating evidence for payers, healthcare decision-makers, and regulatory bodies to support drug pricing, formulary placement, and value-based contracting.

Why Choose Clievi for RWE Patient Data Analysis?

• Regulatory Expertise: Adherence to global compliance standards, ensuring seamless regulatory submissions and post-market regulatory intelligence.

• Advanced Analytics & AI: Leveraging state-of-the-art statistical methodologies, machine learning, and real-world data modeling techniques to generate high-impact insights.

• End-to-End Data Solutions: Offering comprehensive data acquisition, analysis, visualization, and reporting tailored to industry needs.

• Industry-Specific Knowledge: Deep expertise in pharmaceuticals, biotechnology, medical devices, and digital health ensures targeted and relevant research outcomes.

Get Started with Clievi’s RWE Services

Transform real-world patient data into clinically meaningful, regulatory-grade evidence. Contact us today to learn how our RWE Patient Data Analysis solutions can optimize your clinical research, regulatory strategy, and market access planning.