Evidence Synthesis Services

Transforming Data into Actionable Evidence for Informed Decision-Making

In the era of evidence-based medicine, Evidence Synthesis plays a critical role in aggregating, analyzing, and interpreting research findings to inform clinical guidelines, healthcare policies, regulatory approvals, and reimbursement strategies. At Clievi, we specialize in comprehensive Evidence Synthesis Services, employing advanced methodologies to provide robust, high-quality evidence for healthcare decision-makers, regulatory agencies, and life sciences organizations.

Our Evidence Synthesis Solutions

1. Systematic Literature Review (SLR)

• Comprehensive Search Strategy: Conducting structured searches across major databases such as PubMed, Embase, Cochrane Library, Web of Science, and Scopus, ensuring complete coverage of relevant literature.

• PICO Framework Implementation: Defining research questions using Population, Intervention, Comparison, and Outcomes (PICO) to maintain systematic and focused analysis.

• Risk of Bias Assessment: Evaluating study quality using validated tools like Cochrane Risk of Bias (RoB), ROBINS-I, and Newcastle-Ottawa Scale (NOS).

• PRISMA-Compliant Reporting: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for transparent and replicable reviews.

2. Meta-Analysis

• Quantitative Evidence Aggregation: Pooling results from multiple studies using fixed-effects and random-effects models to derive statistically significant conclusions.

• Heterogeneity Assessment: Utilizing I² statistics, Cochran’s Q test, and subgroup analyses to identify variability among studies.

• Publication Bias Detection: Conducting funnel plot analysis and Egger’s test to assess the potential impact of selective reporting.

• Network Meta-Analysis (NMA): Comparing multiple interventions using Bayesian and frequentist approaches when direct head-to-head comparisons are unavailable.

3. Real-World Data (RWD) Synthesis

• Integrating Observational Data: Merging insights from Electronic Health Records (EHRs), insurance claims, registries, and digital health data.

• Comparative Effectiveness Research (CER): Analyzing real-world treatment outcomes to support clinical decision-making and regulatory submissions.

• Causal Inference Techniques: Implementing propensity score matching (PSM), instrumental variable analysis (IVA), and inverse probability weighting (IPW) to reduce confounding.

4. Health Technology Assessment (HTA) and Reimbursement Support

• HTA Dossier Preparation: Developing evidence packages in alignment with global HTA body requirements, including NICE (UK), CADTH (Canada), ICER (US), and IQWiG (Germany).

• Cost-Effectiveness and Budget Impact Modeling: Conducting Markov models, Monte Carlo simulations, and microsimulation analyses to assess economic value.

• Indirect Treatment Comparisons (ITC): Performing Matching-Adjusted Indirect Comparisons (MAIC) and Simulated Treatment Comparisons (STC) when head-to-head trials are lacking.

5. Clinical Practice Guideline Development

• Evidence Grading & Synthesis: Utilizing frameworks such as GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) to classify evidence strength.

• Consensus Methodologies: Employing Delphi panels, Nominal Group Techniques (NGT), and expert opinion gathering to formulate practice recommendations.

• Guideline Adaptation & Updating: Revising and adapting existing guidelines to incorporate latest evidence and emerging therapies.

6. Pharmacovigilance and Post-Marketing Evidence Synthesis

• Drug Safety & Adverse Event Monitoring: Aggregating spontaneous reporting system (SRS) data, pharmacovigilance databases, and literature-based case reports to evaluate drug safety.

• Benefit-Risk Assessment: Applying quantitative modeling techniques, including multi-criteria decision analysis (MCDA) and Bayesian risk-benefit frameworks.

• Signal Detection & Risk Management Planning: Identifying safety signals using disproportionality analysis (PRR, ROR) and machine learning-based signal detection.

Why Choose Clievi for Evidence Synthesis?

• Global Regulatory Alignment: Expertise in conducting evidence synthesis in accordance with FDA, EMA, NICE, CADTH, and other regulatory agency requirements.

• Advanced Analytical Techniques: Proficiency in biostatistics, Bayesian modeling, and AI-driven literature mining for high-precision synthesis.

• Multi-Disciplinary Expertise: A team of epidemiologists, biostatisticians, medical writers, and health economists delivering high-quality evidence synthesis reports.

• Customizable and Scalable Solutions: Tailored approaches to meet the diverse needs of pharmaceutical companies, healthcare providers, policymakers, and regulatory bodies.

Get Started with Clievi’s Evidence Synthesis Services

Leverage the power of evidence-based insights to drive informed healthcare decisions. Contact Clievi today to explore how our Evidence Synthesis Solutions can support your clinical, regulatory, and market access objectives.