Expertise

• Cost-effectiveness and cost-utility analysis

• Budget-impact analysis

• Decision trees, Markov models and microsimulation

• QALY and utility analysis

• Cost-of-illness and burden studies

• Sensitivity, scenario and uncertainty analysis

• Adaptation across healthcare jurisdictions

Objective: Determine whether healthcare interventions generate sufficient clinical and societal value to justify their costs.

• Observational study design

• Existing database and registry analysis

• Burden-of-disease studies

• Treatment patterns and healthcare utilization

• Clinical and economic outcomes

• Patient-reported outcomes

• Real-world effectiveness

Objective: Convert routinely collected and observational data into evidence relevant to clinical practice and healthcare decision making.

• Systematic and targeted literature reviews

• Evidence-gap analysis

• Economic evidence reviews

• HTA evidence development

• Payer evidence requirements

• Value dossiers and reimbursement support

Objective: Establish what is already known, identify what remains uncertain and determine what evidence is needed for adoption or reimbursement.

• Service-delivery evaluation

• Screening programmes

• Access and equity

• Workforce and task-sharing models

• Public-health impact modelling

• Resource allocation

• Programme affordability and sustainability

Objective: Determine how effective interventions can be translated into efficient and sustainable healthcare delivery.

• Biostatistics for clinical and observational data

• Survival analysis, regression modeling, causal inference

• Data visualization and reproducible analytics

Objective: To ensures methodological rigor and credibility

• Peer-reviewed manuscripts

• Conference abstracts and presentations

• Scientific reports

• Policy briefs

• Economic investment cases

• Evidence communication

Objective: Ensure that rigorous analysis results in evidence capable of influencing science and decision making.