Health Economics & Outcomes Research

With increasing pressure to control the rising cost of healthcare, there’s a greater need to demonstrate the value of health care treatments in addition to their efficacy. Health Economics and Outcomes Research (HEOR) plays an increasingly vital role in a drug’s approval and reimbursement with payers. HEOR analyses allow us to evaluate the economics of a given treatment and quantify the associated outcomes.

With valuable experience in innovative HEOR solutions, Axtria delivers:

  • Innovative patient-level simulations
  • Customized cost-effectiveness models
  • Clinical trial simulations
  • Burden of disease analyses
  • Experience with real-world data

HEOR CAPABILITIES

HEOR-Patient-Level-Simulations.png

Innovative patient-level simulations: As treatment options become more complex, it is valuable to develop customized patient-level simulations. These simulations allow us to hone in on the value of treatments to different types of patients and analyze scenarios. These simulations can model:

  • Complex treatment patterns
  • Heterogeneous patient populations from real-world data or clinical trials
  • Impact on clinical and economic outcomes
  • Varying benefits across sub-populations
  • Alternative treatment strategies
Cost-effectiveness-models

Customized cost-effectiveness models: Cost-effectiveness analyses are a critical part of a drug’s approval in Health Technology Assessments (HTAs) around the world as well as its adoption in the US. We develop customized cost-effectiveness models, which help ensure the treatment is available for patients for whom the treatment is cost-effective. These models are:

  • Transparent for internal and external audiences
  • Analytically rigorous
  • Well-documented
  • Flexible to meeting changing client needs
  • Adaptable for global stakeholders
Clinical-Trial-Simulation

Clinical trial simulations: Modeling clinical trials allows our clients to make informed decisions during trial design as well as prepare for questions that may be asked after a trial is read-out. With the high costs associated with clinical trials, clinical trial simulations provide a cost-effective means of performing analysis that complements the clinical trial itself.

  • Make informed decisions during trial design
  • Predict trial results
  • Analyze sub-populations of patients and patients from real-world data
  • Estimate continued benefits during off-label period
  • Analyze scenarios with different treatment strategies

Burden of disease analyses: With the rising cost of healthcare, it’s important to quantify the cost, morbidity, mortality, and other hardships associated with diseases. Axtria helps clients by quantifying the burden of a disease, demonstrating the unmet need, and providing valuable insights for cost-effectiveness models

  • Quantify the costs of a disease
  • Measure the implications of uncontrolled disease
  • Generate real-world evidence for cost-effectiveness analysis
  • Demonstrate the value of treatment post-launch
  • Analyze comparative effectiveness
Burden-of-Disease-Analytics
Burden-of-Disease-Analytics

Burden of disease analyses: With the rising cost of healthcare, it’s important to quantify the cost, morbidity, mortality, and other hardships associated with diseases. Axtria helps clients by quantifying the burden of a disease, demonstrating the unmet need, and providing valuable insights for cost-effectiveness models

  • Quantify the costs of a disease
  • Measure the implications of uncontrolled disease
  • Generate real-world evidence for cost-effectiveness analysis
  • Demonstrate the value of treatment post-launch
  • Analyze comparative effectiveness
Real-World-Evidence

Experience with real-world data: As a data analytics company, Axtria has extensive experience in managing and analyzing a wide variety of healthcare data. With the increasing availability of real-world data, Axtria helps clients by generating insightful real-world evidence (RWE) based on anonymized patient data.

  • Anonymized patient-level data
  • Claims and labs data
  • Electronic health record (EHR) data
  • Wearable data
  • Social media data

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