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Updated: Jun 12, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
[Secondary data for budget impact analyses]
J Sindern1, D Schröder-Bernhardi, L Slawik
1Health Economics & Pricing, Janssen-Cilag GmbH, Neuss. jsindern@its.jnj.com <jsindern@its.jnj.com>
Routine healthcare data effectively models budget impact for new treatments like paliperidone ER. This analysis provides evidence-based assumptions for healthcare budget planning and technology assessment.
Area of Science:
- Health Economics
- Pharmacoeconomics
- Data Science in Healthcare
Context:
- Budget impact analyses (BIAs) are crucial for evaluating new health technologies.
- Evidence-based assumptions on patient proportion, treatment mix, and costs are vital for accurate BIAs.
- Routine healthcare data offers a valuable resource for constructing these evidence-based models.
Purpose:
- To demonstrate the utility of secondary routine healthcare data for budget impact analysis.
- To establish evidence-based assumptions for treatment scenarios in pharmacoeconomic evaluations.
- To assess the budget impact of atypical antipsychotics, specifically paliperidone ER.
Summary:
- Utilized the IMS Disease Analyzer database, containing electronic health records from German physicians.
- Identified schizophrenia patient subgroups and analyzed antipsychotic therapy composition and costs.
- Calculated total antipsychotic therapy costs (2.7 million Euro in 2008) using prescription and pricing data.
Impact:
- Showcased the suitability of IMS Disease Analyzer data for creating robust, evidence-based budget impact models.
- Provides a methodological example for future pharmacoeconomic studies and healthcare policy decisions.
- Supports informed decision-making regarding the adoption and reimbursement of new pharmaceutical interventions.
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