Mapping PBS Drug Pathways in Australia: A Framework and Interactive Tool for Category-Specific Pricing Calculations

Author(s)

Parinita Barman, MPH1, Arpita Kundu, MSc1, Amit Gupta, MSc1, Michael Aristides, MSc2, George Papadopoulos, BSc (Hons)2, Hemant Rathi, MSc1.
1Skyward Analytics, Gurugram, India, 2Lucid Health Consulting, Sydney, Australia.
OBJECTIVES: Australia’s Pharmaceutical Benefits Scheme (PBS) comprises of multiple listing categories, each governed by distinct pricing and reimbursement rules. PBS pricing is based on two key components: the Approved Ex-Manufacturer Price (AEMP), the base amount paid to the sponsor, and the Dispensed Price for Maximum Quantity/Amount (DPMQ/DPMA), which includes pharmacy markups, administration, handling and infrastructure (AHI) fees, and dispensing fees Calculating AEMP from DPMQ/DPMA, or vice versa, requires pathway-specific considerations. This study aimed to develop a framework mapping PBS listing pathways and create an interactive dashboard to automate forward and reverse price calculations based on category-specific PBS rules.

METHODS: PBS policy documents and pricing guidelines were reviewed to identify how price components vary across listing categories. A structure framework was developed to classify drugs by PBS listing pathways, broadly classified as Section 85 and Section 100, which is further categorized into Efficient Funding of Chemotherapy (EFC), non-EFC, Highly Specialized Drugs (HSD), HSD Community Access, botulinum, growth hormone, in vitro fertilization, and opiate dependence treatment programs. This framework was integrated into an interactive dashboard, automating bidirectional AEMP and DPMQ/DPMA calculations, adjusting for categories-specific AHI fees, markups, and pricing rules.
RESULTS: The framework revealed clear structural and pricing differences across PBS pathways. Section 85 used standard community pharmacy pricing, while Section 100 categories included hospital-specific AHI fees. The calculator accurately translated prices across categories, allowing users to input either AEMP or DPMQ/DPMA and compute the corresponding value. Validation was conducted using over 50 PBS listings and calculations were compared to PBS data, demonstrating a consistent error rate of <1%. The tool enables real-time simulations to assess how changes in markups, fees, or category may affect drug pricing.
CONCLUSIONS: The dashboard offers a user-friendly, category-specific approach to navigating complex PBS pricing, thereby supporting sponsors, consultants, and policymakers in preparing HTA submissions and informing reimbursement strategies.

Conference/Value in Health Info

2025-11, ISPOR Europe 2025, Glasgow, Scotland

Value in Health, Volume 28, Issue S2

Code

HPR137

Topic

Economic Evaluation, Health Policy & Regulatory, Health Technology Assessment

Topic Subcategory

Pricing Policy & Schemes, Reimbursement & Access Policy

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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