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Healthcare Funding Decisions and Real-World Benefits: Reducing Bias by Matching Untreated Patients

Author

Listed:
  • Peter Ghijben

    (Monash University)

  • Dennis Petrie

    (Monash University)

  • Silva Zavarsek

    (Deakin University)

  • Gang Chen

    (Monash University)

  • Emily Lancsar

    (The Australian National University)

Abstract

Governments and health insurers often make funding decisions based on health gains from randomised controlled trials. These decisions are inherently uncertain because health gains in trials may not translate to practice owing to differences in the population, treatment use and setting. Post-market analysis of real-world data can provide additional evidence but estimates from standard matching methods may be biased when unobserved characteristics explain whether a patient is treated and their outcomes. We propose a new untreated matching approach that can reduce this bias. Our approach utilises the outcomes of contemporaneous untreated patients to improve the matching of treated and historical control patients. We assess the performance of this new approach compared to standard matching using a simulation study and demonstrate the steps required using a funding decision for prostate cancer treatments in Australia. Our simulation study shows that our new matching approach eliminates nearly all bias when unobserved treatment selection is related to outcomes, and outperforms standard matching in most scenarios. In our empirical example, standard matching overestimated survival by 15% (95% confidence interval 2–34) compared to our untreated matching approach. The health gains estimated using our approach were slightly lower than expected based on the trial evidence, but we also found evidence that in practice prescribers ceased prior therapies earlier, treated a more vulnerable population and continued treatment for longer. Our untreated matching approach offers researchers a new tool for reducing uncertainty in healthcare funding decisions using real-world data.

Suggested Citation

  • Peter Ghijben & Dennis Petrie & Silva Zavarsek & Gang Chen & Emily Lancsar, 2021. "Healthcare Funding Decisions and Real-World Benefits: Reducing Bias by Matching Untreated Patients," PharmacoEconomics, Springer, vol. 39(7), pages 741-756, July.
  • Handle: RePEc:spr:pharme:v:39:y:2021:i:7:d:10.1007_s40273-021-01020-x
    DOI: 10.1007/s40273-021-01020-x
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    References listed on IDEAS

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    1. Bonny Parkinson & Catherine Sermet & Fiona Clement & Steffan Crausaz & Brian Godman & Sarah Garner & Moni Choudhury & Sallie-Anne Pearson & Rosalie Viney & Ruth Lopert & Adam Elshaug, 2015. "Disinvestment and Value-Based Purchasing Strategies for Pharmaceuticals: An International Review," PharmacoEconomics, Springer, vol. 33(9), pages 905-924, September.
    2. Bonny Parkinson & Rosalie Viney & Marion Haas & Stephen Goodall & Preeyaporn Srasuebkul & Sallie-Anne Pearson, 2016. "Real-World Evidence: A Comparison of the Australian Herceptin Program and Clinical Trials of Trastuzumab for HER2-Positive Metastatic Breast Cancer," PharmacoEconomics, Springer, vol. 34(10), pages 1039-1050, October.
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