Gesellschaftliche und volkswirtschaftliche Sicht auf die (zukünftige) Finanzierbarkeit von Arzneimitteln

Wasem, Jürgen; Hüer, Theresa; Abels, Carina

doi:10.1007/978-3-662-63929-0_2

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…Especially because the high-cost groups drive the identified excessive growth in drug spending, which, if continued, would have an even greater impact on future spending than rising life expectancy. These observed over-proportional drug spending growth rates, also identified in other studies [ 55 ], are influenced not only by the upcoming amount of innovations and new therapies but also by the pricing policies of the German SHI. Thus, policymakers should question the current less restrictive requirements for the evaluation and reimbursement of orphan drugs in Germany to ensure the sustainability of the German healthcare system.…”

Section: Discussionsupporting

confidence: 74%

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

2023

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Background Although pharmaceutical expenditures have been rising for decades, the question of their drivers remains unclear, and long-term projections of pharmaceutical spending are still scarce. We use a Markov approach considering different cost-risk groups to show the possible range of future drug spending in Germany and illustrate the influence of various determinants on pharmaceutical expenditure. Methods We compute different medium and long-term projections of pharmaceutical expenditure in Germany up to 2060 and compare extrapolations with constant shares, time-to-death scenarios, and Markov modeling based on transition probabilities. Our modeling is based on data from a large statutory sickness fund covering around four million insureds. We divide the population into six risk groups according to their share of total pharmaceutical expenditures, determine their cost growth rates, survival and transition probabilities, and compute different scenarios related to changes in life expectancy or spending trends in different cost-risk groups. Results If the spending trends in the high-cost groups continue, per-capita expenditure will increase by over 40% until 2040. By 2060, pharmaceutical expenditures could more than double, even if these groups would not benefit from rising life expectancy. By contrast, the isolated effect of demographic change would "only" lead to a long-term increase of around 15%. Conclusion The long-term development of pharmaceutical spending in Germany will depend mainly on future expenditure and life expectancy trends of particularly high-cost patients. Thus, appropriate pricing of new expensive pharmaceuticals is essential for the sustainability of the German healthcare system. Supplementary Information The online version contains supplementary material available at 10.1007/s40273-023-01240-3.

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Section: Discussionsupporting

confidence: 74%

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

2023

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Arzneiverordnungen 2020 im Überblick

Ludwig¹,

Mühlbauer

2021

Arzneiverordnungs-Report 2021

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Dürfen Gentherapien so viel kosten? Ethische Bewertung der hohen Preise und des performanceorientierten Erstattungsmodells

Alex,

König

2023

Gen- Und Zelltherapie 2.023 - Forschung, Klinische Anwendung Und Gesellschaft

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ZusammenfassungIn diesem Kapitel wird untersucht, ob hohe Preise für Gentherapien gerechtfertigt sind und ob die Problematik, die mit hohen Preisen verbunden ist, durch das Erstattungsmodell „pay for performance“ (P4P) behoben werden kann. Dazu wird zunächst beschrieben, wie Preise für neue Arzneimittel, zu denen auch Gentherapien zählen, in Deutschland festgelegt werden (Abschn. 22.2). Danach wird P4P als Beispiel für ein Erstattungsmodell vorgestellt (Abschn. 22.3).

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Gesellschaftliche und volkswirtschaftliche Sicht auf die (zukünftige) Finanzierbarkeit von Arzneimitteln

Cited by 3 publications

References 17 publications

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes

Arzneiverordnungen 2020 im Überblick

Dürfen Gentherapien so viel kosten? Ethische Bewertung der hohen Preise und des performanceorientierten Erstattungsmodells

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