Different Policy Measures and Practices between Swedish Counties Influence Market Dynamics: Part 2—Biosimilar and Originator Etanercept in the Outpatient Setting
Bibliographic record
Abstract
BACKGROUND: Diverging approaches towards market entry and uptake of biosimilars, even within a country, leads to regional variation in biosimilar use. This is the case in Sweden, where the 21 county councils control the healthcare budget and offer regional guidance. OBJECTIVES: This study aimed to analyse the market dynamics of originator and biosimilar etanercept (outpatient setting) in the different counties of Sweden, and examine the influence of local policy measures and practices, in addition to national policy. METHODS: This study was performed in three steps: (1) a structured review of the literature on (biosimilar) policies in Sweden; (2) analysis of market data on the counties' originator and biosimilar etanercept uptake (quarter two 2012 to quarter four 2017) provided by IQVIA™; and (3) discussion of findings in face-to-face semi-structured interviews with the national pricing and reimbursement agency, key experts in the county councils of Skåne, Västra Götaland and Stockholm, and an industry representative. RESULTS: Notwithstanding the existence of a national managed entry agreement for etanercept, wide variations in biosimilar market shares between counties were observed (40-82% in 2017). Over time, early and late adopters of biosimilar etanercept can be distinguished. In quarter four 2017, biosimilar market shares of all counties slightly decreased in accordance with the lower priced originator product from 1 October 2017. As prescriptions for treatment with etanercept are often provided for a year, two approaches are possible to switch patients: active pullback of prescriptions resulting in additional workload, or wait until the patient's next visit. Qualitative analysis indicated that the choice to use the biosimilar or the originator product depends on differences in rebated prices of the biosimilar and originator product, the presence of key opinion leaders, local guidelines, and financial streams and local gainsharing arrangements. Our estimates of current rebated prices and costs after gainsharing for the county councils and Government reveal only limited price differences between products. CONCLUSIONS: Regional variations in use of biosimilar etanercept can be seen although prices are coordinated nationally. This suggests that counties react differently to price differences and highlights the role of local policy and attitudes of stakeholders towards biosimilars and switching. It seems that some counties are hesitant to switch patients, as it is associated with an increased administrative workload that might not be compensated for by savings associated with a lower priced product.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".