Protection of Patient Autonomy via Consumer Protection Litigation: The Israeli Eltroxin Class Action as a Case Study
Bibliographic record
Abstract
Abstract The world famous Eltroxin saga of 2009–2011, which ignited heated public debates in Europe, Canada, and Australia, reveals the problematic nature of standalone autonomy protection cases. Eltroxin is a life‐sustaining thyroid hormone replacement medicine used by millions worldwide; it was reformulated in 2008, and around 10% of patients were badly affected. Poor communication and lack of professional information triggered public hysteria as a global wave of complaints about harmful side effects, including hair loss, weight gain, extreme fatigue, headaches, diarrhoea, and heightened heart rates, flooded the media. Israeli Eltroxin users (around 250 thousand people) were similarly unaware. Following many media reports and ministerial regulations, a high‐profile consumer class action was launched against Perrigo, the distributor. Ten years of court proceedings culminated in a compensation settlement of approximately US$ 14 million. This relatively low sum covered the injuries of those patients who were physically affected; compensation for standalone autonomy injuries to all patients (who were denied information about changes to their life‐sustaining medicine) was refused. The monetary settlement and court decision were hugely disappointing to the class plaintiffs, and a negative signal was sent to the proponents of consumers' and patients' personal autonomy. However, the class action still marked a positive change in pharmaceutical protocols for relations between health authorities, commercial pharmacy entities, and patients/consumers as seen by the proactive communication around a subsequent Eltroxin reformulation in 2020 in Israel, Europe, and South Africa (Aspen Pharmacare, 2020). 1 This paper highlights the vast potential value of consumer class action proceedings, and pharmaceutical consumer (patient) class actions in particular, for public welfare and private autonomy. The paper will explain leading Israeli case law related to consumer autonomy protection in tort law and will argue that this law still holds the unique protection of autonomy as a basic human right and accordingly recognises harm to autonomy as a viable form of damage. Additionally, it illustrates why and how consumer protection class actions are an important tool for protection of human rights in general and of patients' rights in particular.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".