Genetic Insurance Discrimination in Sudden Arrhythmia Death Syndromes
Bibliographic record
Abstract
BACKGROUND: There is virtually no information assessing the insurability of families affected with Sudden Arrhythmia Death Syndromes (SADS) for the determination of the nonclinical implications of genetic screening. It is important to identify the barriers and challenges faced by families as a result of genetic screening for SADS to enable equitable access to insurance coverage. METHODS AND RESULTS: To explore the insurance coverage experiences of SADS-affected families, we administered a cross-sectional online survey across North America from April 28, 2012 to November 13, 2013. Participants included individuals with a SADS diagnosis and their relatives who have applied for insurance (health, life, travel, and disability) or have existing insurance coverage. Of 202 participants, 92% had a SADS diagnosis (92%) as either a proband (50%) or an affected relative (42%); 8% of participants were unaffected family members of a proband; and genetic confirmation was reported by 73%. Of the 54% of SADS respondents who applied for insurance, 60% were rejected by insurers. The preexisting SADS diagnosis was the major reason reported for rejection (57%). Most respondents (80%) had insurance coverage through a spouse/parent plan at the time of diagnosis; 14% experienced a subsequent negative effect on coverage. Thirty-nine percent of affected SADS respondents reported an increase in insurance premium rates. CONCLUSIONS: Increased genetic testing has negatively impacted insurability for SADS patients and affected family members. The challenges in obtaining life and health insurance are mainly because of the preexisting condition, even in the presence of protective laws in the United States.
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".