SWK-11. ASSESSMENT OF THE INDIRECT COSTS ASSOCIATED WITH PROTON THERAPY TREATMENT FOR ALBERTA PATIENTS REFERRED OUT OF COUNTRY
Bibliographic record
Abstract
Abstract BACKGROUND Proton therapy for benign and malignant tumors has dosimetric and clinical advantages over photon therapy. Patients in Alberta, Canada are referred to the United States for proton treatment. The Alberta Heath Care Insurance Plan (AHCIP) pays for the proton treatment and the cost of flights to and from the United States (direct costs). This study aimed to determine the out-of-pocket expenses incurred by patients or their families (indirect costs). METHODS Invitation letters linked to an electronic survey were mailed to patients treated with protons between 2008 and 2018. Expenses for flights for other family members, accommodations, transportation, food, passports, insurance, and opportunity costs including lost wages and productivity were measured. RESULTS Fifty-nine invitation letters were mailed. Seventeen surveys were completed (28.8% response rate). One paper survey was mailed at participant request. Nine respondents were from parent/guardian, 8 from patients. All patients were accompanied to the US by a family member/friend. Considerable variability in costs and reimbursements were reported. Many of the accompanying family/friends had to miss work; only 3 patients themselves reported missed work. Time away from work varied, and varied as to whether it was paid or unpaid time off. CONCLUSIONS Respondents incurred indirect monetary and opportunity costs which were not covered by AHCIP when traveling out of country for proton therapy. Prospective studies could help provide current data minimizing recall bias. These data may be helpful for administrators in assessing the societal cost of out-of-country referral of patients for proton therapy.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".