Comparison of the out-of-pocket costs of Medicare-funded telepsychiatry and face-to-face consultations: A descriptive study
Bibliographic record
Abstract
OBJECTIVE: Telepsychiatry items in the Australian Medicare Benefits Schedule (MBS) were expanded following the COVID-19 pandemic. However, their out-of-pocket costs have not been examined. We describe and compare patient out-of-pocket payments for face-to-face and telepsychiatry (videoconferencing and telephone) MBS items for outpatient psychiatric services to understand the differential out-of-pocket cost burden for patients across these modalities. METHODS: out-of-pocket cost information was obtained from the Medical Costs Finder website, which extracted data from Services Australia's Medicare claims data in 2021-2022. Cost information for corresponding face-to-face, video, and telephone MBS items for outpatient psychiatric services was compared, including (1) Median specialist fees; (2) Median out-of-pocket payments; (3) Medicare reimbursement amounts; and (4) Proportions of patients subject to out-of-pocket fees. RESULTS: Medicare reimbursements are identical for all comparable face-to-face and telepsychiatry items. Specialist fees for comparable items varied across face-to-face to telehealth options, with resulting differences in out-of-pocket costs. For video items, higher proportions of patients were not bulk-billed, with greater out-of-pocket costs than face-to-face items. However, the opposite was true for telephone items compared with face-to-face items. CONCLUSIONS: Initial cost analyses of MBS telepsychiatry items indicate that telephone consultations incur the lowest out-of-pocket costs, followed by face-to-face and video consultations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".