Medicaid spending burden among beneficiaries with treatment-resistant depression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: To evaluate Medicaid spending and healthcare resource utilization (HRU) in treatment-resistant depression (TRD). MATERIALS & METHODS: TRD beneficiaries were identified from Medicaid claims databases (January 2010-March 2017) and matched 1:1 with major depressive disorder (MDD) beneficiaries without TRD (non-TRD-MDD) and randomly selected patients without MDD (non-MDD). Differences in HRU and per-patient-per-year costs were reported in incidence rate ratios (IRRs) and cost differences (CDs), respectively. RESULTS: TRD beneficiaries had higher HRU than 1:1 matched non-TRD-MDD (e.g., inpatient visits: IRR = 1.41) and non-MDD beneficiaries (N = 14,710 per cohort; e.g., inpatient visits: IRR = 3.42, p < 0.01). TRD beneficiaries incurred greater costs versus non-TRD-MDD (CD = US$4382) and non-MDD beneficiaries (CD = US$8294; p < 0.05). CONCLUSION: TRD is associated with higher HRU and costs versus non-TRD-MDD and non-MDD. TRD poses a significant burden to Medicaid.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it