Modeling Health and Economic Outcomes of Providing Stable Housing to Homeless Adults With OUD
Bibliographic record
Abstract
Importance: The number of people experiencing homelessness (PEH) in the US has increased substantially in recent years. The leading cause of death among PEH is drug overdose, with opioids accounting for the majority of such deaths. Objective: To assess the costs and health outcomes of providing stable housing to PEH who have opioid use disorder (OUD). Design, Setting, and Participants: This economic evaluation conducted a model-based cost-effectiveness analysis of PEH with OUD in the US. Exposure: Provision of stable housing, with no requirement to enter OUD treatment. Main Outcomes and Measures: Primary outcomes were overdoses and deaths over 5 years, lifetime per-person discounted quality-adjusted life-years (QALYs) and costs, and incremental cost-effectiveness ratios (ICERs) compared with the status quo (no housing provision). Results: In a model of 1000 PEH (700 male; mean [SD] age, 46.4 [14.0]; 300 female; mean [SD] age, 46.5 [14.3]), under the status quo, 191 (95% CI, 152-237) deaths occurred over 5 years (58 [95% CI, 44-78] from overdose and 133 [95% CI, 101-167] from other causes). With the housing intervention, 140 (95% CI, 114-185) deaths occurred (53 [95% CI, 39-76] from overdose and 87 [95% CI, 73-110] from other causes). The housing intervention was associated with a gain of 3.59 (95% CI, 3.13-3.98) lifetime QALYs per person at an incremental cost of $26 800 (95% CI, $21 200-$32 300) per QALY gained compared with the status quo. Over extensive sensitivity analyses, the ICER remained less than $90 000 per QALY gained. Conclusions and Relevance: This economic evaluation found that investing in stable housing for this marginalized population, even with no requirement to enter OUD treatment, was associated with cost-effectiveness, fewer deaths, and improved health outcomes. Efforts are urgently needed to improve the health of PEH with OUD; it is essential to understand the outcomes and cost-effectiveness of housing provision for this marginalized population because housing status is a key social determinant of health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".