Associations Between Different Types of Housing Insecurity and Future Emergency Department Use Among a Cohort of Emergency Department Patients
Bibliographic record
Abstract
Housing insecurity can take multiple forms, such as unaffordability, crowding, forced moves, multiple moves, and homelessness. Existing research has linked homelessness to increased emergency department (ED) use, but gaps remain in understanding the relationship between different types of housing insecurity and ED use. In this study, we examined the association between different types of housing insecurity, including detailed measures of homelessness, and future ED use among a cohort of patients initially seen in an urban safety-net hospital ED in the United States between November 2016 and January 2018. We found that homelessness was associated with a higher mean number of ED visits in the year post-baseline. Other measures of housing insecurity (unaffordability, crowding, forced moves, and multiple moves) were not associated with greater ED use in the year post-baseline in multivariable models. We also found that only specific types of homelessness, primarily unsheltered homelessness, were associated with increased ED use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".