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Injury Patterns and Hospital Admission After Trauma Among People Experiencing Homelessness

2023· article· en· W4382502155 on OpenAlexaboutno aff
Casey M. Silver, Arielle Thomas, Susheel Reddy, Gwyneth A. Sullivan, Rebecca E. Plevin, Hemal K. Kanzaria, Anne M. Stey

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersNational Cancer InstituteNational Heart, Lung, and Blood Institute
KeywordsMedicineMedicaidRetrospective cohort studyResidenceEmergency medicineObservational studyInjury Severity ScoreCohortEmergency departmentOdds ratioInjury preventionPoison controlDemographyPediatricsInternal medicinePsychiatryHealth care

Abstract

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Importance: Traumatic injury is a major cause of morbidity for people experiencing homelessness (PEH). However, injury patterns and subsequent hospitalization among PEH have not been studied on a national scale. Objective: To evaluate whether differences in mechanisms of injury exist between PEH and housed trauma patients in North America and whether the lack of housing is associated with increased adjusted odds of hospital admission. Design, Setting, and Participants: This was a retrospective observational cohort study of participants in the 2017 to 2018 American College of Surgeons' Trauma Quality Improvement Program. Hospitals across the US and Canada were queried. Participants were patients aged 18 years or older presenting to an emergency department after injury. Data were analyzed from December 2021 to November 2022. Exposures: PEH were identified using the Trauma Quality Improvement Program's alternate home residence variable. Main Outcomes and Measures: The primary outcome was hospital admission. Subgroup analysis was used to compared PEH with low-income housed patients (defined by Medicaid enrollment). Results: A total of 1 738 992 patients (mean [SD] age, 53.6 [21.2] years; 712 120 [41.0%] female; 97 910 [5.9%] Hispanic, 227 638 [13.7%] non-Hispanic Black, and 1 157 950 [69.6%] non-Hispanic White) presented to 790 hospitals with trauma, including 12 266 PEH (0.7%) and 1 726 726 housed patients (99.3%). Compared with housed patients, PEH were younger (mean [SD] age, 45.2 [13.6] years vs 53.7 [21.3] years), more often male (10 343 patients [84.3%] vs 1 016 310 patients [58.9%]), and had higher rates of behavioral comorbidity (2884 patients [23.5%] vs 191 425 patients [11.1%]). PEH sustained different injury patterns, including higher proportions of injuries due to assault (4417 patients [36.0%] vs 165 666 patients [9.6%]), pedestrian-strike (1891 patients [15.4%] vs 55 533 patients [3.2%]), and head injury (8041 patients [65.6%] vs 851 823 patients [49.3%]), compared with housed patients. On multivariable analysis, PEH experienced increased adjusted odds of hospitalization (adjusted odds ratio [aOR], 1.33; 95% CI, 1.24-1.43) compared with housed patients. The association of lacking housing with hospital admission persisted on subgroup comparison of PEH with low-income housed patients (aOR, 1.10; 95% CI, 1.03-1.19). Conclusions and Relevance: Injured PEH had significantly greater adjusted odds of hospital admission. These findings suggest that tailored programs for PEH are needed to prevent their injury patterns and facilitate safe discharge after injury.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.371
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2023
Admission routes1
Has abstractyes

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