Dublin's homeless crisis – is this reflected in emergency department psychiatry referrals?
Bibliographic record
Abstract
Aims This study seeks to explore the prevalence and impact of homelessness in an adult sample of psychiatry referrals over a one-month period via the Emergency Department at St. James's Hospital. Background Homelessness has now reached a crisis point in Ireland. In July 2019, there were 10,275 people documented as homeless nationwide, with the number of homeless families increasing by 178% since June 2015. The majority of individuals registered as homeless are located in Dublin. St. James's Hospital (SJH) provides psychiatric care to a population of 136,704 people across Dublin South-City within areas of significant deprivation according to the most recent social deprivation index. Method All Emergency Department psychiatry referrals over a one-month period were recorded. Month of study was randomly generated. Data were collected from electronic records. Socio-demographic information was analysed. Data were anonymised and recorded using Microsoft Excel. Current homelessness statistics were accessed from the Department of Housing, Planning, and Local Government and compared to the data collected. Result During the month of the Study (March 2019), 4315 adults accessed emergency homeless accommodation in Dublin. Of the 109 psychiatry referrals received through the Emergency Department at SJH during this time, over a quarter (28%) of those referred reported themselves to be homeless or living in temporary accommodation. An additional 5% were documented as living in residential or sheltered care at time of assessment. All of the referred homeless patients were unemployed (n = 30). 50% of homeless patients were referred to psychiatry following expressed thoughts or acts of self-harm. Illicit drug abuse was associated with 73% of referrals. Alcohol abuse was associated with 47%. Of those who were referred, under a quarter (23%) were assessed as having a major mental illness, and in the majority of these cases, illicit drug and alcohol abuse were compounding factors in exacerbating symptomatology. Of those referred, 66% had previously been reviewed by psychiatry during prior ED presentations and 60% of homeless presenters reported that they had previously been, or were currently linked in with community mental health teams. Conclusion Frequently, vulnerable patients most in need of social and psychiatric care, such as homeless people with addiction issues, are eclipsed from accessing supports. The high proportion of patients reporting to be homeless is cause for concern and suggests the need for tailored and integrated multi-disciplinary assessments and interventions at an Emergency Department level.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.001 |
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; both teacher heads agree on what is shown here.
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".