Outcomes of Virtual Versus Physical Psychiatric Admissions: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Telepsychiatry is an effective alternative to in-person care in many settings. However, evidence is lacking on clinical outcomes when telepsychiatry is used to deliver virtual inpatient psychiatric care. This study compared clinical outcomes of patients virtually admitted with outcomes of those physically admitted to a psychiatric hospital in Ireland during the COVID-19 pandemic. Factors associated with transfer from virtual to physical admission were also investigated. METHODS: Data for this retrospective cohort study (N=1,579 patients) were extracted from electronic health records. Admissions were coded as physical or virtual. Outcome measures were treatment response, length of stay, and time to readmission or death within 6 months of discharge. Inverse probability of treatment weighting was used to control for confounding. Outcomes were analyzed by using logistic and Cox regressions. RESULTS: In 2021, a total of 214 patients were virtually admitted and 1,365 were physically admitted. The virtual admission group had significantly lower odds of treatment response (OR=0.58, 95% CI=0.41-0.81), longer lengths of stay (hazard ratio [HR]=0.83, 95% CI=0.71-0.97), and faster times to readmission or death (HR=2.11, 95% CI=1.52-2.93). Lower socioeconomic status, personality disorder or personality difficulties, history of suicide attempt or deliberate self-harm, and lack of insight into need for treatment were associated with a greater likelihood of transfer from virtual to physical admission. CONCLUSIONS: Patients virtually admitted during the COVID-19 pandemic had worse outcomes than patients who were physically admitted. Postpandemic research should further evaluate the effectiveness of virtual psychiatric wards and identify patient characteristics associated with outcomes of such novel services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".