Estimating the trends in attempted suicide using administrative data and patient chart review: a pilot study
Bibliographic record
Abstract
Suicide is a major public health problem and attempted suicide is a known risk factor of suicide death.There is an accepted figure that between 10 to 20 attempts occur for every death by suicide.However, reliable data on attempted suicide seeking medical assistance are scarce and unrepresentative notwithstanding advances in medical charting.Many have tried to contravene this by novel ways of taking the census of attempted suicide with interesting results but few were applicable to very large population.Our study goals are firstly to estimate the level of underestimation of attempted suicide treated in hospital settings; secondly to find, by the adjunction of the Canadian Emergency Department Triage and Acuity Scale (CTAS) used by nurses in emergency triage, to usually used administrative databases a new affordable and dependable way to identify more accurately the number of attempted suicide treated in hospitals.Thirdly, this study seeks to prove that lethality is the main indicator of attempted suicide coding without regards to intention.This study used administrative data that covered physical and psychological diagnosis that could have been or induced by a suicide attempt.The second step added nursing triage notes that suggested that the main complaint of the patient was related to suicidal behavior.Then, attention was brought to cases bearing exclusive suicide attempt diagnosis and if their first unit of hospitalization was intensive care unit to verify if lethality was meaningful in the recording of their diagnosis.This study found that 95% of the attempted suicides seeking medical assistance were not coded as such and their physical or psychological diagnosis was the main diagnosis appearing in the administrative database.CTAS was efficient in locating attempts of low to moderate lethality in emergency department but was not efficient for high lethality case as these would bypass nursing triage and receive immediate medical care.For monitoring purpose, usual administrative databases and CTAS should be associated with another means that could identify suicide attempts with high lethality to give a more realistic estimate of this phenomenon.This study also found that lethality is a major factor in the labelling of attempted suicide but there seems to be other elements interfering other then intentions as only a quarter of very lethal cases were coded as attempted suicides.I would like to thank Dr Gustavo Turecki and Dr Elham Rahme for giving me the instrumental support to pursue my studies.It was appreciated.I also
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".