Detection of Diabetes and Hypertension Comorbidities Among Adult Psychiatric Inpatients
Bibliographic record
Abstract
INTRODUCTION: This study examined adult psychiatric inpatients diagnosed with diabetes or hypertension before admission who then had these diagnoses missing from discharge records. METHODS: We analyzed Medicaid records for adults admitted to inpatient psychiatry in New York State hospitals between 2012 and 2013. We included 6,381 patients with records indicating preexisting diabetes or hypertension in the 12 months before admission. Logistic regression analyses identified factors at the patient, hospital, and system levels related to detection or omission of the diagnosis of diabetes or hypertension upon hospital discharge. RESULTS: Preexisting diabetes or hypertension was missed in 29% and 36% among inpatients, respectively. Diagnoses were more frequently missed in people who were younger, experiencing homelessness, with fewer claims and with claims longer than 30 days before admission. CONCLUSIONS: These findings underscore the importance of comprehensive admission processes in inpatient psychiatric settings to ensure appropriate detection and treatment of medical comorbidities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".