DECREASED HOSPITALIZATIONS AT THE COST OF INCREASED EMERGENCY DEPARTMENT RETURNS? OUTCOMES OF A CLINICAL DECISION UNIT
Bibliographic record
Abstract
BACKGROUND: Within emergency departments (EDs), clinical decision units (CDUs) allow for protocol-driven treatment and observation of patients who are not ready for discharge after initial assessment and care. CDUs can serve as an alternative to short stay inpatient admission, optimizing hospital resource utilization. A CDU was established at our institution in October 2014 to reduce hospitalizations. Preliminary administrative data review, however, revealed a return to ED (RTED) rate of 15% following a CDU stay, 2-3 times the RTED rate reported in the literature. Whether this is the expected cost of reducing hospitalizations remains unclear. Research exploring root causes of RTED following a CDU stay is limited. OBJECTIVES: Following a CDU stay, to determine 1) the number of potentially averted hospitalizations, and 2) the proportion of potentially preventable RTED. DESIGN/METHODS: Retrospective cohort study of all ED visits with a CDU stay from Jan 1, 2015 to Dec 31, 2015. Following administrative database review, health records data was extracted and entered into standardized online forms by trained research assistants, then blindly evaluated by two investigators to determine: a) the most probable cause of each RTED; and b) the number of RTED that were clinically unnecessary. RESULTS: 1503 (89%) of the 1696 index CDU visits were discharged home. Of these visits, 653 had a total ED length of stay of 8 hours or greater, thus were considered averted hospitalizations attributable to a CDU stay. However, 139 (9%) of the 1503 visits had ≥1 associated RTED. Among these, 48 (35%) were deemed clinically unnecessary (89% agreement, Kappa = 0.79) and therefore potentially preventable. The most common reason (88%) for unnecessary RTED was mismatch between expected natural progression of disease (not requiring ED reassessment or treatment) and families’ understanding of disease symptom range and duration. In 90% of these cases, anticipatory guidance regarding natural progression of disease was not provided to parents upon discharge. CONCLUSION: The CDU potentially prevented several inpatient admissions, positively impacting patients and the healthcare system. A relatively high RTED rate, however, was observed, with 35% of RTED being deemed clinically unnecessary and 27% lacking adequate discharge instructions. The CDU’s effectiveness may therefore be further optimized through quality improvement initiatives targeting the ED discharge process.
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".