5 Close to Home: Implementation of a transfer process for paediatric inpatients from tertiary to community care
Bibliographic record
Abstract
Abstract Background Patients presenting to the emergency department who require inpatient care are either admitted to our tertiary care inpatient units or transferred directly to a community hospital. When patients appropriate for community care cannot be transferred due to a lack of community beds and instead remain in a tertiary care bed, there are palpable downstream effects on patient flow. A pre-study audit confirmed that, once admitted, transfers from the inpatient unit to a community bed are rare. This project aimed to improve access to tertiary care beds by increasing inpatient transfers to community hospitals. Objectives The project aimed to transfer 25% of all eligible patients from the Paediatric Medicine inpatient units to community hospitals over a 4-month period by identifying eligible patients and streamlining the transfer process. Design/Methods An Ishikawa diagram with input from inpatient physicians and nurses and community hospital colleagues identified 4 modifiable barriers. A process map was created along with a simplified transfer process. Medical teams and nurse leaders were provided with the charts of contact numbers, geographic locations and levels of care for community hospitals. Intake nurses tracked eligible patients. Encrypted text messages were sent to inpatient physicians on their mobile devices every morning reminding them to assess specific patients for transfer. The outcomes of all identified patients including process and balancing measures were tracked. Results Multiple PDSA cycles focused on improving the success of identifying eligible patients at multiple points in the process. The study’s outcome measure was the rate of successful inpatient transfers for all eligible patients. From November 2018 to March 2019, 120 patients were identified as eligible for transfer at the time of admission: 45 (37.5%) were discharged within 24 hours, 42 (35%) were not considered clinically appropriate for transfer by the attending physician and 33 were considered appropriate for transfer. Twenty-four were approached for transfer (72.7%); 9 were not approached for non-clinical reasons. Six (18.2%) refused transfer and 10 (30%) were successfully transferred. These rates were sustained over the study period. Conclusion A streamlined transfer process can improve patient flow, optimize utilization of tertiary care beds and provide care closer to home. A more robust method of tracking patients that could flag patients and send physicians electronic reminders is needed. Most importantly, optimal use of tertiary care beds requires a culture shift to ensure every patient is considered for transfer to the community when medically appropriate.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".