Don’t drop the baton: A multidisciplinary and interprofessional approach to improving transfer of accountability and information transfer (TOAI).
Bibliographic record
Abstract
3 Background: Cancer care involves complex transitions across facilities, services and providers. Optimal TOAI is critical to ensuring safe transitions in care. In 2018, the Princess Margaret (PM) Cancer Centre, Division of Medical Oncology and Hematology (DMOH), Quality Program conducted a multi-incident analysis to identify trends in patient transfer-related events (TRE). Priority areas for quality improvement included (1) use of standardized verbal communication, (2) timeliness of handover and (3) documentation. The PM TOAI Working Group (WG) was established to tailor, standardize, implement and evaluate optimal TOAI practices across PM, with the objective of eliminating TRE by 2024. Methods: The WG was established with multi-disciplinary and inter-professional representation across PM services, and met monthly. A needs assessment and environmental scan were completed. Change initiatives were prioritized, and WG focused on developing standards of work (SOW), educational approaches, and evaluation. This work coincided with University Health Network (UHN)’s adoption of I-PASS as the institution’s preferred handover tool, and I-PASS was embedded in all standards created. Change initiatives were: (1) An inter-/intra-facility TOAI SOW was developed (2) A nursing workflow mandating verbal/written handover with patient re-assessment within 1hr of transfer was created (3) Physician (MD) safety huddles with a focus on TOAI in acute oncology clinics and inpatient wards were established, and (4) Evening/weekend inpatient MD handovers were restructured and standardized. From Oct 2021 to Dec 2023, the TOAI WG completed eight cycles of PDSA change initiatives. Pre- and post-implementation surveys were conducted to identify and address barriers. Audits were used to evaluate consistency & quality of inpatient handover rounds. Results: PM reported a serious safety event rate per 10 000 adjusted patient days (SSER) of 1.24(2016); this has been reduced to 0.29 (2024). From 2013-2018, TRE occurred at PM with intervals ranging from 1 to 38 days. In the latter half of 2018, since establishing the TOAI WG, there was a gap of 123 days before the most recent event occurred. The current days between events is > 800 as of May 2024. Conclusions: Systematic implementation of TOAI initiatives at PM has improved the safety and effectiveness of patient care transitions through the adoption of tailored, standardized communication tools and targeted education, which has facilitated a sustained culture shift toward TOAI. These initiatives have reduced SSEs and fostered better communication and collaboration amongst healthcare providers. The sustained improvements highlight the significance of broad engagement of front-line staff and continuous evaluation in ensuring safe, high quality healthcare practices.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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".