Collaborative Approach to Developing Infection Prevention Control Recommendations at a Tertiary-Care Pediatric Hospital
Bibliographic record
Abstract
Background: Stollery Children’s Hospital (SCH) is a tertiary-care pediatric hospital with a complex infrastructure: 3 NICUs located at 3 different hospitals, and all of the pediatric inpatient beds, PICU, PCICU, and a medical-surgical NICU at the main SCH site shared buildings with an academic adult hospital. We describe a collaborative process used to develop standardized SCH Infection Prevention and Control (IPC) recommendations. Methods: The SCH IPC formed a working group with Patient and Family-Centered Care (PFCC) and family representatives in 2014 to enhance the engagement of families in regards to IPC issues and initiatives. The working group identified inconsistent messages provided to families when a child was admitted as a patient requiring additional precautions (PRAP). The working group then developed a framework of key questions to be answered for family care providers of PRAP. The working group held several consultative meetings with frontline staff followed by a review of published guidelines and consultations with other pediatric hospitals about contentious issues. A consensus meeting with all key stakeholders was held to finalize IPC recommendations. Results: The key contentious issues included (1) whether personal protective equipment is required for family care providers who stay overnight with PRAP and (2) whether family care providers of PRAP are allowed to access nutrition centers on clinical units and family lounges in PCICU–PICU–NICU that were stocked with free hot meals for the families. No directly applicable recommendation was available IPC guidelines on these issues. Discussions of these topics were directed by PFCC at family councils of various clinical programs with efforts to seek opinions from more family representatives. Expert opinions and current practice were also obtained from Canadian hospitals through emails and from US hospitals through SHEA Open Forum by ICP. A final consensus meeting revisiting all available information was held, and a new Stollery IPC guideline was created with families as partners sharing the IPC vision of minimizing transmission risk at SCH. Conclusions: A consultative engagement and consensus process was successful in the development of IPC recommendations for family care providers for PRAP for implementation at a tertiary-care pediatric hospital with a complex infrastructure. The next step is to develop family-friendly educational and resource materials with clear and concise messages. Funding: None Disclosures: None
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".