69 Fewer pokes with faster PICCs: A quality improvement initiative to improve timely access to PICCs in paediatric care
Bibliographic record
Abstract
Abstract Background Children requiring long courses of intravenous (IV) therapy often require a peripherally inserted central catheter (PICC). PICCs ensure stable access for IV antibiotics, parenteral nutrition, and other therapies. PICCs also help avoid pain from frequent needle pokes for bloodwork and new IV catheter insertions. Until recently, all PICC insertions at our tertiary hospital were performed by Interventional Radiology (IR) physicians. However, demand for PICCs exceeded IR’s capacity to insert them, leading to delays. In 2022, mean wait time for a PICC insertion was 3.9 days, with only 43% of patients receiving a PICC within 3 days of the request, and 12% of patients who needed a PICC were not able to receive one at all due to delays. Objectives The aim of this quality improvement (QI) initiative was to have >90% of paediatric inpatients who require a PICC receive one within 3 days of the request. Design/Methods The Model for Improvement framework was used. An interdisciplinary QI team started by collecting baseline data. They analyzed the root causes of delayed PICC insertions and identified that scarce IR resources were a primary driver of delays. They conducted a literature review and international environmental scan, created a process map, and engaged with groups across the hospital to identify change ideas. Change ideas were prioritized using an effort-impact matrix. The chosen intervention was to implement a nurse-inserted PICC service to complement existing IR services. Nurses from the Vascular Access Team were specially trained to insert PICCs in children, and the PICC Nurse pilot was launched in June 2023 using Plan-Do-Study-Act (PDSA) methodology to test and adapt changes. Data to track process, balancing, and outcome measures were collected in a REDCap database. Patient, caregiver, and healthcare provider satisfaction data were collected by electronic surveys accessed via a quick response (QR) code. Results In the first 16 months after the launch of the PICC Nurse service, 90 PICCs were inserted by the team. The low numbers in the initial phase (an average of 3.5 PICCs per month) were largely due to conservative eligibility criteria and lack of a formal process for sedation support, resulting in a small number of children being eligible. Ongoing PDSA cycles led to a partnership with Anesthesia for sedation support, and re-evaluation of eligibility criteria with stakeholders. These changes resulted in an increase from an average of 3.5 PICCs per month by the nurse team in the first 6 months, to an average of 7.5 PICCs per month in the most recent 6 months (Figure 1). The mean wait time for PICC insertions by the PICC Nurses was 1.6 days, down from the previous baseline of 3.9 days. 87% of patients who had their PICC inserted by a nurse received their PICC within 3 days. The majority of delays longer than 3 days occurred due to coordination with other procedures under sedation. PICC cancellations also significantly decreased. No adverse events during the PICC insertion procedure were reported. 46 people responded to the satisfaction survey; 16 patients/caregivers and 30 healthcare providers. 98% of respondents reported they were “satisfied” or “extremely satisfied” with the PICC insertion procedure by the PICC Nurse team. Conclusion The nurse-inserted PICC service in paediatrics was feasible, well-accepted, and safe. It enabled patients to more readily access optimum therapies and avoid the pain of repeated pokes. Patients with PICCs may be repatriated to community hospitals to complete treatment, or may be discharged home where outpatient programs exist. By empowering nurses to practice to their full scope, capacity within IR is increased, bottlenecks are reduced, and scarce tertiary care resources can be more appropriately allocated.
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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 | 0.032 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".