Complex Care Needs a Team Approach: How Implementation of a Nurse Key‐Worker Can Improve Care for Children With Medical Complexity and Their Families
Bibliographic record
Abstract
BACKGROUND: Children with medical complexity (CMC) have complex, chronic conditions and require specialized care and extensive support across multiple sectors. Children's Healthcare Canada guidelines highlight the importance of care coordination for this population. The BC Children's Hospital Complex Care programme introduced a Nurse Key Worker (NKW) to perform care coordination in conjunction with the expertise of physicians and nurse practitioner (NP). OBJECTIVES: To assess the feasibility of the NKW role in coordinating care for families of CMC. To evaluate the activities performed to meet care coordination needs. METHODS: Thirty-one caregivers of CMC (0-19 years old) were invited to work with the NKW. Electronic health records were utilized to determine the number of patient appointments before and after NKW implementation. Caregivers completed the Family Experience with Care Coordination Measure and Patient-Reported Outcomes Measurement Information System Self-Efficacy tools at baseline and 9 months post-implementation. The physician, NP and NKW completed the Care Coordination Measurement Tool for a duration of 2 weeks to assess and quantify care coordination needs. RESULTS: There was an average of 45% increase in the number of patient appointments after NKW implementation. Caregivers of CMC recognized their NKW as a reliable, skilled, single point of contact. More caregivers reported feeling "very confident" in their ability to care for their CMC. The NKW addressed 168 care coordination needs and performed 576 activities, whereas the NP and physician addressed 115 care coordination needs and performed 282 activities. The care coordination activities prevented unnecessary emergency and clinic visits and reduced family stress and burden. CONCLUSION: The NKW effectively addressed the care coordination needs of CMC and their families without requiring additional physician or NP resources. The NKW, NP and physician performed different activities to meet care coordination needs.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".