Children With Medical Complexity in the Canadian Maritimes: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Ongoing developments in the medical field have improved survival rates and long-term management of children with complex chronic health conditions. While the number of children with medical complexity is small, they use a significant amount of health resources across various health settings and sectors. Research to date exploring this pediatric population has relied primarily on quantitative or qualitative data alone, leaving significant gaps in our understanding of this population. OBJECTIVE: The objective of this research is to use health administrative and family-reported data to gain an in-depth understanding of patterns of health resource use and health care needs of children with medical complexity and their families in the Canadian Maritimes. METHODS: An explanatory sequential mixed methods design will be used to achieve our research objective. Phase 1 of this research will leverage the use of health administrative data to examine the prevalence and health service use of children with medical complexity. Phase 2 will use case study methods to collect multiple sources of family-reported data to generate a greater understanding of their experiences, health resource use, and health care needs. Two cases will be developed in each of the 3 provinces. Cases will be developed through semistructured interviews with families and their health care providers and health resource journaling. Findings will be triangulated from phase 1 and 2 using a joint display table to visually depict the convergence and divergence between the quantitative and qualitative findings. This triangulation will result in a comprehensive and in-depth understanding into the population of children with medical complexity. RESULTS: This study will be completed in May 2022. Findings from each phase of the research and integration of the two will be reported in full in 2022. CONCLUSIONS: There is a current disconnect between the Canadian health care system and the needs of children with medical complexity and their families. By combining health administrative and family-reported data, this study will unveil critical information about children with medical complexity and their families to more efficiently and effectively meet their health care needs. Results from this research will be the first step in designing patient-oriented health policies and programs to improve the health care experiences, health system use, and health outcomes of children with medical complexity and their families. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33426.
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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 | 0.089 | 0.064 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.090 | 0.012 |
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".