The Clinical Definition of Children With Medical Complexity: A Modified Delphi Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Children with medical complexity (CMC) comprise a subgroup of children with severe chronic diseases. A conceptual definition for CMC has been formulated, but there is no agreement on criteria to fulfill each of the 4 proposed domains: diagnostic conditions, functional limitations, health care use, and family-identified needs. Our objective with this study was to identify a standardized definition of CMC. METHODS: Through a scoping review of the CMC literature, we identified potential criteria to fulfill each domain. These were incorporated into an electronic survey that was completed by a geographic and professionally varied panel of 81 American and Canadian respondents with expertise in managing CMC (response rate 70%) as part of a 4-iteration Delphi procedure. Respondents were asked to vote for the inclusion of each criterion in the definition, and for those with quantitative components (eg, hospitalization rates), to generate a consensus threshold value for meeting that criterion. The final criteria were analyzed by a committee and collapsed when situations of redundancy arose. RESULTS: Of 1411 studies considered, 132 informed 55 criteria for the initial survey, which was presented to 81 respondents. Consensus for inclusion was reached on 48 criteria and for exclusion on 1 criterion. The committee collapsed those 48 criteria into 39 final criteria, 1 for diagnostic conditions, 2 for functional limitations, 13 for health care use, and 23 for family needs. CONCLUSIONS: These results represent the first consensus-based, standardized definition of CMC. Standardized identification is needed to advance understanding of their epidemiology and outcomes, as well as to rigorously study treatment strategies and care models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 |
| 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".