16 Assessing the requirements for a patient-facing virtual platform to enhance care coordination for children with medical complexity
Bibliographic record
Abstract
Children with medical complexity (CMC) require specialized care from multiple health care providers across various settings; hospital, home and community. Communication and care coordination are essential to provide streamlined, accessible care. Currently a child’s executive medical summary, known as a care plan, is thought to be the gold standard in assisting with care coordination. However, there are many limitations regarding care plan use such as: lack of shared ownership, limited capability to update in real-time, and lack of universal access. Previous literature indicates that care plans should be cloud-based and comprehensive, allowing for more functions other than the executive medical summary alone. To determine the requirements and design features that are needed (e.g. care plans and care maps) in a cloud-based care coordination platform in order to best serve parents and health care providers (HCP) of CMC. 10 parents of CMC and 10 HCPs participated in phase one of a feasibility study aiming to design, test and implement a patient-facing care coordination platform. Participants were recruited through purposive sampling and provided informed consent. Participants were shown screen-shots of the virtual platform, had the various functionalities explained to them verbally and were interviewed throughout the process about what they were shown and their likes/dislikes using an open ended semi-structured interview guide. The interviews were audio recorded and transcribed verbatim with data analysis occurring simultaneously. Data was coded individually by three members of the research team who then met to review emerging codes and came to consensus on codes and emerging themes. Parents of CMC were enthusiastic about the prospect of having a cloud-based care plan that they would be able to update in real-time. Most HCPs were weary of allowing parents the ability to make changes to the care plans, suggesting various mechanisms that would increase their comfort. Parents and HCPs also provided various suggestions regarding content that should be added to the platform such as: additional care plan sub-headings and symptom trackers. Parents and HCPs provided many ways in which the patient-facing virtual care platform could be improved prior to usability testing. Care plans continue to be viewed as a valuable tool and other novel concepts for care provision emerged.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".