Pilot-testing a pediatric complex care coordination service
Bibliographic record
Abstract
This case, based on data collected in a longitudinal field study, presents Dr. Nathalie Major-Cook, a Children's Hospital of Eastern Ontario (CHEO) pediatrician, who in January 2012 was considering what to do about a 2-year grant-funded pilot project, which had provided an innovative patient care coordination service to 23 families of children described as technology-dependent, medically complex and fragile. Convinced that the Complex Care Coordination service is worthwhile, Dr. Major-Cook wants to move it beyond the pilot test phase to a funded, ongoing service. The case situation is a ‘cliff hanger,’ in that in January 2012, Dr. Major-Cook has not yet learned whether a proposal to fund this as an ongoing service will be approved. If it does not receive approval, she will face the unpleasant task of explaining to parents that this valuable service will end in a few short months. If it does receive approval, several decisions need to be made and actions taken in order to scale the service up, so that it can support about 100 families of technology-dependent, medically complex and fragile children in the region. Dr. Major-Cook also wonders if there is anything else she can do to tip the scales in favor of this decision. The case context is unique and captivating; the young patients under Dr. Major-Cook's care suffer from multiple, and sometimes rare life-threatening diseases. The new Complex Care Coordination model, entailing several new roles and a new way to exchange important information among care providers, was designed to improve the quality of healthcare service delivery, increase parental satisfaction and reduce care costs. Although the project plan specified that an electronic health record would be developed to support coordination among care team members, a fully integrated electronic health record had not yet been implemented. Instead, a ‘SPOC’ (Single Point of Care) document was made available to every specialist clinician and social service provider who treated the child. The case describes the steps leading to approval of the pilot-test project, the project itself, and its preliminary evaluation.
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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 | 0.034 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".