81 Family Perceptions of TRaC-K (Telehealth Rounding and Consultation for Kids) a Novel Inpatient Tertiary Regional Virtual Health Collaborative
Bibliographic record
Abstract
Abstract Background Telehealth Rounding and Consultation for Kids (TRaC-K) is an innovative virtual tertiary-regional collaborative care service for regional pediatric inpatients launched in Southern Alberta in August 2020. TRaC-K uses a mobile audiovisual platform to connect regional and tertiary pediatricians and multidisciplinary clinicians caring for admitted children from Southeastern Alberta. The mobile cart also enables children and families to participate in TRaC-K sessions at the bedside. The TRaC-K model is being evaluated during a 1 year pilot between the Alberta Children’s Hospital (ACH) and the Medicine Hat Regional Hospital (MHRH). Objectives As part of the evaluation of the TRaC-K model, we aimed to explore family perceptions of their experience participating in one or more TRaC-K sessions. Design/Methods Family perceptions of receiving care using the TRaC-K model were explored using qualitative analysis of family interviews. Semi-structured interviews were conducted with consenting families who had participated in one or more TRaC-K sessions while their child was admitted at ACH or MHRH. Interviews were conducted via ZOOM or telephone by a research coordinator experienced in qualitative interviews. A short questionnaire of participant information was completed. A series of questions were asked in addition to clarifying questions. Interviews were recorded, transcribed and the NVivo 12 Pro qualitative data analysis software was used for coding. Inductive thematic analysis was completed by two research team members and three transcriptions were coded by both and compared to ensure alignment in coding methodology. There were 15 transcriptions in total. Themes and subthemes were shared with the research team to validate the assignment of quotes to themes and further organize the themes and subthemes. Results Of the 85 TRaC-K sessions during the one year pilot, 36 sessions included at least one family member participant. Of the family members participating in a TRaC-K session, 15 families completed an interview with contributions from one or more parents/guardians. Thematic analysis identified five themes and several subthemes. Themes included: 1. family centered care, 2. access to care closer to home with a subtheme of ease of transition, 3. enhances quality of care with a subtheme of assessment, 4. communication tool with subthemes of real time, technology, facilitates collaboration and shared decision making, and 5. increases family confidence. Conclusion TRaC-K, a tertiary-regional inpatient virtual health model, was perceived by families to be beneficial to their child’s care and their own experience with inpatient care. Families were able to identify many facets of their experience with this novel model of care. To enhance family centered care for families from outside large urban centers whose children require inpatient admission, virtual health models like TRaC-K that enable tertiary-regional clinician collaboration and family participation should be spread to other pediatric inpatient populations.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".