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Record W4307054517 · doi:10.1093/pch/pxac100.034

35 Co-Creation, Development and Evaluation of Online Care Maps for Children with Medical Complexity

2022· article· en· W4307054517 on OpenAlexaff
Sherri Adams, Blossom Dharmaraj, Madison Beatty, Clara Moore, Arti D. Desai, Leah Bartlett, Erin Culbert, Eyal Cohen, Jennifer Stinson, Julia Orkin

Bibliographic record

VenuePaediatrics & Child Health · 2022
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsSickKids FoundationCredit Valley HospitalHospital for Sick Children
Fundersnot available
KeywordsNonprobability samplingSituatedNursingQualitative researchPsychologyMedical educationMedicineComputer scienceArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

Abstract Background Given the nature of their child’s underlying condition, parents of children with medical complexity (CMC) are relied upon to act as the primary care coordinator for their child. Tools like a care map have been shown to be effective in supporting patients and families, however, the use of an online care map that can be edited in real time has not been used and evaluated. Objectives The aims of this study were to: 1) determine the requirements and design features of a co-created online platform supporting care map creation, 2) use the platform for the development of a shareable standardized parent created care map, and 3) explore the utility and feasibility of an online care map from multiple perspectives including (i) parents, (ii) health care providers (HCPs), and (iii) non-HCPs. Design/Methods This qualitative study utilized interpretive description. Purposive sampling guided participant selection. In phase 1, the requirements and design features for a care map creation tool situated in an online patient and family facing platform were identified through semi-structured interviews with parents and HCPs/non-HCPs of CMC. This data was used to co-create the care map feature. In phase 2, parents used this online platform to create, update, and share care maps. Semi-structured interviews with parents and HCPs/non-HCPs of CMC were conducted to explore care map creation and utility. Results In phase 1, thirty-two interviews with parents (n=16) and HCPs/non-HCPs (n=16) were conducted. Four primary themes related to the requirements and design features for an online care map were identified and included: 1) useful features, 2) suggestions, 3) sharing, and 4) future use, which informed development of the online tool. In phase 2, thirty-six parents were on boarded to the online platform with n=25 (69%) choosing to create a care map. Semi-structured interview data with parents (n=15) and HCPs/non-HCPs (n=13) demonstrated four primary themes to inform the future use of online care maps: 1) clinical usage of care maps, 2) benefits of use, 3) challenges for usage, and 4) suggestions to improve usability. Conclusion Parents have valuable feedback informing the co-creation of an online platform to create and share care maps. Parents reported uncertainty in the clinical usage of care maps, however, HCPs found them very informative. Further research is needed to understand the importance of education and clarity of roles in the use of a care map for clinical care of CMC.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.060
GPT teacher head0.371
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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