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Record W3208936513 · doi:10.1093/pch/pxab061.103

128 Evaluation of a Secure Messaging System for Children with Medical Complexity

2021· article· en· W3208936513 on OpenAlexaff
Camilla Parpia, Susan Miranda, Madison Beatty, Clara Moore, Sherri Adams, Jennifer Stinson, Arti D. Desai, Leah Bartlett, Erin Culbert, Julia Orkin, Eyal Cohen

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsCredit Valley HospitalHospital for Sick ChildrenSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsDocumentationPhoneThematic analysisComputer scienceDescriptive statisticsHealth careWorld Wide WebMedical recordInternet privacyMedicineQualitative research

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Complex Care Background The Connecting2gether (C2) platform is a secure online information-sharing tool that aims to improve care for Children with Medical Complexity (CMC) and their families. A key feature of C2 is secure messaging that enables parents to communicate with their child’s healthcare providers (HCPs) in an easy and timely manner. Objectives The objectives of this project are to (1) describe the usage of the secure messaging system; and (2) conduct a thematic comparative evaluation of the secure messaging tool, and email and phone calls. Design/Methods This study is a sub-component of a larger project investigating the overall feasibility and acceptability of the C2 platform. Parents of CMC were recruited from a tertiary level Complex Care program to use the C2 platform for a period of 6 months. Messaging data was extracted from C2 usage reports, and phone and email documentation was extracted from the patient’s electronic medical record. Codes were developed iteratively through comprehensive review of the C2 messages. Message, phone, and email data were then coded by two investigators using thematic analysis. Quantitative data from C2 usage reports were analyzed using descriptive statistics. Results Thirty-four parents and 90 care team members, including HCPs, family, and patient information coordinators were registered on the platform. 4027 messages were exchanged on C2. On average, parents sent 33.4 messages and received 66.4 messages on C2. Of all messages on C2, 32.6% were related to comments, questions, and concerns about the platform itself and its features. Figure 1 demonstrates the thematic content of messages related to care, and highlights the differences in messaging content between the 3 forms of communication. Email and phone content focused primarily on clinical care whereas C2 messaging content also emphasized other aspects of care including education, provision of resources, and personal support. Conclusion This study demonstrates the role that a secure messaging system can have for parents of CMC in being active members of their child’s care. Phone and email were mostly used to discuss medications or clinical issues, whereas C2 enabled the discussion of the patient as a whole. The use of secure messaging can therefore complement other forms of communication between providers and families, instead of replacing them. Further research is needed to understand clinical outcomes associated with the use of secure messaging in order to understand its role in improving patient care and overall caregiver and provider experience.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.068
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.082
GPT teacher head0.405
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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