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Record W4307055232 · doi:10.1093/pch/pxac100.032

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

2022· article· en· W4307055232 on OpenAlexaff
Camilla Parpia, Clara Moore, Madison Beatty, Susan Miranda, Sherri Adams, Jennifer Stinson, Arti D. Desai, Leah Bartlett, Erin Culbert, Eyal Cohen, Julia Orkin

Bibliographic record

VenuePaediatrics & Child Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsSickKids FoundationCredit Valley HospitalHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsDocumentationPhoneThematic analysisDescriptive statisticsText messagingInformation sharingWorld Wide WebComputer scienceInternet privacyMedicineNursingQualitative research

Abstract

fetched live from OpenAlex

Abstract 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 which enables parents to communicate with their child’s care team members (CTMs) in a timely manner. Objectives (1) Evaluate the use of a secure messaging system, (2) Examine and compare the content of messages to email and phone calls, and (3) Explore parent and CTMs’ perceptions and experience using secure messaging as a method of communication. Design/Methods This study is a sub-study of a larger feasibility evaluation of the C2 platform. Parents of CMC were recruited from a tertiary level complex care program to use the C2 platform for 6 months. Parents could invite CTMs involved in their child’s care to register on the platform. Secure messages were extracted from C2 usage reports, and phone and email documentation from the electronic medical record. Quantitative data from C2 usage reports were analyzed using descriptive statistics. Messaging content codes were iteratively developed through review of the C2 messages. Semi-structured interviews were completed with parents and CTMs. Communication and interview data were analyzed using thematic analysis. Results 36 parents and 43 care team members, including HCPs and family members, registered on the C2 platform. Participants sent a total of 1853 messages on C2 with parents and nurse practitioners sending a mean of 33.1 and 87.4 messages, respectively. 85.5% of all C2 messages were responded to within 24 hours. Email and phone calls focused primarily on clinical concerns and medications, whereas C2 messaging focused more on education, proactive check-ins, and non-medical aspects of the child’s life (Figure 1). Four themes emerged from the participant interviews related to C2 messaging: Connection to Care Team, Efficient Communication, Clinical Uses of Secure Messaging, and Barriers to Use (Figure 2). Conclusion Overall, our study provides valuable insight into the benefits of secure messaging in the care of CMC. Secure messaging provided the opportunity for continued patient education, proactive check-ins from HCPs, and casual conversations about family and child life, which contributed to parents feeling an improved sense of connection with their child’s health care team. Secure messaging can be a beneficial additional communication method to improve communication between parents and their care team, reduce the associated burden of care coordination, and ultimately, improve the experience of care delivery.

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)0.014
metaresearch head score (Gemma)0.052
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 score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.052
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.068
GPT teacher head0.398
Teacher spread0.330 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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