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Record W4292648763 · doi:10.2196/41310

Digital Communication Between Patients and Health Care Professionals Across Disciplines and Sectors After Hospital Discharge: Facilitators, Barriers, and Effects

2022· article· en· W4292648763 on OpenAlexvenueno aff
Lili Worre Høpfner Jensen, Birthe Dinesen, Søren Kold, Ole Rahbek

Bibliographic record

VenueIproceedings · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsHealth professionalsHospital dischargeHealth careNursingDischarge planningMedicinePsychologyBusinessIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

Background Over the past decade, hospital admissions for patients undergoing orthopedic surgery have been shortened, and the time for informing and educating patients prior to discharge has been compromised. The transition of care from hospital to home poses a substantial risk of adverse events. Patients have difficulty remembering information and struggle to assess the severity of symptoms after discharge, leading to unplanned telephone contacts and clinic visits. These inquiries are frequent and pose a substantial burden on the health care system and patients. The COVID-19 pandemic showed an emerging need to implement new communication technologies. Asynchronous digital communication (DC) may provide easy access to health care and seamless communication across sectors. Objective This study aimed to investigate how DC can facilitate easy communication between patients and health care professionals (HCPs) across sectors and the effects of DC on patient-initiated telephone contacts after discharge. Methods The overall theoretical approach was inspired by Continuity of Care and the Consolidated Framework for Implementation Research. Substudy I was a scoping review on DC between patients and HCPs after hospital discharge. Substudy II explored DC in an orthopedic surgery setting and through a triangulation of qualitative data collection techniques. Substudy III investigated the effect of DC on patient-initiated telephone contacts after discharge. Results Preliminary findings from substudy I show that DC is increasingly used to support patient-provider communication after discharge. In substudy II, preliminary findings show that DC is feasible in a real-life setting, providing patients with easy access to HCPs, who accept and adapt DC to existing cross-sectoral workflows. However, barriers exist related to the technological integration between systems and individuals’ hesitation to use DC. In substudy III, DC is to be tested in a randomized controlled trial. Conclusions This study generates new knowledge of asynchronous DC that may guide future implementations across the health care system.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.001
Open science0.0000.003
Research integrity0.0000.001
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 head0.037
GPT teacher head0.383
Teacher spread0.346 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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