How digital health solutions align with the roles and functions that support hospital to home transitions for older adults: a rapid review study protocol
Bibliographic record
Abstract
INTRODUCTION: Older adults may experience challenges during the hospital to home transitions that could be mitigated by digital health solutions. However, to promote adoption in practice and realise benefits, there is a need to specify how digital health solutions contribute to hospital to home transitions, particularly pertinent in this era of social distancing. This rapid review will: (1) elucidate the various roles and functions that have been developed to support hospital to home transitions of care, (2) identify existing digital health solutions that support hospital to home transitions of care, (3) identify gaps and new opportunities where digital health solutions can support these roles and functions and (4) create recommendations that will inform the design and structure of future digital health interventions that support hospital to home transitions for older adults (eg, the pre-trial results of the Digital Bridge intervention; ClinicalTrials.gov Identifier: NCT04287192). METHODS AND ANALYSIS: A two-phase rapid review will be conducted to meet identified aims. In phase 1, a selective literature review will be used to generate a conceptual map of the roles and functions of individuals that support hospital to home transitions for older adults. In phase 2, a search on MEDLINE, EMBASE and CINAHL will identify literature on digital health solutions that support hospital to home transitions. The ways in which digital health solutions can support the roles and functions that facilitate these transitions will then be mapped in the analysis and generation of findings. ETHICS AND DISSEMINATION: This protocol is a review of the literature and does not involve human subjects, and therefore, does not require ethics approval. This review will permit the identification of gaps and new opportunities for digital processes and platforms that enable care transitions and can help inform the design and implementation of future digital health interventions. Review findings will be disseminated through publications and presentations to key stakeholders.
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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 | 0.162 | 0.171 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.066 | 0.014 |
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".