Platform-Based Patient-Clinician Digital Health Interventions for Care Transitions: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Care transitions are complex and can make patients vulnerable to adverse events. Poor communication among clinicians, patients, and their caregivers is a critical gap during these periods of transition. Technology solutions such as platform-based patient-clinician digital health interventions (DHIs) can provide support and education to patients. OBJECTIVE: The aims of this scoping review were to explore the literature on platform-based patient-clinician DHIs specific to hospital-to-home care transitions and identify the barriers to and enablers of the uptake and implementation of these DHIs. METHODS: A scoping review was conducted. A total of 4 databases (MEDLINE, CINAHL, Embase, and the Cochrane Central Register of Controlled Trials) were searched on July 13, 2022. Studies involving patients aged >18 years who used platform-based DHIs during their hospital-to-home transition were included. In total, 2 reviewers independently screened the articles for eligibility using a 2-stage process of title and abstract and full-text screening. Eligible studies underwent data extraction, and the results were analyzed using descriptive and narrative methods. RESULTS: We screened 8322 articles, of which 97 (1.17%) met our inclusion criteria. DHIs were implemented using a mobile app (59/97, 61%), a web-based platform (28/97, 29%), or a combination of both (10/97, 10%). The 2 most common health conditions related to the DHIs were cardiac disease (22/97, 23%) and stroke (11/97, 11%). Outcomes varied greatly but were grouped by health care use, complications, and wellness outcomes. The top 2 barriers were lack of interest (13/97, 13%) and time constraints to use the DHIs (10/97, 10%), and the top 2 enablers were the ability to use the DHIs (17/97, 18%) and their ease of use (11/97, 11%). The main conflicting theme was access (enabler; 28/97, 29%) or limited access (barrier; 15/97, 15%) to technology or the internet. CONCLUSIONS: Platform-based DHIs could help improve communication, coordination, and information sharing between clinicians and patients during transition periods. Further research is needed to assess the effectiveness of these platform-based DHIs on patient outcomes.
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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 | 0.020 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".