Patient‐mediated interventions in hospital: A systematic review
Bibliographic record
Abstract
AIMS: To describe the characteristics of hospital-based, patient-mediated interventions and their impact on patient, clinician and organization outcomes. DESIGN: Systematic review. DATA SOURCES: Health literature databases (MEDLINE, CINAHL and EMBASE) were searched in August 2021. Backward and forward citation searching was conducted. REVIEW METHODS: Studies investigating patient-mediated interventions, targeted at adult hospitalized patients were eligible. Data were extracted related to study and intervention characteristics. Narrative synthesis was used to understand intervention impact on patient, clinician and organization outcomes (as per a framework). Methodological quality was assessed using the Mixed Methods Assessment Tool. RESULTS: Thirty-three studies, reporting 18 interventions, were included. Twelve interventions prompted patients to report health information about their own health/needs/concerns and six interventions encouraged patients to provide feedback about clinical practice. Across all interventions, there was evidence that patients used patient-mediated interventions and that they may improve patient communication. Healthcare professional outcomes were mixed for actual/intended use, acceptability and usefulness of interventions; yet there was some evidence of healthcare professional behaviour change. Interventions that encouraged patients to report health information about their own health/needs/concerns appeared more successful than other types of interventions. CONCLUSIONS: There is some evidence that hospital-based patient-mediated interventions may influence patient communication and healthcare professional behaviour. Patient-mediated interventions that encourage patients to report patient data before a clinical encounter may be more impactful than interventions that encourage patient feedback during or post-encounter. IMPACT: To date, most patient-mediated intervention research has been conducted in primary care settings; we uncovered the types of patient-mediated interventions that have been trialled in hospitals. We found that patient communication and healthcare professional behaviour may be influenced by these patient-mediated interventions. Future researchers could explore the suitability and effectiveness of a wider range of hospital-based patient-mediated interventions. NO PATIENT OR PUBLIC CONTRIBUTION: There was no funding to remunerate a patient/member of the public for this review.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".