Using Patient- and Family-Reported Outcome and Experience Measures Across Transitions of Care for Frail Older Adults Living at Home: A Meta-Narrative Synthesis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Our aim was to create a "storyline" that provides empirical explanation of stakeholders' perspectives underlying the use of patient- and family-reported outcome and experience measures to inform continuity across transitions in care for frail older adults and their family caregivers living at home. RESEARCH DESIGN AND METHODS: We conducted a meta-narrative synthesis to explore stakeholder perspectives pertaining to use of patient-reported outcome and experience measures (PROMs and PREMs) across micro (patients, family caregivers, and healthcare providers), meso (organizational managers/executives/programs), and macro (decision-/policy-makers) levels in healthcare. Systematic searches identified 9,942 citations of which 40 were included based on full-text screening. RESULTS: PROMs and PREMS (54 PROMs; 4 PREMs; 1 with PROM and PREM elements; 6 unspecified PROMs) were rarely used to inform continuity across transitions of care and were typically used independently, rarely together (n = 3). Two overarching traditions motivated stakeholders' use. The first significant motivation by diverse stakeholders to use PROMs and PREMs was the desire to restore/support independence and care at home, predominantly at a micro-level. The second motivation to using PROMs and PREMs was to evaluate health services, including cost-effectiveness of programs and hospital discharge (planning); this focus was rarely at a macro-level and more often split between micro- and meso-levels of healthcare. DISCUSSION AND IMPLICATIONS: The motivations underlying stakeholders' use of these tools were distinct, yet synergistic between the goals of person/family-centered care and healthcare system-level goals aimed at efficient use of health services. There is a missed opportunity here for PROMs and PREMs to be used together to inform continuity across transitions of care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".