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 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 | 0.049 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".