Patient-centred innovation for multimorbidity care: a mixed-methods, randomised trial and qualitative study of the patients’ experience
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Patient-centred interventions to help patients with multimorbidity have had mixed results. AIM: To assess the effectiveness of a provider-created, patient-centred, multi-provider case conference with follow-up, and understand under what circumstances it worked, and did not work. DESIGN AND SETTING: Mixed-methods design with a pragmatic randomised trial and qualitative study, involving nine urban primary care sites in Ontario, Canada. METHOD: Patients aged 18-80 years with ≥3 chronic conditions were referred to the Telemedicine IMPACT Plus intervention; a nurse and patient planned a multi-provider case conference during which a care plan could be created. The patients were randomised into an intervention or control group. Two subgroup analyses and a fidelity assessment were conducted, with the primary outcomes at 4 months being self-management and self-efficacy. Secondary outcomes were mental and physical health status, quality of life, and health behaviours. A thematic analysis explored the patients' experiences of the intervention. RESULTS: = 0.006). More providers and follow-up hours were associated with poorer outcomes. Five themes were identified in the qualitative study: valuing the team, patients feeling supported, receiving a follow-up plan, being offered new and helpful additions to their treatment regimen, and experiencing positive outcomes. CONCLUSION: Overall, the intervention showed improvements only for patients who had an annual income of ≥C$50 000, implying a need to address the costs of intervention components not covered by existing health policies. Findings suggest a need to optimise team composition by revising the number and type of providers according to patient preferences and to enhance the hours of nurse follow-up to better support the patient in carrying out the case conference's recommendations.
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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 | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it