Concept mapping brainstorming results for improving care transitions for adults with hip fracture in Ontario, Canada
Bibliographic record
Abstract
Introduction: Individuals who have experienced a hip fracture often undergo numerous transitions in care between providers and sectors. These transitions are a time of vulnerability with the potential for poor health outcomes and experiences, yet there are limited recommendations on how to improve this care journey for adults with hip fracture. Target Audience: The target audience for our study include decision-makers and providers with a hip fracture portfolio, as well as patients who have experienced a hip fracture and their unpaid caregivers. Who was involved: This study included patient and caregiver partners. They were involved in the grant application, study participant recruitment, data collection, and final data analysis. This study also included healthcare provider and decision-maker partners who supported participant recruitment and will be knowledge users. Aims and Methods: The aim of this study was to create a list of actionable recommendations to improve care transitions for individuals with hip fracture from the perspectives of patients, caregivers, providers, and decision-makers. We used a mixed methods concept mapping approach, to gather perspectives from these key stakeholders in Ontario, Canada. Here, we report on the results of the first phase of the concept mapping study. Participants created a list of statements that they felt would improve care transitions for individuals who had experienced a hip fracture. The statements were analyzed inductively and grouped thematically. Results: Thirty-two individuals participated in the brainstorming phase of this study (2 patients, 5 caregivers, 21 providers, 4 decision-makers). They created 887 statements that were condensed by the research team into 72 final statements. The final statements were grouped into seven main themes and were divided into four domains for care transition improvement. The first is the patient-related domain, which encompassed two themes: self-management and self-management-support, and rehabilitation therapy and activities. The second domain is provider-related and includes: healthcare provider skills and communication and trust. The third domain includes two system-related themes: continuity of care and health system efficiencies. The last domain relates to care processes with one theme: transition planning and follow up care. Learnings for the international audience: Previous literature on improving care transitions has had focused primarily on the transfer of information between care providers with little emphasis on the caregiver/patient role. Our results, however, highlight the importance of meaningful patient and caregiver engagement, with active involvement in all aspects of care including the transition process. Further, many statements created by our participants included policies, assessments, and care specific to individuals with hip fracture and cognitive impairment/delirium, emphasizing this as an important area for consideration when aiming to improve care transitions. Next Steps: The next phases of concept mapping will be conducted, which will include statement sorting and rating (importance and priority). A final concept mapping session will be held integrating the qualitative and quantitative data and an opportunity to reflect on the findings with key stakeholders. Statements that are rated highly importance and priority will inform actionable recommendations to improve care transitions for hip fracture.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".