Care Coordination of Older Adults With Diabetes: A Scoping Review
Bibliographic record
Abstract
OBJECTIVES: Care coordination is a common intervention to support older adults with diabetes and their caregivers, and provides individualized, integrated health and social care. However, the optimal approach of care coordination is not well described. In this scoping review we synthesized evidence regarding the implementation of traditional and virtual care coordination for older adults with diabetes to inform future research and best practices. METHODS: The Joanna Briggs Institute scoping review methods were used. A systematic search was conducted in CINAHL, Embase, EmCare, and Medline, as well as a targeted grey literature search, and a hand-search of reference lists. Screening and data extraction were completed by 3 independent reviewers. RESULTS: Forty-two articles were included in the synthesis. Included studies operationalized care coordination in different ways. The most commonly implemented elements of care coordination were regular communication and monitoring. In contrast, coordination between health-care teams and the community, individualized planning, and caregiver involvement were less often reported. Outcomes to evaluate the impact of care coordination were predominantly diabetes-centric, and less often person-centred. In addition, evidence indicates that older adults value a trusting relationship with their care coordinator. CONCLUSIONS: Studies assessing care coordination for older adults with diabetes have shown positive outcomes. To inform best practices, future intervention research for this population should focus on evaluating the impact of comprehensive care planning, system navigation across the health and social care sectors, the care coordinator and patient relationship and caregiver support.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".