Nurses’ and Patients’ Perspectives on Care Coordination Across Health Care and Social Services Sectors: A Qualitative Study
Bibliographic record
Abstract
BackgroundNurse care coordinators strive to build connections between different organizations to assist patients with complex needs in navigating the healthcare system. However, they often lack adequate support in their roles and encounter challenges related to the tasks themselves and to organizational and systemic factors.PurposeThis study aims to evaluate a care coordination program in Quebec from the perspectives of both providers and beneficiaries.MethodsWe used a qualitative research design following an experience-based co-design approach.19 semi-structured interviews were held, ten with nurse care coordinators and nine with older adults and informal caregivers. An interview guide based on Valentijn et al. framework was used. Data were analysed using both deductive and inductive approaches.ResultsFactors influencing care coordination practice and the experience of older adults were identified. These include growing complexity of needs, patient-centered care, trusting relationships, interprofessional collaboration, communication tools, role clarity, shared values and objectives, the merger of health and social care institutions, and governmental guidelines and standards.ConclusionMany integrated care objectives are effectively implemented. Despite nurses' efforts, older adults have expressed a need for more presence from care coordinators and better communication. This stems from the increasing complexity of patients' needs and situations, as well as the nursing shortage. The study provides a systemic perspective on the challenges of a care coordination program at various levels. As such, it offers valuable insights for care providers, staff managers, and policymakers in integrated healthcare systems, enabling targeted improvements and offering guidance for broader application.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".