Nursing Care Coordination for Patients with Complex Needs in Primary Healthcare: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: Millions of people worldwide have complex health and social care needs. Care coordination for these patients is a core dimension of integrated care and a key responsibility for primary healthcare. Registered nurses play a substantial role in care coordination. This review draws on previous theoretical work and provides a synthesis of care coordination interventions as operationalized by nurses for complex patient populations in primary healthcare. METHODOLOGY: We followed Arksey and O'Malley's methodological framework for scoping reviews. We carried out a systematic search across CINAHL, MEDLINE, Scopus and ProQuest. Only empirical studies were included. We performed a thematic analysis using deductive (the American Nurses Association Framework) and inductive approaches. Findings were discussed with a group of experts. RESULTS: Thirty-four articles were included in the synthesis. Overall, nursing care coordination activities were synthesized into three categories: those targeting the patient, family and caregivers; those targeting health and social care teams; and those bringing together patients and professionals. Interpersonal communication and information transfer emerged as cross-cutting activities that support every other activity. Our results also brought to light the nurses' contribution to care coordination efforts for patients with complex needs as well as critical components that should be present in every care coordination intervention for this clientele. These include an increased intensity and frequency of activities, relational continuity of care, and home visits. CONCLUSION: With the growing complexity of patient's needs, efforts must be directed towards enabling the primary healthcare level to effectively play its substantial role in care coordination. This includes finding primary care employment models that would facilitate multidisciplinary teamwork and the delivery of integrated care, and guarantee the delivery of intensive yet efficient coordinated 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 | 0.017 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 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".