Social workers coordination in primary healthcare for patients with complex needs: A scoping review
Bibliographic record
Abstract
Introduction Care coordination has been part of social work for some time. It has been recognized as contributing to care coordination for long-term care for the elderly and mental health but less is known about their contribution in primary care with patients with complex health and social needs. As social workers are increasingly present in primary healthcare, this scoping review aims to provide a synthesis of social workers’ coordination activities for patients with complex needs in primary healthcare. Methods CINAHL, Medline, Scopus, SocioIndex, Social Work Abstracts, and ProQuest databases were searched, from 2004 to 2020 for peer-reviewed literature. A thematic analysis using deductive and inductive approaches was used to conduct this scoping review. Results Eighteen studies on 11 different care coordination interventions were included. The care coordination activities have been classified into four categories: 1) activities that target the patient, family, and caregivers; 2) activities that target health and social care professionals and services; 3) activities that link the patient and family with health and social professionals and services; and 4) cross-cutting activities that support and enhance other activity. Discussion A variety of care coordination interventions conducted by social workers were identified, all of which included related but different activities. Still, the common aim is to reduce fragmentation of care. Social workers, because of their disciplinary skills characterized by linkages to nonmedical services, can make a significant contribution to the coordination of care in primary health care, in collaboration with nurses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".