Team Leadership for Interprofessional Collaborative Practice in Primary Care: A scoping review
Bibliographic record
Abstract
Context: Health systems have been shifting toward interprofessional collaboration (IPC) and team-based practice to address fragmented care, strengthen a system for integrated, coordinated care, and improve patient outcomes. Despite recognition by the Canadian Interprofessional Health Collaborative that leadership is one of the strategic foci needed for IPC, there is a limited investigation of leadership competencies and capacity for fostering teamwork among interprofessional health care providers. Objective: To examine existing research about facilitators and barriers among the individuals leading IPC in primary care settings. Study Design and Analysis: A scoping review of articles from health care, business, organizational leadership, and multi-disciplinary databases since January 2000 as the timeframe within which primary health care reform was initiated in Canada. Setting or Dataset: A total of 4997 articles were title and abstract screened using Covidence. In a second stage, 377 full-text articles were reviewed and screened, resulting in 101 articles from which data was extracted. At least two investigators screened each article at all stages, and a third reviewer resolved discrepancies. Results: While leadership was discussed in all included articles, only 29.7% of the studies specifically focused on the leadership role for IPC in primary care. Effective leadership was characterized by the following personal attributes: i) good communication; ii) charisma; iii) inclusiveness; iv) supportiveness; v) reliability. Studies showed that the designation of a leader was context dependent. There were no formal processes to designate the team leader within IPC teams, however this literature suggests the primary sources of the leader’s authority stemmed from exhibiting leadership attributes (12.9%), hierarchy-based assignment (7.9%), and better knowledge of patients (5.9%). The main factors limiting effective leadership were hierarchical governance, authoritative leadership, a high degree of physician specialization, frequent staff turnover, and inadequate training for health care providers to work as a team. Conclusions: The results of this scoping review indicate the need to conduct further detailed research on leadership for IPC in primary health care teams. This includes advancing a purposeful leadership development model specific to IPC that could improve health services delivery and improve patient satisfaction and integrated primary health 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 | 0.040 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".