Exploring the relationship between governance mechanisms in healthcare and health workforce outcomes: a systematic review
Bibliographic record
Abstract
BACKGROUND: The objective of this systematic review of diverse evidence was to examine the relationship between health system governance and workforce outcomes. Particular attention was paid to how governance mechanisms facilitate change in the workforce to ensure the effective use of all health providers. METHODS: In accordance with standard systematic review procedures, the research team independently screened over 4300 abstracts found in database searches, website searches, and bibliographies. Searches were limited to 2001-2012, included only publications from Canada, the United Kingdom, the Netherlands, New Zealand, Australia, and the United States. Peer- reviewed papers and grey literature were considered. Two reviewers independently rated articles on quality and relevance and classified them into themes identified by the team. One hundred and thirteen articles that discussed both workforce and governance were retained and extracted into narrative summary tables for synthesis. RESULTS: Six types of governance mechanisms emerged from our analysis. Shared governance, Magnet accreditation, and professional development initiatives were all associated with improved outcomes for the health workforce (e.g., decreased turnover, increased job satisfaction, increased empowerment, etc.). Implementation of quality-focused initiatives was associated with apprehension among providers, but opportunities for provider training on these initiatives increased quality and improved work attitudes. Research on reorganization of healthcare delivery suggests that changing to team-based care is accompanied by stress and concerns about role clarity, that outcomes vary for providers in private versus public organizations, and that co-operative clinics are beneficial for physicians. Funding schemes required a supplementary search to achieve adequate depth and coverage. Those findings are reported elsewhere. CONCLUSIONS: The results of the review show that while there are governance mechanisms that consider workforce impacts, it is not to the extent one might expect given the importance of the workforce for improving patient outcomes. Furthermore, to successfully implement governance mechanisms in this domain, there are key strategies recommended to support change and achieve desired outcomes. The most important of these are: to build trust by clearly articulating the organization's goal; considering the workforce through planning, implementation, and evaluation phases; and providing strong leadership.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".