Help! Working with change: An organizational change process model and online registry of resources
Bibliographic record
Abstract
Abstract Background The health system is continuously undergoing change in response to various internal and external drivers. The organizational change literature is complex and multi-disciplinary, making it challenging for health professionals to utilize efficiently. To support practitioners through times of change, The National Collaborating Centre for Methods and Tools (NCCMT) developed a health sector-specific model of organizational change, by synthesizing existing models and frameworks, and developed an online registry of resources to help guide practitioners through the change process. Objectives Existing change process models were identified through a scoping review of reviews published from 2000-2015, supplemental searches using a snowball method, and contact with key informants. A thematic analysis identified key themes and activities. To support the use of the model, a search of the academic and grey literature was conducted to identify practical organizational change tools. Resources were tagged with specific stages in the model and added to an online interactive Registry. The online Registry is available for practitioners to gain knowledge and understanding of processes of change relevant to the health sector, identify facilitators and barriers to change, and use methods and tools to support practitioners throughout the change process. Results A total of 30 organizational change process models were identified and synthesized to create a new five-stage model: assessing the NEED for change; PLANning for change; IMPLEMENTing change initiatives; SUSTAINing change within the organization; and EVOLVing to continuously meet drivers for change. The easy to use and interactive platform hosts over 100 practical tools linked to stages in the model to support organization and systems change. Conclusions This new resource will support the implementation of evidence-informed practices, policies and programs in public health and the broader health care system. Key messages The health system is continuously undergoing change and can be challenging to navigate. A health sector-specific organizational change process model and online registry of resources can help guide public health professionals throughout the change process.
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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 | 0.044 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".