Organizational Context Matters: A Research Toolkit for Conducting Standardized Case Studies of Integrated Care Initiatives
Bibliographic record
Abstract
INTRODUCTION: The variable success of integrated care initiatives has led experts to recommend tailoring design and implementation to the organizational context. Yet, organizational contexts are rarely described, understood, or measured with sufficient depth and breadth in empirical studies or in practice. We thus lack knowledge of when and specifically how organizational contexts matter. To facilitate the accumulation of evidence, we developed a research toolkit for conducting case studies using standardized measures of the (inter-)organizational context for integrating care. THEORY AND METHODS: We used a multi-method approach to develop the research toolkit: (1) development and validation of the Context and Capabilities for Integrating Care (CCIC) Framework, (2) identification, assessment, and selection of survey instruments, (3) development of document review methods, (4) development of interview guide resources, and (5) pilot testing of the document review guidelines, consolidated survey, and interview guide. RESULTS: The toolkit provides a framework and measurement tools that examine 18 organizational and inter-organizational factors that affect the implementation and success of integrated care initiatives. DISCUSSION AND CONCLUSION: The toolkit can be used to characterize and compare organizational contexts across cases and enable comparison of results across studies. This information can enhance our understanding of the influence of organizational contexts, support the transfer of best practices, and help explain why some integrated care initiatives succeed and some fail.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".