Bibliographic record
Abstract
BACKGROUND: : Health care transformations often involve the development of networks to ensure smooth and safe patient flows throughout the care continuum. However, more empirical information is needed on the workings of health networks and on how their structures, processes, and systems influence access to high-quality patient care. PURPOSE: : Using Miller's concept of configuration, we describe the workings of a health network specialized in the provision of neonatal-perinatal care, a specialty where accessibility issues are quite problematic. We aimed to generate evidence that will assist policy makers, network managers, and clinicians in facilitating access to high-quality neonatal-perinatal care. METHODOLOGY/APPROACH: : From late 2007 to early 2008, we conducted a case study of all (N = 7) neonatal intensive care units (NICUs) in the province of Quebec (Canada). We performed field work into two purposefully selected NICUs. This involved 450 hours of nonparticipant observation and 56 semistructured interviews with various actors. Data from these sources were triangulated with data collected during informal interviews with key actors from the other five NICUs in the province and from administrative databases. FINDINGS: : We found that the elements of this health network are pulled together by a core orchestrating theme: "Forcing the system." Indeed, in attempting to fulfill the network mission of providing access to high-quality neonatal-perinatal care, clinicians and managers must implement various strategies to compensate for the misfit of the configuration. Although these strategies are successful in providing access to neonatal-perinatal care, they, however, have adverse effects that are paradoxically in contradiction with the network's core mission. PRACTICE IMPLICATIONS: : This configuration analysis enabled us to identify a set of modifiable elements that contribute to the misfit of the configuration and its suboptimal functioning. The comprehensiveness of the configuration approach was proven useful for the analysis of such a complex organizational form.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".