Patterns of health information exchange strategies underlying health information technologies capabilities building
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The combination of electronic health records (EHRs), health information exchange (HIE), and telehealthholds a high potential for improving the coordination of care and saving lives. As well, the benefits of the three HIT on hospitals' depend on the patterns of capabilities that are available and used by clinicians. However, little is known about how the three HIT, actually empirically coexist and about the strategies underlying the use of HIE in hospital settings. Based on data from a European Union survey, we use a combination of hierarchical and non-hierarchical clustering and discriminant analysis to identify patterns of hospitals' HIT capabilities. Five statistically significantly separated configurations were derived from a data set of 1038 acute care hospitals. The actual empirical coexistence of the three HIT capabilities and associated HIE strategies revealed by this study can be counter-intuitive and shed light on misalignments that may impede the realisation of the potential benefits.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it