Interoperability in NHS Acute Trusts within England: a Situation and Capability Analysis using Freedom of Information requests
Bibliographic record
Abstract
Abstract Background Many central initiatives to improve digital maturity and interoperability in the NHS started after 2015. There are few prior assessments of digital maturity and interoperability. Methods Freedom of Information Act requests were sent to all English Acute NHS Trusts and Clinical Commissioning Groups (CCGs) to obtain information regarding digital maturity according to the Healthcare Information and Management Systems Society (HIMSS) Electronic Medical Record Adoption Mode (EMRAM) scale, and interoperability. Results One third of Acute NHS Trusts have an EMR that meets requirements for EMRAM stage 6 or above. 17.4% of responding Trusts considered this. 59.1% of responding Trusts stated that their EMR allows for functional interoperability with other (interoperable) EMRs. The majority of responding Trusts had not conferred with other Trusts when making EMR purchasing decisions. Discussion In order to realise the benefits of digitisation and interoperability, we discuss policy recommendations including actions for local health economies.
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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 | 0.027 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".