A Framework for the Design of Web Service Based Clinical Management Systems to Support Inter and Intra Organizational Patient Journeys
Bibliographic record
Abstract
The clinical management of premature and ill term babies is challenged by the necessity of several inter and intra organizational patient journeys. Premature and ill-term babies born in regional Australia and Canada must be moved to another hospital with Neonatal Intensive Care Unit (NICU) facilities. NICU babies requiring surgery must be moved to a Level IV NICU for surgery. Current clinical management supports the transfer of limited patient data via paper or telephone exchange. In this article a framework for the design of Web-service-based clinical management systems to support inter and intra organizational patient journeys is presented. A series of Web services are described and integrated and coordinated through BPEL processes enabling greater support for inter- and intra-organizational transfer of patient data. This framework is demonstrated through a NICU case study. A key benefit of this framework is that it enables the establishment of “on demand” patient journeys eliminating the need to establish permanent point-to-point connections.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".