MODELING CLINICAL PATHWAYS AS BUSINESS PROCESS MODELS USING BUSINESS PROCESS MODELING NOTATION
Bibliographic record
Abstract
We take a healthcare knowledge management approach to represent the Clinical Pathway (CP) as workflows. We have developed a semantic representation of CP in terms of a CP ontology that outlines the different clinical processes, their properties, constraints and relationships, and is able to computerize a range of CP. To model business workflows we use the graphical Business Process Modeling Notation (BPMN) modeling language that generates a BPMN ontology. To represent a CP as a BPMN workflow, we have developed a semantic interoperability (mapping ontology) framework between the CP ontology and the BPMN ontology. The mapping ontology allows the alignment of relations between two ontologies and ensures that a clinical process defined in the CP ontology is mapped to a standard BPMN workflow element. We execute our BPMN-based CP in the Lombardi workflow engine, whereby users can view the execution of the CP and make the necessary adjustments.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".