FHIR: Reducing Friction in the Exchange of Healthcare Data
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
With the full clout of the Centers for Medicare and Medicaid Services currently being brought to bear on healthcare providers to meet high standards for patient data interoperability and accessibility, it would be easy to assume the only reason this goal wasn't accomplished long ago is simply a lack of will. Interoperable data? How hard can that be? Much harder than you think, it turns out. To dig into why this is the case, we asked Pat Helland, a principal architect at Salesforce, to speak with James Agnew (CTO) and Adam Cole (senior solutions architect) of Smile CDR, a Toronto, Ontario-based provider of a leading platform used by healthcare organizations to achieve FHIR (Fast Healthcare Interoperability Resources) compliance. They discuss the efforts and misadventures witnessed along the way to a time where it no longer seems inconceivable for healthcare providers to exchange patient records.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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