A Bounded Health Information Technology System Design Approach to Support Community-Based Care Delivery
Bibliographic record
Abstract
Health information technology (HIT) offers great potential for supporting healthcare delivery, particularly collaborative care delivery that is provided across multiple settings and providers. To date much of HIT design has focused on digitizing data or processes on a departmental or healthcare provider basis. However, this bounded approach has not scaled well for supporting community based care across disparate providers or settings because of the lack of boundaries (e.g. disprate data and processes) that exist in community based care. Cloud computing approaches that leverage mobile form applications for developing integrated HIT solutions have the potential to support collaborative healthcare delivery in the community. However, to date there is a shortage of methods that describe how to develop integrated cloud computing solutions to support community based care delivery. In particular there is a need for methods that identify how to incorporate boundaries into cloud computing systems design. This paper uses a three year case study of the design of the Palliative Care Information System (PAL-IS) to provide system design insight on cloud computing approaches that leverage mobile forms applications to support community care management.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".