Implementing point-of-care testing to improve outcomes
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
Point-of-care testing (POCT) is defined as testing performed outside of the central laboratory at or near the patient’s bedside. A number of devices have been developed that permit a wide menu of tests to be performed at the POC. In most cases the unit cost of POC tests is greater than similar testing performed in the central laboratory. For this reason when implementing POCT it is important to demonstrate an improvement in outcomes to justify the added incremental cost of the testing. Outcomes may be classified as either medical outcomes, financial outcomes or outcomes reflecting an improvement in clinical operations or efficiency. In most cases where outcomes have been demonstrated for POCT the impact has been to improve the efficiency of clinical operations. Less often POCT has been linked to an improvement in medical outcomes. This paper will describe selected case studies available in the literature to demonstrate how improved outcomes can be achieved and documented from POCT in a variety of different settings.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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