Appropriateness of the use of intravenous immune globulin before and after the introduction of a utilization control program.
Bibliographic record
Abstract
BACKGROUND: Intravenous immune globulin (IVIG) is an expensive and sometimes scarce blood product that carries some risk. It may often be used inappropriately. We evaluated the appropriateness of IVIG use before and after the introduction of an utilization control program to reduce inappropriate use. METHODS: We used the RAND/UCLA Appropriateness Method to measure the appropriateness of IVIG use in the province of British Columbia (BC) in 2001 and 2003, before and after the introduction of a utilization control program designed to reduce inappropriate use. For comparison, we measured the appropriateness of use during the same periods in the province of Alberta, which had no control program. RESULTS: Of 2256 instances of IVIG use, 54.1% were deemed to be appropriate, 17.4% were of uncertain benefit, and 28.5% were deemed inappropriate. The frequency of inappropriate use in BC after the introduction of the utilization control program did not differ significantly from the frequency before the program or the frequency in Alberta. INTERPRETATION: Almost half of IVIG use in BC and Alberta was judged to be inappropriate or of uncertain benefit, and the frequency of inappropriate use did not decrease after implementation of a utilization control program in BC. More effective utilization controls are necessary to prevent wasted resources and unnecessary risk to patients.
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.
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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".