Product standardisation as a tool to control prescribing costs – a case study of alginate liquid preparations
Bibliographic record
Abstract
INTRODUCTION: Product standardisation involves promoting the prescribing of pre-selected products within a particular category across a healthcare region and is designed to improve patient safety by promoting continuity of medicine use across the primary/secondary care interface, in addition to cost containment without compromising clinical care (i.e. maintaining safety and efficacy). OBJECTIVES: To examine the impact of product standardisation on the prescribing of compound alginate preparations within primary care in Northern Ireland. METHODS: Data were obtained on alginate prescribing from the Northern Ireland Central Services Agency (Prescription Pricing Branch), covering a period of 43 months. Two standardisation promotion interventions were carried out at months 18 and 33. In addition to conventional statistical analyses, a simple interrupted time series analysis approach, using graphical interpretation, was used to facilitate interpretation of the data. RESULTS: There was a significant increase in the prescribed share of the preferred alginate product in each of the four health boards in Northern Ireland and a decrease in the cost per Defined Daily Dose for alginate liquid preparations overall. Compliance with the standardisation policy was, however, incomplete and was influenced to a marked degree by the activities of the pharmaceutical industry. The overall economic impact of the prescribing changes during the study was small (3.1%). CONCLUSION: The findings suggested that product standardisation significantly influenced the prescribing pattern for compound alginate liquid preparations within primary care across Northern Ireland.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".