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.
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 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 | 0.002 | 0.006 |
| 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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".