Medical device standardisation for diabetes: a 6–year evaluation of cost savings
Bibliographic record
Abstract
Background/Aims This is a follow-up study to research published in 2017, which evaluated the effectiveness of an audit and change programme aiming to improve the cost-effectiveness of self-monitoring of blood glucose prescribing in two Greater Manchester clinical commissioning groups. The present study aimed to assess the longevity of the changes achieved over a 6-year period, comparing clinical commissioning groups that adopted the change programme in 2015 with those that adopted it later or not at all in Greater Manchester. Methods Prescribing data for Greater Manchester were extracted from a publicly available database and categorised into three groups: clinical commissioning groups that adopted a medicines optimisation programme in 2015, those that adopted it later and those that did not adopt the programme. The savings of each clinical commissioning group were balanced using diabetes prevalence data and compared against an average clinical commissioning group in England. Data were compared using Kruskal Wallis tests, post-hoc Dunn's tests, Mann-Whitney U tests and linear regression. Results Clinical commissioning groups that implemented the change programme in 2015 had greater savings than those that did not implement the change programme (P=0.0036). The former group also saw greater percentage reductions in mean self-monitoring of blood glucose unit costs than the NHS England average (29.6% vs 20.3%; P<0.001) between the fourth quarter of 2014 and the fourth quarter of 2020. Conclusions A structured change programme that aims to standardise prescribing can lead to substantial cost savings over a time period of 6 years.
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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 | 0.005 | 0.001 |
| 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 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".