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Prototype Prescribing Outlier Dashboard for Brixham And Paignton PCN

At OpenPrescribing we are piloting a number of data-driven approaches to identify unusual prescribing and collect feedback on this prescribing to inform development of new tools to support prescribers and organisations to audit and review prescribing. These pilot results are provided for the interest of advanced users, although we don't know how relevant they are in practice. There is substantial variation in prescribing behaviours, across various different areas of medicine. Some variation can be explained by demographic changes, or local policies or guidelines, but much of the remaining variation is less easy to explain.

The DataLab is keen to hear your feedback on the results. You can do this by completing the following survey or emailing us at [email protected]. Please DO NOT INCLUDE IDENTIFIABLE PATIENT information in your feedback. All feedback is helpful, you can send short or detailed feedback.

This report has been developed to automatically identify prescribing patterns at a chemical level which are furthest away from “typical prescribing” and can be classified as an “outlier”. We calculate the number of prescriptions for each chemical in the BNF coding system, the count of all prescriptions within that chemical's BNF subparagraph, for prescriptions dispensed between June 2021 and December 2021. We then calculate the ratio of these counts along with the mean and standard deviation of those ratios across all PCNs. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given PCN is from the population mean. We then rank your “z-scores” to find the top 10 results where prescribing is an outlier for prescribing higher than its peers and those where it is an outlier for prescribing lower than its peers.

For each outlier chemical, a kernel density estimation plot of all PCN's chemical:subparagraph ratios is provided, with this PCN's ratio overlaid in red.

It is important to remember that this information was generated automatically and it is therefore likely that some of the behaviour is warranted. This report seeks only to collect information about where this variation may be warranted and where it might not, to inform research on this topic. Our full analytical method code is openly available on GitHub here.

This is a new, experimental feature. We'd love to .

Prescribing where Brixham And Paignton PCN is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Tetracosactide 2 Hypothalamic & anterior pituitary hormone & antioestrogens 5 0.40 0.01 0.07 5.25
Ferrous gluconate 546 Oral iron 3,121 0.17 0.04 0.03 4.05
Flumetasone pivalate 14 Otitis externa 720 0.02 0.00 0.00 3.83
Levonorgestrel 73 Oral progestogen-only contraceptives 1,720 0.04 0.01 0.01 3.76
Triptorelin 267 Prostate cancer and gonadorelin analogues 514 0.52 0.09 0.12 3.62
Levofloxacin 47 Quinolones 185 0.25 0.05 0.06 3.50
Cyproterone acetate 5 Male sex hormones and antagonists 3,102 0.00 0.00 0.00 3.43
Fesoterodine fumarate 504 Drugs for urinary frequency enuresis and incontinence 4,427 0.11 0.03 0.03 3.42
Atenolol 5,752 Beta-adrenoceptor blocking drugs 24,267 0.24 0.13 0.03 3.31
Lisinopril 14,933 Angiotensin-converting enzyme inhibitors 26,864 0.56 0.18 0.12 3.26

Prescribing where Brixham And Paignton PCN is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Desogestrel 1,480 Oral progestogen-only contraceptives 1,720 0.86 0.94 0.03 -2.75
Acamprosate calcium 5 Alcohol dependence 18 0.28 0.83 0.23 -2.36
Mesalazine (Systemic) 635 Aminosalicylates 1,490 0.43 0.64 0.10 -2.26
Ramipril 10,591 Angiotensin-converting enzyme inhibitors 26,864 0.39 0.70 0.14 -2.23
Ferrous fumarate 419 Oral iron 3,121 0.13 0.57 0.20 -2.21
Glycopyrronium bromide 0 Antimuscarinic drugs 146 0.00 0.78 0.36 -2.14
    Bisoprolol fumarate 13,093 Beta-adrenoceptor blocking drugs 24,267 0.54 0.66 0.06 -2.09
    Umeclidinium bromide/vilanterol 36 Compound bronchodilator preparations 1,671 0.02 0.50 0.25 -1.92
    Erythromycin 33 Macrolides 1,357 0.02 0.11 0.05 -1.86
    Aripiprazole 394 Antipsychotic drugs 5,737 0.07 0.13 0.03 -1.77