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Prototype Prescribing Outlier Dashboard for Bridge View 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 Bridge View PCN is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Ertugliflozin 378 Other antidiabetic drugs 3,885 0.10 0.00 0.00 43.52
Doxycycline monohydrate 34 Tetracyclines 994 0.03 0.00 0.00 9.21
Saxagliptin 534 Other antidiabetic drugs 3,885 0.14 0.01 0.02 7.45
Dipyridamole and aspirin 1 Antiplatelet drugs 8,313 0.00 0.00 0.00 5.91
Dexpanthenol 11 Emollients 565 0.02 0.00 0.00 5.68
Zolpidem tartrate 764 Hypnotics 2,664 0.29 0.07 0.04 5.34
Brivaracetam 124 Control of epilepsy 9,694 0.01 0.00 0.00 4.70
Celiprolol hydrochloride 40 Beta-adrenoceptor blocking drugs 9,477 0.00 0.00 0.00 4.59
Ferric maltol 19 Oral iron 1,553 0.01 0.00 0.00 4.51
Varicella vaccine live 8 Vaccines and antisera 6,276 0.00 0.00 0.00 4.16

Prescribing where Bridge View PCN is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Zinc oxide 9 Soothing haemorrhoidal preparations 33 0.27 0.78 0.13 -3.84
Ciprofloxacin 92 Quinolones 164 0.56 0.86 0.08 -3.60
Glucose blood testing reagents 1,242 Diabetic diagnostic and monitoring agents 1,445 0.86 0.94 0.02 -3.53
Atropine sulfate 0 Mydriatics and cycloplegics 5 0.00 0.75 0.22 -3.46
    Coal tar 45 Shampoos and some other scalp preparations 241 0.19 0.40 0.09 -2.51
    Aspirin 4,531 Antiplatelet drugs 8,313 0.55 0.65 0.04 -2.46
    Salicylic acid 4 Preparations for warts and calluses 29 0.14 0.65 0.22 -2.36
    Alfentanil hydrochloride 0 Opioid analgesics 4 0.00 0.84 0.35 -2.36
      Timolol and bimatoprost 27 Treatment of glaucoma 2,016 0.01 0.10 0.04 -2.13
      Sodium picosulfate 0 Bowel cleansing preparations 2 0.00 0.70 0.35 -2.04