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Prototype Prescribing Outlier Dashboard for The Willow Group

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 Practices. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given Practice 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 Practice's chemical:subparagraph ratios is provided, with this Practice'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 The Willow Group is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Salicylic acid 1 Drugs for oral ulceration and inflammation 143 0.01 0.00 0.00 3.80
Denosumab 135 Bisphosphonates and other drugs 1,797 0.08 0.01 0.02 3.53
Isophane insulin 1,140 Intermediate and long-acting insulins 2,539 0.45 0.12 0.10 3.21
Formoterol/glycopyrronium/budesonide 34 Corticosteroids (respiratory) 7,393 0.00 0.00 0.00 2.87
Quinapril hydrochloride with diuretic 4 Angiotensin-converting enzyme inhibitors 15,635 0.00 0.00 0.00 2.86
Soluble insulin (Neutral insulin) 65 Short-acting insulins 882 0.07 0.01 0.02 2.78
Mometasone furoate 548 Topical corticosteroids 3,070 0.18 0.07 0.04 2.53
Dulaglutide 1,229 Other antidiabetic drugs 6,437 0.19 0.06 0.05 2.50
Methocarbamol 444 Skeletal muscle relaxants 982 0.45 0.08 0.15 2.45
Benzalkonium chloride 54 Shampoos and some other scalp preparations 322 0.17 0.04 0.05 2.44

Prescribing where The Willow Group is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Urea hydrogen peroxide 2 Removal of ear wax and other substances 12 0.17 0.83 0.33 -2.02
Other emollient preparations 759 Emollients 990 0.77 0.89 0.07 -1.81
Baclofen 497 Skeletal muscle relaxants 982 0.51 0.83 0.18 -1.77
Betamethasone valerate 528 Topical corticosteroids 3,070 0.17 0.28 0.07 -1.65
Bimatoprost 44 Treatment of glaucoma 1,974 0.02 0.11 0.06 -1.49
Insulin glargine 344 Intermediate and long-acting insulins 2,539 0.14 0.33 0.13 -1.48
Ganciclovir 0 Antivirals 1 0.00 0.63 0.43 -1.46
    Medroxyprogesterone acetate 0 Progestogens 1 0.00 0.66 0.45 -1.46
      Mercaptopurine 36 Antimetabolites 120 0.30 0.80 0.35 -1.45
      Lansoprazole 5,531 Proton pump inhibitors 25,468 0.22 0.44 0.16 -1.42