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Prototype Prescribing Outlier Dashboard for Derby Family Medical Centre

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 Derby Family Medical Centre is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Tafluprost and timolol 24 Treatment of glaucoma 296 0.08 0.00 0.01 9.98
Timolol 33 Beta-adrenoceptor blocking drugs 2,710 0.01 0.00 0.00 8.55
Loprazolam mesilate 8 Hypnotics 186 0.04 0.00 0.01 6.32
Triptorelin acetate 13 Prostate cancer and gonadorelin analogues 34 0.38 0.02 0.06 6.11
Zonisamide 77 Control of epilepsy 1,453 0.05 0.01 0.01 5.82
Dimenhydrinate/cinnarizine 7 Drugs used in nausea and vertigo 342 0.02 0.00 0.00 5.25
Fluocinolone acetonide 48 Topical corticosteroids 910 0.05 0.01 0.01 5.18
Acenocoumarol 7 Oral anticoagulants 501 0.01 0.00 0.00 4.54
Other calcium supplement preparations 11 Calcium supplements 18 0.61 0.05 0.12 4.53
Clomipramine hydrochloride 89 Tricyclic and related antidepressant drugs 1,071 0.08 0.01 0.02 4.53

Prescribing where Derby Family Medical Centre is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Calcium carbonate 7 Calcium supplements 18 0.39 0.95 0.13 -4.29
Colecalciferol 861 Vitamin D 987 0.87 0.96 0.02 -3.72
Quetiapine 30 Antipsychotic drugs 642 0.05 0.35 0.12 -2.49
Co-codamol (Codeine phosphate/paracetamol) 241 Non-opioid analgesics and compound preparations 2,368 0.10 0.45 0.15 -2.27
Prednisolone 283 Use of corticosteroids 374 0.76 0.89 0.06 -2.25
Methotrexate 47 Rheumatic disease suppressant drugs 179 0.26 0.58 0.15 -2.03
Fexofenadine hydrochloride 123 Antihistamines 1,096 0.11 0.34 0.12 -1.96
Progesterone 0 Progestogens and progesterone receptor modulators 43 0.00 0.53 0.27 -1.96
    Zinc sulfate monohydrate 0 Zinc 4 0.00 0.74 0.39 -1.90
      Morphine sulfate 56 Opioid analgesics 979 0.06 0.20 0.08 -1.88