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Prototype Prescribing Outlier Dashboard for Great Massingham Surgery

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 Great Massingham Surgery is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Metoprolol tartrate 254 Beta-adrenoceptor blocking drugs 3,959 0.06 0.01 0.01 6.35
Tryptophan 4 Other antidepressant drugs 2,015 0.00 0.00 0.00 5.58
Trifluoperazine 27 Antipsychotic drugs 682 0.04 0.00 0.01 4.83
Urea 74 Emollients 223 0.33 0.09 0.06 4.10
Diamorphine hydrochloride (Systemic) 13 Opioid analgesics 1,659 0.01 0.00 0.00 3.99
Methocarbamol 254 Skeletal muscle relaxants 396 0.64 0.08 0.15 3.70
Triamcinolone acetonide 50 Drugs used in nasal allergy 800 0.06 0.01 0.02 3.62
Travoprost 166 Treatment of glaucoma 1,251 0.13 0.04 0.03 3.07
Calcitriol 8 Preparations for psoriasis 95 0.08 0.01 0.02 2.95
Flupentixol hydrochloride 82 Other antidepressant drugs 2,015 0.04 0.01 0.01 2.87

Prescribing where Great Massingham Surgery is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Other emollient preparations 149 Emollients 223 0.67 0.89 0.07 -3.25
Baclofen 109 Skeletal muscle relaxants 396 0.28 0.83 0.18 -3.05
Nicotine 0 Nicotine dependence 6 0.00 0.65 0.33 -1.95
    Aciclovir 67 Herpes simplex and varicella-zoster 81 0.83 0.95 0.07 -1.91
    Donepezil hydrochloride 59 Drugs for dementia 390 0.15 0.49 0.18 -1.84
    Mirtazapine 756 Other antidepressant drugs 2,015 0.38 0.57 0.10 -1.83
    Letrozole 13 Breast cancer 242 0.05 0.45 0.22 -1.82
    Fusidic acid 30 Antibacterial preparations also used systemically 61 0.49 0.75 0.14 -1.80
    Levothyroxine sodium 3,413 Thyroid hormones 3,436 0.99 1.00 0.00 -1.78
    Colecalciferol 1,201 Vitamin D 1,302 0.92 0.96 0.02 -1.68