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Prototype Prescribing Outlier Dashboard for Dr Gandecha & Partner

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 Dr Gandecha & Partner is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Isometheptene mucate 3 Non-opioid analgesics and compound preparations 842 0.00 0.00 0.00 19.52
Vigabatrin 8 Control of epilepsy 410 0.02 0.00 0.00 12.72
Almotriptan 6 Treatment of acute migraine 22 0.27 0.01 0.02 11.42
Levofloxacin 3 Quinolones 3 1.00 0.05 0.08 11.24
Belladonna alkaloids 6 Antispasmodic and other drugs altering gut motility 88 0.07 0.00 0.01 10.41
Chlordiazepoxide hydrochloride 9 Anxiolytics 74 0.12 0.01 0.02 7.45
Meptazinol hydrochloride 8 Opioid analgesics 121 0.07 0.00 0.01 6.02
Triptorelin 1 Prostate cancer and gonadorelin analogues 1 1.00 0.09 0.16 5.88
Erythromycin 13 Macrolides 22 0.59 0.12 0.08 5.70
Estradiol with progestogen 13 Oestrogens and Hormone Replacement Therapy 13 1.00 0.39 0.12 5.15

Prescribing where Dr Gandecha & Partner is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Ciprofloxacin 0 Quinolones 3 0.00 0.86 0.14 -6.29
    Desogestrel 10 Oral progestogen-only contraceptives 14 0.71 0.93 0.05 -4.07
    Estradiol 0 Oestrogens and Hormone Replacement Therapy 13 0.00 0.47 0.14 -3.37
      Donepezil hydrochloride 0 Drugs for dementia 28 0.00 0.49 0.18 -2.66
        Omeprazole 189 Proton pump inhibitors 2,653 0.07 0.50 0.16 -2.64
        Quetiapine 8 Antipsychotic drugs 203 0.04 0.35 0.12 -2.55
        Mometasone furoate 3 Drugs used in nasal allergy 142 0.02 0.32 0.13 -2.26
        Pregabalin 44 Control of epilepsy 410 0.11 0.27 0.08 -2.07
        Clopidogrel 292 Antiplatelet drugs 1,469 0.20 0.32 0.06 -2.03
        Fluticasone propionate (Inhalation) 8 Corticosteroids (respiratory) 537 0.01 0.17 0.08 -2.01