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Prototype Prescribing Outlier Dashboard for Blackdown Practice

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 Blackdown Practice is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Dipyridamole and aspirin 8 Antiplatelet drugs 3,886 0.00 0.00 0.00 83.83
Orphenadrine hydrochloride 7 Antimuscarinic drugs used in parkinsonism 15 0.47 0.01 0.03 14.42
Methenamine hippurate 229 Urinary-tract infections 530 0.43 0.04 0.06 6.68
Brivaracetam 45 Control of epilepsy 2,037 0.02 0.00 0.00 5.35
Perampanel 41 Control of epilepsy 2,037 0.02 0.00 0.00 4.96
Ins degludec/liraglutide 14 Other antidiabetic drugs 543 0.03 0.00 0.00 4.92
Clemastine fumarate 2 Antihistamines 1,243 0.00 0.00 0.00 3.94
Isophane insulin 246 Intermediate and long-acting insulins 476 0.52 0.12 0.10 3.88
Terazosin hydrochloride 21 Alpha-adrenoceptor blocking drugs 396 0.05 0.01 0.01 3.50
Loratadine 418 Antihistamines 1,243 0.34 0.12 0.06 3.43

Prescribing where Blackdown Practice is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Nitrofurantoin 301 Urinary-tract infections 530 0.57 0.96 0.06 -6.68
Medroxyprogesterone acetate 24 Parenteral progestogen-only contraceptives 52 0.46 0.88 0.15 -2.74
Cefalexin 32 Cephalosporins 45 0.71 0.96 0.10 -2.61
Glycopyrronium bromide 0 Antimuscarinic drugs 13 0.00 0.82 0.35 -2.34
    Mercaptopurine 0 Antimetabolites 13 0.00 0.80 0.35 -2.32
      Doxazosin mesilate 375 Alpha-adrenoceptor blocking drugs 396 0.95 0.99 0.02 -2.27
      Glucose 4 Treatment of hypoglycaemia 11 0.36 0.75 0.20 -1.95
      Methylprednisolone acetate 0 Local corticosteroid injections 35 0.00 0.74 0.39 -1.89
        Naftidrofuryl oxalate 0 Peripheral vasodilators and related drugs 1 0.00 0.67 0.39 -1.73
          Tramadol hydrochloride 228 Opioid analgesics 1,962 0.12 0.27 0.09 -1.67