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Prototype Prescribing Outlier Dashboard for NHS South East London CCG

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 CCGs. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given CCG 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 CCG's chemical:subparagraph ratios is provided, with this CCG'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 NHS South East London CCG is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Ziprasidone hydrochloride 4 Antipsychotic drugs 172,796 0.00 0.00 0.00 10.20
Caffeine citrate 15 CNS Stimulants and drugs used for ADHD 29,691 0.00 0.00 0.00 10.20
Mefloquine hydrochloride 54 Antimalarials 30,761 0.00 0.00 0.00 7.92
Proguanil hydrochloride with atovaquone 52 Antimalarials 30,761 0.00 0.00 0.00 5.42
Tioguanine 8 Antimetabolites 868 0.01 0.00 0.00 5.31
Bethanechol chloride 76 Drugs for urinary retention 95,213 0.00 0.00 0.00 5.18
Cefadroxil 67 Cephalosporins 7,764 0.01 0.00 0.00 5.16
Emulsifying wax 4,004 Emollients 67,452 0.06 0.01 0.01 4.87
Pentamidine isetionate 1 Drugs for pneumocystis pneumonia 1 1.00 0.05 0.21 4.53
Metformin hydrochloride/sitagliptin 7,055 Other antidiabetic drugs 206,449 0.03 0.01 0.01 4.13

Prescribing where NHS South East London CCG is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Atovaquone 0 Drugs for pneumocystis pneumonia 1 0.00 0.95 0.21 -4.53
    Potassium permanganate 128 Oxidisers and dyes 191 0.67 0.94 0.10 -2.70
    Aluminium chloride 709 Antiperspirants 745 0.95 0.99 0.02 -2.65
    Terbinafine hydrochloride 5,932 Other antifungals 6,061 0.98 0.99 0.01 -2.61
    Glucose 2,461 Treatment of hypoglycaemia 3,845 0.64 0.78 0.06 -2.52
    Morphine sulfate 29,887 Opioid analgesics 218,486 0.14 0.22 0.04 -2.30
    Prednisolone 61,039 Use of corticosteroids 71,325 0.86 0.89 0.02 -2.17
    Influenza 190,811 Vaccines and antisera 201,114 0.95 0.97 0.01 -1.98
    Theophylline 3,296 Theophylline 3,847 0.86 0.94 0.04 -1.92
    Colecalciferol 378,281 Vitamin D 397,332 0.95 0.97 0.01 -1.81