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Prototype Prescribing Outlier Dashboard for Guide Bridge Medical 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 Guide Bridge Medical Practice is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Orphenadrine hydrochloride 31 Antimuscarinic drugs used in parkinsonism 54 0.57 0.01 0.03 17.78
Ferric maltol 15 Oral iron 631 0.02 0.00 0.00 6.37
Promazine hydrochloride 155 Antipsychotic drugs 633 0.24 0.01 0.04 6.19
Zonisamide 70 Control of epilepsy 1,720 0.04 0.01 0.01 4.30
Bromfenac 1 Ocular diagnostic & peri-operative prepn & photodynamic tt 1 1.00 0.09 0.21 4.25
Semaglutide 258 Other antidiabetic drugs 1,010 0.26 0.05 0.05 4.00
Tars 16 Preparations for psoriasis 80 0.20 0.04 0.04 3.93
Propantheline bromide 30 Antispasmodic and other drugs altering gut motility 282 0.11 0.01 0.02 3.90
Demeclocycline hydrochloride 3 Tetracyclines 129 0.02 0.00 0.01 3.90
Opicapone 4 Dopaminergic drugs used in parkinsonism 59 0.07 0.01 0.02 3.65

Prescribing where Guide Bridge Medical Practice is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Spironolactone 47 Potassium-sparing diuretics and aldosterone antagonists 130 0.36 0.72 0.14 -2.61
Procyclidine hydrochloride 18 Antimuscarinic drugs used in parkinsonism 54 0.33 0.85 0.21 -2.48
Calcipotriol 54 Preparations for psoriasis 80 0.68 0.87 0.08 -2.44
Clarithromycin 28 Macrolides 153 0.18 0.57 0.16 -2.44
Folic acid 311 Drugs used in megaloblastic anaemias 956 0.33 0.69 0.16 -2.34
Budesonide 0 Corticosteroids 2 0.00 0.71 0.32 -2.21
    Methotrexate 21 Rheumatic disease suppressant drugs 82 0.26 0.58 0.15 -2.07
    Amiodarone hydrochloride 0 Drugs for arrhythmias 26 0.00 0.48 0.25 -1.89
      Finasteride 68 Male sex hormones and antagonists 112 0.61 0.82 0.11 -1.86
      Bendroflumethiazide 103 Thiazides and related diuretics 336 0.31 0.57 0.16 -1.67