Static outliers for Railway Medical Group

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. 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.

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 using the BNF subparagraph as a denominator, for prescriptions dispensed between April 2021 and August 2021. We then calculate the mean and standard deviation for each numerator and denominator pair across all practices/CCGs/PCNs/STPs. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given practice/CCG/PCN/STP is from the population mean. We then rank your “z-scores” to find the top 5 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.

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. Our full analytical method code is openly available on GitHub here.

The DataLab is keen to hear your feedback on the results. You can do this by completing the following survey or emailing us at ebmdatalab@phc.ox.ac.uk. Please DO NOT INCLUDE IDENTIFIABLE PATIENT information in your feedback. All feedback is helpful, you can send short or detailed feedback.

Prescribing where Railway Medical Group is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Phenylephrine hydrochloride 2 Mydriatics and cycloplegics 8 0.25 0.00 0.02 14.69
Biphasic isophane insulin 876 Intermediate and long-acting insulins 1494 0.59 0.13 0.11 4.09
Azelastine hydrochloride 81 Drugs used in nasal allergy 1411 0.06 0.01 0.01 4.07
Paliperidone 28 Antipsychotic drugs 4033 0.01 0.00 0.00 3.68
Lixisenatide 36 Other antidiabetic drugs 1487 0.02 0.00 0.01 3.60

Prescribing where Railway Medical Group is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Co-codamol (Codeine phosphate/paracetamol) 7 Non-opioid analgesics and compound preparations 3710 0.00 0.45 0.15 -2.92
Glycopyrronium bromide 0 Antimuscarinic drugs 8 0.00 0.82 0.36 -2.30
Zopiclone 281 Hypnotics 942 0.30 0.60 0.14 -2.18
Aspirin 4297 Antiplatelet drugs 8218 0.52 0.65 0.06 -2.14
Insulin glargine 117 Intermediate and long-acting insulins 1494 0.08 0.33 0.13 -1.90