Static outliers for Mythe Medical 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. 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 Mythe Medical Practice is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Combined mestranol 6 Combined hormonal contraceptives 277 0.02 0.00 0.00 32.90
Miconazole nitrate 24 Vaginal and vulval infections 83 0.29 0.01 0.04 7.64
Fidaxomicin 1 Some other antibacterials 11 0.09 0.00 0.01 6.95
Naldemedine 3 Peripheral opioid-receptor antagonists 3 1.00 0.03 0.14 6.74
Sodium clodronate 18 Bisphosphonates and other drugs 521 0.03 0.00 0.01 6.58

Prescribing where Mythe Medical Practice is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Naloxegol 0 Peripheral opioid-receptor antagonists 3 0.00 0.97 0.15 -6.30
Clotrimazole 50 Vaginal and vulval infections 83 0.60 0.90 0.10 -3.09
Procyclidine hydrochloride 6 Antimuscarinic drugs used in parkinsonism 19 0.32 0.84 0.21 -2.53
Mercaptopurine 0 Antimetabolites 6 0.00 0.80 0.35 -2.31
Salicylic acid 0 Preparations for warts and calluses 4 0.00 0.69 0.31 -2.20