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.
BNF Chemical | Chemical Items | BNF Subparagraph | Subparagraph Items | Ratio | Mean | std | Z_Score | Plots |
---|---|---|---|---|---|---|---|---|
Dequalinium chloride | 2 | Vaginal and vulval infections | 60 | 0.03 | 0.00 | 0.01 | 5.74 | |
Xylometazoline hydrochloride | 7 | Topical nasal decongestants | 10 | 0.70 | 0.10 | 0.20 | 3.07 | |
Salmeterol | 112 | Selective beta(2)-agonists | 2612 | 0.04 | 0.01 | 0.01 | 2.88 | |
Combined ethinylestradiol 20mcg | 89 | Combined hormonal contraceptives | 293 | 0.30 | 0.12 | 0.07 | 2.75 | |
Bimatoprost | 250 | Treatment of glaucoma | 925 | 0.27 | 0.11 | 0.06 | 2.69 | |
BNF Chemical | Chemical Items | BNF Subparagraph | Subparagraph Items | Ratio | Mean | std | Z_Score | Plots |
---|---|---|---|---|---|---|---|---|
Emollient bath and shower preparations | 1 | Emollient bath and shower preparations | 7 | 0.14 | 0.61 | 0.21 | -2.21 | |
Lithium carbonate | 0 | Drugs used for mania and hypomania | 265 | 0.00 | 0.61 | 0.28 | -2.19 | |
Combined ethinylestradiol 30mcg | 198 | Combined hormonal contraceptives | 293 | 0.68 | 0.81 | 0.07 | -1.80 | |
Microgynon 30 tablets : 48 Levest 150/30 tablets (Morningside) : 49 Millinette 30microgram/75microgram tablets : 2 Ovranette 150microgram/30microgram tablets : 1 Femodene ED tablets : 1 Marvelon tablets : 9 Gedarel 30microgram/150microgram tablets : 18 Lucette 0.03mg/3mg tablets : 27 Femodene tablets : 8 Rigevidon tablets : 17 Microgynon 30 ED tablets : 6 Yasmin tablets : 6 Cimizt 30microgram/150microgram tablets : 6 | ||||||||
Dexamethasone | 7 | Corticosteroids | 53 | 0.13 | 0.50 | 0.23 | -1.61 | |
Ramipril | 1534 | Angiotensin-converting enzyme inhibitors | 3627 | 0.42 | 0.69 | 0.17 | -1.60 | |