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 |  |
Clotrimazole 100mg pessaries : 2 Canesten 2% thrush cream : 2 Clotrimazole 200mg pessaries : 1 Fluconazole 150mg capsule and Clotrimazole 2% cream : 1 Clotrimazole 500mg pessaries : 7 Clotrimazole 500mg pessary and Clotrimazole 2% cream : 21 Clotrimazole 2% cream : 11 Clotrimazole 10% cream and Clotrimazole 2% cream : 5 | ||||||||
| 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 |  |