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 |
---|---|---|---|---|---|---|---|---|
Dolutegravir | 1 | HIV infection | 2 | 0.50 | 0.01 | 0.06 | 8.78 | |
Ibuprofen lysine | 20 | Non-steroidal anti-inflammatory drugs | 4142 | 0.00 | 0.00 | 0.00 | 6.13 | |
Insulin glulisine | 372 | Short-acting insulins | 1477 | 0.25 | 0.03 | 0.04 | 5.43 | |
Emtricitabine and tenofovir alafenamide | 1 | HIV infection | 2 | 0.50 | 0.02 | 0.10 | 4.62 | |
Almotriptan | 85 | Treatment of acute migraine | 1281 | 0.07 | 0.01 | 0.01 | 3.96 | |
BNF Chemical | Chemical Items | BNF Subparagraph | Subparagraph Items | Ratio | Mean | std | Z_Score | Plots |
---|---|---|---|---|---|---|---|---|
Insulin aspart | 772 | Short-acting insulins | 1477 | 0.52 | 0.79 | 0.09 | -3.09 | |
Insulin aspart 100units/ml inj 3ml pf dispos dev : 1 NovoRapid 100units/ml solution for injection 10ml vials : 94 NovoRapid Penfill 100units/ml inj 3ml cartridges : 154 NovoRapid FlexPen 100units/ml inj 3ml pre-filled pens : 414 NovoRapid FlexTouch 100units/ml inj 3ml pre-filled pens : 16 NovoRapid PumpCart 100units/ml inj 1.6ml cartridges : 11 Fiasp FlexTouch 100units/ml inj 3ml pre-filled pens : 45 Fiasp Penfill 100units/ml inj 3ml cartridges : 14 Fiasp 100units/ml solution for injection 10ml vials : 23 | ||||||||
Ketoconazole | 135 | Shampoos and some other scalp preparations | 466 | 0.29 | 0.50 | 0.08 | -2.53 | |
Carbimazole | 213 | Antithyroid drugs | 258 | 0.83 | 0.93 | 0.04 | -2.39 | |
Mupirocin | 6 | Antibacterial preparations only used topically | 32 | 0.19 | 0.67 | 0.23 | -2.09 | |
Ivermectin | 24 | Topical preparation for rosacea | 36 | 0.67 | 0.88 | 0.12 | -1.81 | |