Static outliers for Excel Primary Care
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 Excel Primary Care is higher than most
| BNF Chemical | Chemical Items | BNF Subparagraph | Subparagraph Items | Ratio | Mean | std | Z_Score | Plots |
|---|---|---|---|---|---|---|---|---|
| Diclofenac sodium | 5 | Ocular diagnostic & peri-operative prepn & photodynamic tt | 5 | 1.00 | 0.03 | 0.13 | 7.71 |  |
| Dexamfetamine sulfate | 5 | CNS Stimulants and drugs used for ADHD | 10 | 0.50 | 0.03 | 0.07 | 7.16 |  |
| Low protein cereals | 10 | Foods for special diets | 241 | 0.04 | 0.00 | 0.01 | 5.37 |  |
| Rutosides | 8 | Peripheral vasodilators and related drugs | 8 | 1.00 | 0.06 | 0.19 | 4.94 |  |
| Lacidipine | 715 | Calcium-channel blockers | 5865 | 0.12 | 0.01 | 0.03 | 4.03 |  |
Prescribing where Excel Primary Care is lower than most
| BNF Chemical | Chemical Items | BNF Subparagraph | Subparagraph Items | Ratio | Mean | std | Z_Score | Plots |
|---|---|---|---|---|---|---|---|---|
| Methylphenidate hydrochloride | 0 | CNS Stimulants and drugs used for ADHD | 10 | 0.00 | 0.65 | 0.21 | -3.15 |  |
| Cetirizine hydrochloride | 90 | Antihistamines | 1088 | 0.08 | 0.28 | 0.11 | -1.86 |  |
| Paracetamol | 799 | Non-opioid analgesics and compound preparations | 4462 | 0.18 | 0.48 | 0.16 | -1.86 |  |
Paracetamol 500mg tablets : 678 Paracetamol 250mg/5ml oral suspension sugar free : 54 Paracetamol 120mg/5ml oral suspension paediatric sugar free : 2 Paracetamol 250mg/5ml oral suspension : 14 Paracetamol 500mg capsules : 23 Paracetamol 500mg effervescent tablets : 7 Paracetamol 500mg soluble tablets : 21 | ||||||||
| Naftidrofuryl oxalate | 0 | Peripheral vasodilators and related drugs | 8 | 0.00 | 0.66 | 0.39 | -1.69 |  |
| Tacrolimus | 0 | Corticosteroids and other immunosuppressants | 5 | 0.00 | 0.62 | 0.40 | -1.56 |  |