Static outliers for Grantham And Rural PCN

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 Grantham And Rural PCN is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Insulin human 3 Short-acting insulins 1466 0.00 0.00 0.00 5.38
Paliperidone 25 Antipsychotic drugs 4898 0.01 0.00 0.00 5.30
Ethambutol hydrochloride 2 Antituberculosis drugs 2 1.00 0.07 0.18 5.22
Botulinum toxin type A 1 Essential tremor,chorea,tics and related disorders 18 0.06 0.00 0.01 4.99
Cimetidine 163 H2-Receptor antagonists 490 0.33 0.07 0.06 4.62

Prescribing where Grantham And Rural PCN is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Calcium carbonate 100 Calcium supplements 129 0.78 0.96 0.05 -3.74
Salbutamol 10298 Selective beta(2)-agonists 12559 0.82 0.90 0.03 -2.61
Salbutamol 100micrograms/dose inhaler CFC free : 8276
Salbutamol 200micrograms/dose dry powder inhaler : 6
Salbutamol 2.5mg/2.5ml nebuliser liquid unit dose vials : 142
Salbutamol 5mg/ml nebuliser liquid : 3
Salbutamol 5mg/2.5ml nebuliser liquid unit dose vials : 69
Salbutamol 2mg/5ml oral solution sugar free : 6
Salbutamol 100micrograms/dose breath actuated inh CFC free : 311
Salbutamol 100micrograms/dose dry powder inhaler : 3
Ventolin 200micrograms/dose Accuhaler : 102
Ventolin 100micrograms/dose Evohaler : 734
Ventolin 2.5mg Nebules : 7
Ventolin 5mg Nebules : 2
Salamol 100micrograms/dose inhaler CFC free (Teva) : 239
Salamol 100micrograms/dose Easi-Breathe inhaler : 116
Airomir 100micrograms/dose inhaler : 3
Airomir 100micrograms/dose Autohaler : 5
Easyhaler Salbutamol sulfate 100micrograms/dose dry pdr inh : 255
Easyhaler Salbutamol sulfate 200micrograms/dose dry pdr inh : 19
Famotidine 247 H2-Receptor antagonists 490 0.50 0.80 0.12 -2.38
Rifampicin 0 Antituberculosis drugs 2 0.00 0.74 0.35 -2.12
Nicotine 17 Nicotine dependence 160 0.11 0.57 0.25 -1.87