Static outliers for Silverdale 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 Silverdale Medical Practice is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Griseofulvin 4 Other antifungals 20 0.20 0.01 0.03 5.62
Felbinac 5 Rubefacients, topical NSAIDS, capsaicin and poultice 1065 0.00 0.00 0.00 4.43
Benzydamine hydrochloride 5 Rubefacients, topical NSAIDS, capsaicin and poultice 1065 0.00 0.00 0.00 4.14
Fusidic acid 39 Antibacterials 90 0.43 0.09 0.09 3.80
Isophane insulin 201 Intermediate and long-acting insulins 399 0.50 0.12 0.10 3.71

Prescribing where Silverdale Medical Practice is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Terbinafine hydrochloride 16 Other antifungals 20 0.80 0.99 0.03 -5.62
Chloramphenicol 46 Antibacterials 90 0.51 0.78 0.13 -2.08
Beclometasone dipropionate 757 Corticosteroids (respiratory) 2309 0.33 0.57 0.12 -2.03
Qvar 50 inhaler : 36
Qvar 100 inhaler : 109
Easyhaler Beclometasone 200micrograms/dose dry pdr inhaler : 31
Clenil Modulite 50micrograms/dose inhaler : 61
Clenil Modulite 100micrograms/dose inhaler : 154
Fostair 100micrograms/dose / 6micrograms/dose inhaler : 146
Fostair 200micrograms/dose / 6micrograms/dose inhaler : 70
Fostair NEXThaler 200microg/dose / 6microg/dose dry pdr inh : 37
Beclometasone 100micrograms/dose inhaler CFC free : 2
Beclometasone 200microg/Formoterol 6microg/dose inh CFC free : 14
Clenil Modulite 200micrograms/dose inhaler : 22
Fostair NEXThaler 100microg/dose / 6microg/dose dry pdr inh : 22
Qvar 100micrograms/dose Easi-Breathe inhaler : 17
Qvar 100 Autohaler : 11
Beclometasone 100microg/Formoterol 6microg/dose inh CFCfree : 20
Beclometasone 200microg/Formoterol 6microg/dose dry pdr inh : 5
Losartan potassium 476 Angiotensin-II receptor antagonists 2586 0.18 0.50 0.19 -1.70
Budesonide 2 Corticosteroids 12 0.17 0.70 0.34 -1.58