Static outliers for Whitley 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 Whitley PCN is higher than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Human papillomavirus (Type 6,11,16,18)	2	Vaccines and antisera	22	0.09	0.00	0.0	21.59
Gardasil vacc inj 0.5ml pre-filled syringes : 2
Azilsartan medoxomil	13	Angiotensin-II receptor antagonists	4229	0.00	0.00	0.0	16.92
Azilsartan medoxomil 40mg tablets : 6 Azilsartan medoxomil 80mg tablets : 7
Bambuterol hydrochloride	48	Selective beta(2)-agonists	6975	0.01	0.00	0.0	12.06
Bambuterol 10mg tablets : 48
Tolfenamic acid	21	Treatment of acute migraine	625	0.03	0.00	0.0	10.46
Tolfenamic acid 200mg tablets : 21
Fenofibrate	871	Lipid-regulating drugs	19641	0.04	0.01	0.0	8.34
Fenofibrate micronised 200mg capsules : 257 Fenofibrate micronised 67mg capsules : 44 Fenofibrate micronised 267mg capsules : 196 Fenofibrate micronised 160mg tablets : 314 Supralip 160mg tablets : 60

Prescribing where Whitley PCN is lower than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Vitamin A	0	Vitamin A	2	0.00	0.83	0.30	-2.74

Clopidogrel	1319	Antiplatelet drugs	6191	0.21	0.32	0.04	-2.57
Clopidogrel 75mg tablets : 1309 Clopidogrel 75mg/5ml oral solution : 4 Clopidogrel 75mg/5ml oral suspension : 6
Carbimazole	112	Antithyroid drugs	136	0.82	0.93	0.04	-2.44
Carbimazole 5mg tablets : 85 Carbimazole 20mg tablets : 18 Carbimazole 10mg tablets : 5 Carbimazole 15mg tablets : 4
Rifampicin	0	Antituberculosis drugs	1	0.00	0.74	0.35	-2.12

Letrozole	23	Breast cancer	331	0.07	0.43	0.18	-2.03
Letrozole 2.5mg tablets : 23