Static outliers for Greensands

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 Greensands is higher than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Low protein cooking aids	2	Foods for special diets	102	0.02	0.00	0.00	5.48
Loprofin low protein egg replacer : 1 Loprofin low protein egg white replacer : 1
Other eczema preparations	2	Preparations for eczema	2	1.00	0.06	0.22	4.19
Elena's Night Cream Extra : 1 Elena's Illumination cream : 1
Compound alginates and proprietary indigestion preparations	5	Compound Alginates and proprietary indigestion preparations	228	0.02	0.00	0.00	4.17
Rennie Peppermint chewable tablets : 5
Low protein grains/flours	2	Foods for special diets	102	0.02	0.00	0.00	4.11
Loprofin low protein rice : 2
Low protein pasta	8	Foods for special diets	102	0.08	0.00	0.02	3.84
Loprofin low protein pasta penne : 2 Loprofin low protein pasta long cut spaghetti : 2 Loprofin low protein pasta fusilli : 2 Loprofin low protein pasta lasagne : 1 Loprofin low protein pasta macaroni elbows : 1

Prescribing where Greensands is lower than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Gamolenic acid	0	Preparations for eczema	2	0.00	0.90	0.30	-3.03

Atropine sulfate	0	Mydriatics and cycloplegics	2	0.00	0.72	0.38	-1.91

Ramipril	1685	Angiotensin-converting enzyme inhibitors	4521	0.37	0.69	0.17	-1.90
Ramipril 1.25mg capsules : 221 Ramipril 2.5mg capsules : 556 Ramipril 5mg capsules : 417 Ramipril 10mg capsules : 446 Ramipril 5mg tablets : 9 Ramipril 1.25mg tablets : 4 Ramipril 2.5mg tablets : 21 Ramipril 10mg tablets : 11
Folic acid	713	Drugs used in megaloblastic anaemias	1679	0.42	0.70	0.16	-1.72
Folic acid 5mg tablets : 703 Folic acid 400microgram tablets : 10
Naftidrofuryl oxalate	0	Peripheral vasodilators and related drugs	3	0.00	0.66	0.39	-1.69