Static outliers for Lawns 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 Lawns Practice is higher than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Gluten free/low protein drink	1	Foods for special diets	26	0.04	0.00	0.00	26.79
Mevalia Lattis low protein drink : 1
Carvedilol	453	Beta-adrenoceptor blocking drugs	2547	0.18	0.01	0.01	13.40
Carvedilol 12.5mg tablets : 133 Carvedilol 25mg tablets : 269 Carvedilol 6.25mg tablets : 30 Carvedilol 3.125mg tablets : 21
Azithromycin	3	Antibacterials	35	0.09	0.00	0.01	9.27
Azithromycin 15mg/g eye dps 0.25g ud preservative free : 3
Glipizide	64	Sulfonylureas	468	0.14	0.00	0.01	9.26
Glipizide 5mg tablets : 64
Dronabinol/cannabidiol	5	Skeletal muscle relaxants	63	0.08	0.00	0.01	8.98
Sativex oromucosal spray : 5

Prescribing where Lawns Practice is lower than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Ivermectin	0	Topical preparation for rosacea	1	0.00	0.88	0.24	-3.72

Cabergoline	0	Bromocriptine and other dopaminergic drugs	5	0.00	0.86	0.27	-3.16

Ramipril	951	Angiotensin-converting enzyme inhibitors	3555	0.27	0.69	0.17	-2.54
Ramipril 1.25mg capsules : 47 Ramipril 2.5mg capsules : 248 Ramipril 5mg capsules : 293 Ramipril 10mg capsules : 260 Ramipril 2.5mg tablets : 67 Ramipril 10mg tablets : 26 Ramipril 5mg tablets : 10
Sertraline hydrochloride	704	Selective serotonin re-uptake inhibitors	2939	0.24	0.45	0.09	-2.43
Sertraline 50mg tablets : 399 Sertraline 100mg tablets : 301 Sertraline 25mg tablets : 4
Dexamethasone	16	Otitis externa	33	0.48	0.78	0.13	-2.25
Otomize ear spray : 16