Static outliers for Isca 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 Isca Medical Practice is higher than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Azithromycin	2	Antibacterials	20	0.10	0.00	0.01	10.85
Azyter 15mg/g eye drops 0.25g unit dose : 2
Lercanidipine hydrochloride	1142	Calcium-channel blockers	2180	0.52	0.06	0.07	6.39
Lercanidipine 10mg tablets : 496 Lercanidipine 20mg tablets : 634 Zanidip 20mg tablets : 12
Ciprofloxain/dexameth	8	Otitis externa	25	0.32	0.05	0.06	4.33
Ciprofloxacin 0.3% / Dexamethasone 0.1% ear drops : 8
Indacaterol/glycopyrronium	113	Compound bronchodilator preparations	118	0.96	0.16	0.20	3.91
Ultibro Breezhaler 85microg/43microg pdr caps with dev : 108 Indacaterol 85microg/Glycopyrronium brom 54microg/dose : 5
Soluble insulin (Neutral insulin)	8	Short-acting insulins	78	0.10	0.01	0.02	3.89
Humulin S 100units/ml solution for injection 3ml cartridges : 8

Prescribing where Isca Medical Practice is lower than most

BNF Chemical	Chemical Items	BNF Subparagraph	Subparagraph Items	Ratio	Mean	std	Z_Score
Amlodipine	926	Calcium-channel blockers	2180	0.42	0.75	0.11	-2.91
Amlodipine 5mg tablets : 475 Amlodipine 10mg tablets : 451
Dexamethasone	11	Otitis externa	25	0.44	0.78	0.13	-2.59
Otomize ear spray : 11
Nicorandil	0	Other antianginal drugs	14	0.00	0.51	0.20	-2.49

Co-codamol (Codeine phosphate/paracetamol)	117	Non-opioid analgesics and compound preparations	1078	0.11	0.45	0.15	-2.23
Co-codamol 8mg/500mg tablets : 28 Co-codamol 8mg/500mg capsules : 9 Co-codamol 30mg/500mg tablets : 23 Co-codamol 30mg/500mg capsules : 16 Co-codamol 15mg/500mg capsules : 25 Tylex 30mg/500mg capsules : 6 Co-codamol 15mg/500mg tablets : 10
Alfentanil hydrochloride	0	Opioid analgesics	2	0.00	0.82	0.37	-2.21