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Prototype Prescribing Outlier Dashboard for NHS Kernow CCG

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. These pilot results are provided for the interest of advanced users, although we don't know how relevant they are in 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.

The DataLab is keen to hear your feedback on the results. You can do this by completing the following survey or emailing us at [email protected]. Please DO NOT INCLUDE IDENTIFIABLE PATIENT information in your feedback. All feedback is helpful, you can send short or detailed feedback.

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, the count of all prescriptions within that chemical's BNF subparagraph, for prescriptions dispensed between June 2021 and December 2021. We then calculate the ratio of these counts along with the mean and standard deviation of those ratios across all CCGs. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given CCG is from the population mean. We then rank your “z-scores” to find the top 10 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.

For each outlier chemical, a kernel density estimation plot of all CCG's chemical:subparagraph ratios is provided, with this CCG's ratio overlaid in red.

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, to inform research on this topic. Our full analytical method code is openly available on GitHub here.

This is a new, experimental feature. We'd love to .

Prescribing where NHS Kernow CCG is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Prilocaine hydrochloride 109 Local anaesthetics 10,741 0.01 0.00 0.00 10.12
Sodium lactate 4 Electrolytes and water 1,892 0.00 0.00 0.00 9.98
Trimetazidine hydrochloride 159 Calcium-channel blockers 308,527 0.00 0.00 0.00 9.05
Glibenclamide 9 Sulfonylureas 32,421 0.00 0.00 0.00 6.43
Estradiol and nomegestrol 143 Combined hormonal contraceptives 23,475 0.01 0.00 0.00 6.12
Tolcapone 30 Dopaminergic drugs used in parkinsonism 32,355 0.00 0.00 0.00 5.20
Beclometasone dipropionate (Systemic) 362 Corticosteroids 1,449 0.25 0.03 0.05 4.82
INR blood testing reagents 754 Oral anticoagulants 160,356 0.00 0.00 0.00 4.51
Benzalkonium chloride 2,122 Barrier preparations 6,792 0.31 0.06 0.06 4.35
Prazosin hydrochloride 522 Alpha-adrenoceptor blocking drugs 38,552 0.01 0.00 0.00 4.03

Prescribing where NHS Kernow CCG is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Doxazosin mesilate 37,521 Alpha-adrenoceptor blocking drugs 38,552 0.97 0.99 0.00 -3.57
Levothyroxine sodium 265,539 Thyroid hormones 266,809 1.00 1.00 0.00 -2.81
Budesonide 692 Corticosteroids 1,449 0.48 0.72 0.10 -2.37
Ferrous fumarate 9,934 Oral iron 43,987 0.23 0.56 0.16 -2.08
Ramipril 155,904 Angiotensin-converting enzyme inhibitors 351,136 0.44 0.69 0.12 -2.04
Tamoxifen citrate 2,152 Breast cancer 15,391 0.14 0.26 0.06 -1.97
Zinc oxide 918 Barrier preparations 6,792 0.14 0.45 0.16 -1.97
Valproic acid 1,405 Drugs used for mania and hypomania 9,089 0.15 0.42 0.14 -1.93
Gamolenic acid 2 Preparations for eczema 4 0.50 0.90 0.21 -1.91
Tacrolimus 631 Drugs affecting the immune response 970 0.65 0.80 0.08 -1.88