Static outliers for Chilwell Valley And Meadows 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 Chilwell Valley And Meadows Practice is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Triptorelin embonate 17 Prostate cancer and gonadorelin analogues 29 0.59 0.02 0.07 7.53
Calcium acetate/magnesium carbonate 5 Phosphate binding agents 7 0.71 0.05 0.18 3.66
Estradiol and nomegestrol 3 Combined hormonal contraceptives 355 0.01 0.00 0.00 3.35
Acrivastine 19 Antihistamines 872 0.02 0.00 0.01 3.29
Timolol and travoprost 86 Treatment of glaucoma 886 0.10 0.02 0.02 3.09

Prescribing where Chilwell Valley And Meadows Practice is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Glucose blood testing reagents 645 Diabetic diagnostic and monitoring agents 734 0.88 0.95 0.03 -1.96
Carbomer 940/980 15 Tear deficiency, eye lubricant/astringent 248 0.06 0.34 0.15 -1.88
Ciprofloxacin 36 Quinolones 57 0.63 0.86 0.15 -1.53
Moxonidine 3 Centrally-acting antihypertensive drugs 21 0.14 0.64 0.34 -1.49
Aspirin 1244 Antiplatelet drugs 2205 0.56 0.65 0.06 -1.46