Skip to main content

Prototype Prescribing Outlier Dashboard for I J Healthcare

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 Practices. From this we can calculate the “z-score”, which is a measure of how many standard deviations a given Practice 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 Practice's chemical:subparagraph ratios is provided, with this Practice'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 I J Healthcare is higher than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Ephedrine hydrochloride 1 Topical nasal decongestants 1 1.00 0.01 0.04 22.74
Tryptophan 9 Other antidepressant drugs 1,722 0.01 0.00 0.00 14.80
Solifenacin/tamsulosin 80 Drugs for urinary retention 467 0.17 0.01 0.01 11.30
Dicycloverine hydrochloride 63 Antispasmodic and other drugs altering gut motility 515 0.12 0.01 0.01 8.92
Acarbose 36 Other antidiabetic drugs 832 0.04 0.00 0.00 8.67
Dexamethasone 62 Use of corticosteroids 318 0.19 0.03 0.02 7.46
Aspirin 36 Non-opioid analgesics and compound preparations 1,746 0.02 0.00 0.00 7.43
Loprazolam mesilate 24 Hypnotics 545 0.04 0.00 0.01 6.48
Oestrogens conjugated with progestogen 9 Oestrogens and Hormone Replacement Therapy 68 0.13 0.01 0.02 5.95
Fluvoxamine maleate 33 Selective serotonin re-uptake inhibitors 2,867 0.01 0.00 0.00 5.92

Prescribing where I J Healthcare is lower than most

BNF Chemical Chemical Items BNF Subparagraph Subparagraph Items Ratio Mean std Z_Score Plots
Nitrofurantoin 191 Urinary-tract infections 266 0.72 0.96 0.06 -4.16
Tamsulosin hydrochloride 325 Drugs for urinary retention 467 0.70 0.92 0.06 -3.77
Permethrin 0 Parasiticidal preparations 4 0.00 0.83 0.24 -3.46
    Trimethoprim 40 Sulfonamides and trimethoprim 76 0.53 0.87 0.12 -2.82
    Finasteride 121 Male sex hormones and antagonists 223 0.54 0.82 0.11 -2.43
    Co-amilofruse (Amiloride hydrochloride/frusemide) 0 Potassium sparing diuretics and compounds 6 0.00 0.69 0.33 -2.10
      Ramipril 1,073 Angiotensin-converting enzyme inhibitors 3,054 0.35 0.69 0.17 -2.07
      Hypromellose 34 Tear deficiency, eye lubricant/astringent 245 0.14 0.45 0.15 -2.05
      Dexamethasone 1 Corticosteroids 29 0.03 0.49 0.22 -2.03
      Moxonidine 0 Centrally-acting antihypertensive drugs 52 0.00 0.65 0.33 -1.95