Below are the database queries which are used to create this measure. These are run against a copy of the BSA prescribing data which we store in Google BigQuery. We're working on making our BigQuery tables publicly available at which point it will be possible to run and modify these queries yourself. But even where code and database queries are not directly useable by others we believe it is always preferable to make them public.
|Description||Items prescribed for topical treatment of fungal nail infections per 1000 patients|
|Why it matters||These treatments have a low cure rate, and treatment is required for three to six months. Consideration should be given as to whether this is an effective treatment.|
|Tags||Standard, Efficacy, Infections|
|Implies cost savings||No|
|History||View change history on GitHub →|
SELECT CAST(month AS DATE) AS month, practice AS practice_id, SUM(items) AS numerator FROM hscic.normalised_prescribing WHERE bnf_code IN ("1310020A0AAAAAA", "1310020A0BBAAAA", "1310020A0BCAAAA", "1310020A0BDAAAA", "1310020A0BEAAAC", "1310020A0BFAAAA", "1310020A0BFAAAC", "1310020T0AAAAAA", "1310020T0BBAAAA") GROUP BY month, practice_id
SELECT CAST(month AS DATE) AS month, practice AS practice_id, SUM(total_list_size / 1000.0) AS denominator FROM hscic.practice_statistics GROUP BY month, practice_id