Antibiotic stewardship: co-amoxiclav, cephalosporins & quinolones prescribing volume

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 Number of prescription items for co-amoxiclav, cephalosporins and quinolones per 1000 patients
Why it matters Co-amoxiclav, cephalosporins and quinolones are broad spectrum antibiotics that can be used when others have failed. However they should only be used where narrow spectrum antibiotics are not likely to be effective, as they can increase the risk of Clostridioides difficile, MRSA and other drug-resistant bacteria developing.

We are no longer using STAR-PUs in this measure. Read more about why we have to decided to do this on our blog.
Tags Antimicrobial Stewardship, Standard, Infections, NICE
Implies cost savings No
Authored by christopher.wood
Checked by richard.croker
Last reviewed 2024-08-05
Next review due 2026-08-05
History View change history on GitHub →

Numerator SQL

SELECT
     CAST(month AS DATE) AS month,
     practice AS practice_id,
     SUM(items) AS numerator
 FROM hscic.normalised_prescribing
 WHERE bnf_code IN ("0501013K0AAAAAA", "0501013K0AAABAB", "0501013K0AAADAD", "0501013K0AAAGAG", "0501013K0AAAHAH", "0501013K0AAAIAI", "0501013K0AAAJAJ", "0501013K0AAAKAK", "0501013K0AAANAN", "0501013K0BBAAAA", "0501013K0BBAJAD", "0501013K0BBAKAG", "0501013K0BBALAJ", "0501013K0BBAMAK", "0501021A0AAAAAA", "0501021A0AAABAB", "0501021A0AAACAC", "0501021A0AAAEAE", "0501021A0AAAGAG", "0501021A0AAAJAJ", "0501021A0AAAKAK", "0501021A0BBABAB", "0501021A0BBACAC", "0501021A0BBADAE", "0501021A0BBAEAG", "0501021B0AAAAAA", "0501021B0AAACAC", "0501021C0AAAAAA", "0501021C0AAACAC", "0501021C0BBAAAA", "0501021K0AAAAAA", "0501021K0AAABAB", "0501021K0AAACAC", "0501021K0BBAAAA", "0501021K0BBABAB", "0501021K0BBACAC", "0501021L0AAAAAA", "0501021L0AAABAB", "0501021L0AAACAC", "0501021L0AAADAD", "0501021L0AAAEAE", "0501021L0AAAGAG", "0501021L0AAAHAH", "0501021L0AAANAN", "0501021L0AAAPAP", "0501021L0BCAAAA", "0501021L0BCABAB", "0501021L0BCACAG", "0501021L0BCADAH", "0501021L0BCAEAC", "0501021L0BCAFAD", "0501021M0AAAAAA", "0501021M0AAABAB", "0501021M0BCAAAA", "0501021M0BCABAB", "0501120L0AAAAAA", "0501120L0AAAFAF", "0501120L0AAAGAG", "0501120L0AAAJAJ", "0501120L0AAAUAU", "0501120L0AABGBG", "0501120L0BBAAAA", "0501120L0BBABAF", "0501120L0BBADAJ", "0501120L0BBAJBG", "0501120P0AAAAAA", "0501120P0AAABAB", "0501120P0BBACAB", "0501120Q0AAAAAA", "0501120Q0BBAAAA", "0501120X0AAAAAA", "0501120X0AAABAB", "0501120Y0AAAAAA", "0501120Y0BBAAAA")
 GROUP BY month, practice_id

Denominator SQL

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
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