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 → |
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", "0501120P0BBAAAA", "0501120P0BBACAB", "0501120Q0AAAAAA", "0501120Q0BBAAAA", "0501120X0AAAAAA", "0501120X0AAABAB", "0501120Y0AAAAAA", "0501120Y0BBAAAA")
GROUP BY month, practice_idSELECT
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