Prescribing of continuous glucose monitoring sensors

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 Prescribing of continuous glucose monitoring sensors per 1000 patients
Why it matters Continuous glucose monitoring devices (CGM) can significantly reduce the need for people with diabetes to conduct finger-prick testing.

NICE guidance for Type 1 diabetes in adults, Type 2 diabetes in adults and Type 1 and Type 2 diabetes in children and young people were all updated in March 2022. The updates include recommendations that all patients with type 1 diabetes should be offered a choice of real-time continuous glucose monitoring (rtCGM) or intermittently scanned continuous glucose monitoring (isCGM) and that adults with type 2 diabetes on multiple daily insulin injections should be offered GM where they meet specific clinical criteria.

Tags Standard, Diabetes
Implies cost savings No
Authored by richard.croker
History View change history on GitHub →

Numerator SQL

     CAST(month AS DATE) AS month,
     practice AS practice_id,
     SUM(p.quantity) AS numerator
 FROM hscic.normalised_prescribing p -- joins prescribing data to subquery below, filtering list to BNF codes created in subquery 
 INNER JOIN -- joins the prescribing data table to the subquery thereby filtering the prescribing data to only these codes 
 (SELECT bnf_code FROM dmd.vmp WHERE id = 34865511000001109 -- selects bnf_codes from vmp table matching VMP id 
 UNION DISTINCT -- joins vmp and amp tables together 
 SELECT bnf_code FROM dmd.amp WHERE vmp = 34865511000001109 AND bnf_code IS NOT NULL) bnf -- selects bnf_codes from amp table matching VMP id where they exist 
 ON p.bnf_code = bnf.bnf_code
 GROUP BY month, practice_id

Denominator SQL

     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