Literature DB >> 28730750

Improving type 2 diabetes mellitus glycaemic outcomes is possible without spending more on medication: Lessons from the UK National Diabetes Audit.

Adrian H Heald1,2, Mark Livingston3, Nagaraj Malipatil1, Michal Becher4, Joyce Craig5, Mike Stedman6, Anthony A Fryer7,8.   

Abstract

AIMS: To determine the factors at general practice level that relate to glycaemic control outcomes in people with type 2 diabetes (T2DM).
METHODS: Data were accessed from 4050 general practices (50% of total) covering 1.6 million patients with T2DM in the UK National Diabetes Audit 2013 to 2014 and 2014 to 2015. This audit reported characteristics, services and outcomes in the T2DM population, including percentage of patients who had total glycaemic control (TGC), defined as glycated haemoglobin (HbA1c) ≤7.5% (58 mmol/mol), and the percentage who were at higher glycaemic risk (HGR), defined as HbA1c >10% (86 mmol/mol); the respective figures were 67.2% and 6.2%. The medication data were examined in terms of annual defined daily doses (DDDs). Multivariate linear regression analysis was used to identify associations between DDD and patient and practice characteristics.
RESULTS: Over the period 2012/2013 to 2015/2016, patient numbers grew 4% annually and annual medication expenditure by 8%, but glycaemic control outcomes did not improve. The main findings were that practices with better outcomes: had a higher percentage of patients aged >65 years; provided more effective diabetes services (including case identification, care checks, patient education, percentage of patients with blood pressure and cholesterol under control and more patients with type 1 diabetes achieving target HbA1c levels); spent less overall on prescribing per patient with T2DM; and on average, prescribed fewer sulphonylureas, less insulin (for patients with T2DM), fewer glucagon-like peptide-1 agonists, more metformin, more dipeptidyl peptidase-4 inhibitors, and more blood glucose monitoring strips. Ethnicity and social disadvantage and levels of thiazolidinedione (glitazone) prescribing had no significant impact on outcomes. Sodium-glucose co-transporter-2 inhibitor use was too low for an effect to be observed in the period examined.
CONCLUSIONS: If all practices brought their service and medication to the level of the top decile practices, they could achieve 74.7% compared with the median of 67.3% of patients achieving TGC, showing an increase of 213 000 in patients achieving TGC, while reducing the number at HGR to 3.8% compared with 6.1%, benefiting 62 000 patients. This could have a major impact on the overall consequent healthcare costs of managing diabetes complications with their attendant mortality risks.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  HbA1c; big data; diabetes; outcome; prescribing; primary care

Mesh:

Substances:

Year:  2017        PMID: 28730750     DOI: 10.1111/dom.13067

Source DB:  PubMed          Journal:  Diabetes Obes Metab        ISSN: 1462-8902            Impact factor:   6.577


  13 in total

1.  Long-term conditions and the National Diabetes Audit.

Authors:  Adrian Heald; Mike Stedman; Sanam Farman; Anthony Fryer; Sue Bailey; Roger Gadsby
Journal:  Br J Gen Pract       Date:  2018-07       Impact factor: 5.386

2.  Impact of a Clinical Pharmacist Intervention Program on the Follow-up of Type-2 Diabetic Patients.

Authors:  Abdel-Hameed I Ebid; Mohamed A Mobarez; Ramadan A Ramadan; Mohamed A Mahmoud
Journal:  Hosp Pharm       Date:  2020-11-25

3.  Time trends and geographical variation in prescribing of drugs for diabetes in England from 1998 to 2017.

Authors:  Helen J Curtis; John M Dennis; Beverley M Shields; Alex J Walker; Seb Bacon; Andrew T Hattersley; Angus G Jones; Ben Goldacre
Journal:  Diabetes Obes Metab       Date:  2018-06-05       Impact factor: 6.577

4.  Time trends in prescribing of type 2 diabetes drugs, glycaemic response and risk factors: A retrospective analysis of primary care data, 2010-2017.

Authors:  John M Dennis; William E Henley; Andrew P McGovern; Andrew J Farmer; Naveed Sattar; Rury R Holman; Ewan R Pearson; Andrew T Hattersley; Beverley M Shields; Angus G Jones
Journal:  Diabetes Obes Metab       Date:  2019-04-04       Impact factor: 6.577

5.  Impact of a Community Pharmacist-Delivered Information Program on the Follow-up of Type-2 Diabetic Patients: A Cluster Randomized Controlled Study.

Authors:  Yves Michiels; Olivier Bugnon; Annie Chicoye; Sylvie Dejager; Christine Moisan; François-André Allaert; Catherine Hunault; Laura Romengas; Hubert Méchin; Bruno Vergès
Journal:  Adv Ther       Date:  2019-05-02       Impact factor: 3.845

6.  The experience of blood glucose monitoring in people with type 2 diabetes mellitus (T2DM).

Authors:  Mike Stedman; Rustam Rea; Christopher J Duff; Mark Livingston; Katie McLoughlin; Louise Wong; Stephen Brown; Katherine Grady; Roger Gadsby; John M Gibson; Angela Paisley; Anthony A Fryer; Adrian H Heald
Journal:  Endocrinol Diabetes Metab       Date:  2021-12-17

7.  Disparities in glycaemic control, monitoring, and treatment of type 2 diabetes in England: A retrospective cohort analysis.

Authors:  Martin B Whyte; William Hinton; Andrew McGovern; Jeremy van Vlymen; Filipa Ferreira; Silvio Calderara; Julie Mount; Neil Munro; Simon de Lusignan
Journal:  PLoS Med       Date:  2019-10-07       Impact factor: 11.069

8.  Analysis of English general practice level data linking medication levels, service activity and demography to levels of glycaemic control being achieved in type 2 diabetes to improve clinical practice and patient outcomes.

Authors:  Adrian Heald; Mark Davies; Mike Stedman; Mark Livingston; Mark Lunt; Anthony Fryer; Roger Gadsby
Journal:  BMJ Open       Date:  2019-09-06       Impact factor: 2.692

9.  Cost of hospital treatment of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) compared to the non-diabetes population: a detailed economic evaluation.

Authors:  Mike Stedman; Mark Lunt; Mark Davies; Mark Livingston; Christopher Duff; Anthony Fryer; Simon George Anderson; Roger Gadsby; Martin Gibson; Gerry Rayman; Adrian Heald
Journal:  BMJ Open       Date:  2020-05-05       Impact factor: 2.692

10.  Data quality predicts care quality: findings from a national clinical audit.

Authors:  Mark Yates; Katie Bechman; Elaine M Dennison; Alexander J MacGregor; Jo Ledingham; Sam Norton; James B Galloway
Journal:  Arthritis Res Ther       Date:  2020-04-17       Impact factor: 5.156

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