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Clinic variation in glycaemic control for children with Type 1 diabetes in England and Wales: a population‐based, multilevel analysis
Author(s) -
Charalampopoulos D.,
Amin R.,
Warner J. T.,
MunizTerrera G.,
Mazarello Paes V.,
Viner R. M.,
Stephenson T.
Publication year - 2017
Publication title -
diabetic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.474
H-Index - 145
eISSN - 1464-5491
pISSN - 0742-3071
DOI - 10.1111/dme.13442
Subject(s) - medicine , type 2 diabetes , multilevel model , variation (astronomy) , population , diabetes mellitus , demography , pediatrics , gerontology , environmental health , endocrinology , statistics , sociology , physics , mathematics , astrophysics
Abstract Aim To understand the scope for improving children's glycaemic outcomes by reducing variation between clinics and examine the role of insulin regimen and clinic characteristics. Methods Cross‐sectional analysis of 2012–2013 National Paediatric Diabetes Audit data from 21 773 children aged < 19 years with Type 1 diabetes cared for at 176 clinics organized into 11 regional diabetes networks in England and Wales. Variation in HbA 1c was explored by multilevel models with a random effect for clinic. The impact of clinic context was quantified by computing the per cent of total variation in HbA 1c which occurs between clinics (intraclass correlation coefficient; ICC ). Results Overall, 69 of the 176 diabetes clinics (39%) had a glycaemic performance that differed significantly from the national average after adjusting for patient case‐mix with respect to age, gender, diabetes duration, deprivation and ethnicity. However, differences between clinics accounted for 4.7% of the total variation in HbA 1c . Inclusion of within‐clinic HbA 1c standard deviation led to a substantial reduction in ICC to 2.4%. Insulin regimen, clinic volume and diabetes networks had a small or moderate impact on ICC . Conclusions Differences between diabetes clinics accounted for only a small portion of the total variation in glycaemic control because most of the variation was within clinics. This implies that national glycaemic improvements might best be achieved not only by targeting poor centres but also by shifting the whole distribution of clinics to higher levels of quality.