Care delivery in youth with type 2 diabetes - are we meeting clinical practice guidelines?

BACKGROUND: Studies indicate high rates of treatment failure and early onset diabetes-related complications in youth-onset type 2 diabetes (T2D). We aim to describe the quality of care provided to children and youth with T2D. METHODS: This prospective cohort study used administrative datasets to describe individuals aged 10-24 yr diagnosed with T2D at <20 yr of age (488 individuals; 2111 person-years). The primary outcome was being 'at goal' for adherence to Canadian clinical practice guidelines (CPGs). This was defined as having either optimal [three diabetes-related physician visits/year, three hemoglobin A1C (A1C) tests/year, and all recommended screening tests for complications (i.e., retinopathy, nephropathy)] or good (two diabetes-related physician visits/year, two A1C tests/year, and at least two screening tests) adherence to CPGs. Descriptive statistics and logistic regression modeling were used. RESULTS: Sixty eight percentage person-years had poor adherence to CPGs (<2 physician visits and A1c tests/year and no screening tests). Only 29% and 25% were at goal for adherence in the 15-19 and 20-24 yr age groups, respectively. There was a 52% decreased odds of being at goal for adherence 4 yr after diagnosis of T2D (p < 0.001). For every year increase in age at diagnosis, there was a 5% decreased odds of being at goal (p = 0.04). CONCLUSIONS: Youth with T2D are not receiving high quality care, and older youth and young adults are particularly at risk. Future research is needed to understand the effectiveness of care in the context of poor adherence as well as patient, physician, and health system factors that might improve adherence.

Adherence to clinical practice guidelines in the management of children, youth, and young adults with type 1 diabetes--a prospective population cohort study.

OBJECTIVE: To describe adherence to clinical practice guidelines for the treatment of childhood type 1 diabetes and identify associated patient and system level factors. STUDY DESIGN: This prospective cohort study used population-based administrative data to describe individuals aged 1-24 years who had been diagnosed with type 1 diabetes at <20 years of age (1472 unique individuals and 5883 person-years over a 7-year period) living in British Columbia, Canada. The outcome measure was proportion 'at goal,' which was defined as having optimal adherence (3 diabetes-related physician visits/year, 3 hemoglobin A1c (HbA1c) tests/year, 1 glucagon prescription dispensed/year, and appropriate screening for diabetes-related comorbidity [ie, hypothyroidism] and complications [ie, retinopathy and nephropathy]), or good adherence to guidelines (2 diabetes-related physician visits/year, 2 HbA1c tests/year, and appropriate screening for diabetes-related comorbidity and complications). Statistical methods included descriptive statistics and logistic regression modeling. RESULTS: Fifty-four percent person-years had poor adherence to guidelines (<2 diabetes-related physician visits and HbA1c tests/year) and 7.4% had optimal adherence. The proportion of person-years at goal was higher in females vs males (41.0% vs 37.6%; P = .007). Individuals 4-years post-diagnosis of diabetes were 78% less likely to be at goal compared with the year of diagnosis (P < .0001). CONCLUSIONS: The treatment of pediatric type 1 diabetes likely does not meet national and international standards. Future studies should explore facilitators and barriers to adherence to guidelines among health care providers, patients, and families, and whether adherence to guidelines is associated with glycemic control.

Validation of classification algorithms for childhood diabetes identified from administrative data.

OBJECTIVE: Type 1 diabetes is the most common form of diabetes among children; however, the proportion of cases of childhood type 2 diabetes is increasing. In Canada, the National Diabetes Surveillance System (NDSS) uses administrative health data to describe trends in the epidemiology of diabetes, but does not specify diabetes type. The objective of this study was to validate algorithms to classify diabetes type in children <20 yr identified using the NDSS methodology. PATIENTS AND METHODS: We applied the NDSS case definition to children living in British Columbia between 1 April 1996 and 31 March 2007. Through an iterative process, four potential classification algorithms were developed based on demographic characteristics and drug-utilization patterns. Each algorithm was then validated against a gold standard clinical database. RESULTS: Algorithms based primarily on an age rule (i.e., age <10 at diagnosis categorized type 1 diabetes) were most sensitive in the identification of type 1 diabetes; algorithms with restrictions on drug utilization (i.e., no prescriptions for insulin ± glucose monitoring strips categorized type 2 diabetes) were most sensitive for identifying type 2 diabetes. One algorithm was identified as having the optimal balance of sensitivity (Sn) and specificity (Sp) for the identification of both type 1 (Sn: 98.6%; Sp: 78.2%; PPV: 97.8%) and type 2 diabetes (Sn: 83.2%; Sp: 97.5%; PPV: 73.7%). CONCLUSIONS: Demographic characteristics in combination with drug-utilization patterns can be used to differentiate diabetes type among cases of pediatric diabetes identified within administrative health databases. Validation of similar algorithms in other regions is warranted.