Targets and teamwork: Understanding differences in pediatric diabetes centers treatment outcomes

OBJECTIVE

The reason for center differences in metabolic control of childhood diabetes is still unknown. We sought to determine to what extent the targets, expectations, and goals that diabetes care professionals have for their patients is a determinant of center differences in metabolic outcomes.

RESEARCH DESIGN AND METHODS

Children, under the age of 11 with type 1 diabetes and their parents treated at the study centers participated. Clinical, medical, and demographic data were obtained, along with blood sample for centralized assay. Parents and all members of the diabetes care team completed questionnaires on treatment targets for hemoglobin A1c (HbA1c) and recommended frequency of blood glucose monitoring.

RESULTS

Totally 1113 (53% male) children (mean age 8.0 ± 2.1 years) from 18 centers in 17 countries, along with parents and 113 health-care professionals, participated. There were substantial differences in mean HbA1c between centers ranging from 7.3 ± 0.8% (53 mmol/mol ± 8.7) to 8.9 ± 1.1% (74 mmol/mol ± 12.0). Centers with lower mean HbA1c had (1) parents who reported lower targets for their children, (2) health-care professionals that reported lower targets and more frequent testing, and (3) teams with less disagreement about recommended targets. Multiple regression analysis indicated that teams reporting higher HbA1c targets and more target disagreement had parents reporting higher treatment targets. This seemed to partially account for center differences in Hb1Ac.

CONCLUSIONS

The diabetes care teams' cohesiveness and perspectives on treatment targets, expectations, and recommendations have an influence on parental targets, contributing to the differences in pediatric diabetes center outcomes.

Core Standards of the EUBIROD Project. Defining a European Diabetes Data Dictionary for Clinical Audit and Healthcare Delivery

BACKGROUND

A set of core diabetes indicators were identified in a clinical review of current evidence for the EUBIROD project. In order to allow accurate comparisons of diabetes indicators, a standardised currency for data storage and aggregation was required. We aimed to define a robust European data dictionary with appropriate clinical definitions that can be used to analyse diabetes outcomes and provide the foundation for data collection from existing electronic health records for diabetes.

METHODS

Existing clinical datasets used by 15 partner institutions across Europe were collated and common data items analysed for consistency in terms of recording, data definition and units of measurement. Where necessary, data mappings and algorithms were specified in order to allow partners to meet the standard definitions. A series of descriptive elements were created to document metadata for each data item, including recording, consistency, completeness and quality.

RESULTS

While datasets varied in terms of consistency, it was possible to create a common standard that could be used by all. The minimum dataset defined 53 data items that were classified according to their feasibility and validity. Mappings and standardised definitions were used to create an electronic directory for diabetes care, providing the foundation for the EUBIROD data analysis repository, also used to implement the diabetes registry and model of care for Cyprus.

CONCLUSIONS

The development of data dictionaries and standards can be used to improve the quality and comparability of health information. A data dictionary has been developed to be compatible with other existing data sources for diabetes, within and beyond Europe.