RESUMO
Identifying patients at high risk for diabetic ketoacidosis (DKA) is crucial for informing efforts at preventive intervention. This study sought to develop and validate an electronic medical record (EMR)-based tool for predicting DKA risk in pediatric patients with type 1 diabetes. Based on analysis of data from 1,864 patients with type 1 diabetes, three factors emerged as significant predictors of DKA: most recent A1C, type of health insurance (public vs. private), and prior DKA. A prediction model was developed based on these factors and tested to identify and categorize patients at low, moderate, and high risk for experiencing DKA within the next year. This work demonstrates that risk for DKA can be predicted using a simple model that can be automatically derived from variables in the EMR.
RESUMO
Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes a project at Texas Children's Hospital aimed at improving identification of patients with type 1 diabetes at high risk for diabetic ketoacidosis.
RESUMO
Introduction: While type 1 diabetes is frequently encountered clinically in pediatric endocrinology fellowship training, other types of diabetes may only be encountered in educational settings. Adult learners learn best through knowledge application, but to date there are no published curricula utilizing application educational strategies for all forms of diabetes. Methods: We utilized a team-based learning (TBL) approach to create four modules on different types of diabetes: type 1 diabetes, type 2 diabetes, neonatal diabetes, and maturity-onset diabetes of the young. We divided our fellows (all training years, n = 11) into two teams and delivered four separate, 90-minute sessions. To emphasize the application of knowledge, we modified the format to combine the readiness assurance test (RAT) with application problem (APP) questions. The combined RAT/APP questions were answered by individuals and teams. We analyzed scores from individual and team tests and evaluated each module. Additionally, we acquired subjective data from the fellows regarding their experiences. Results: Teams outperformed individuals on the tests, as expected (94% vs. 76% correct questions, respectively). All the fellows agreed that the sessions should be included permanently. Additionally, all agreed the sessions helped them apply knowledge. Subjectively, the fellows were very engaged and lively during the sessions and felt the sessions were feasible as implemented. Discussion: TBL can be a valuable educational strategy to increase the application of knowledge for diabetes in pediatric endocrinology fellows. Future studies examining the use of this strategy to increase critical thinking skills and knowledge retention in the long-term would be useful.
