DEKODE-A cloud-based performance feedback model improved DKA care across multiple hospitals in the UK.

Area of Science:

• Endocrinology
• Metabolic Disorders
• Healthcare Quality Improvement

Background:

• Diabetes-related ketoacidosis (DKA) care varies significantly across healthcare settings.
• There is a need for robust data collection systems to monitor DKA management and outcomes.
• Understanding factors influencing DKA care variations is crucial for improving patient outcomes.

Purpose of the Study:

• To establish a multi-centre data gathering system for DKA management.
• To identify trends in DKA complications and outcomes.
• To improve adherence to national guidelines for DKA care.

Main Methods:

• A cloud-based Quality Improvement Project (QIP) was implemented across 11 UK hospitals.
• Data on DKA episodes were collected between January 2020 and December 2022.
• Regular feedback on adherence and outcomes was provided to participating hospitals.

Main Results:

• Significant improvements in fluid prescription adherence were observed in five hospitals (p < 0.001).
• Notable increases in glucose monitoring adherence occurred in three hospitals (p < 0.001).
• While overall complications did not significantly change, quarterly fluctuations highlighted the impact of feedback.

Conclusions:

• A sustainable QIP can improve adherence to DKA care guidelines.
• The project serves as an early warning system for adverse trends in DKA management.
• This initiative advances data collection practices in acute diabetes care.