Identifying interhospital variation in hyperosmolar hyperglycemic syndrome (hyperosmolar hyperglycemic state (HHS)) care: development and outcomes of the Digital Evaluation of Ketosis and Other Diabetes Emergencies (DEKODE) HHS model
Authors' conclusion
The DEKODE-HHS model represents the first UK multicenter surveillance initiative for HHS. It identifies variation in practice and outcome predictors while highlighting systemic barriers to guideline adherence. This model provides a scalable framework for continuous quality improvement in HHS management and may inform future updates to national guidance.
Study context
- Population
- Adults meeting Joint British Diabetes Societies criteria for HHS, 12 NHS hospitals, 2021–2024
- Participants
- 218 HHS episodes
- Outcome
- HHS episode characteristics and outcomes
Methodological detailsmulticentre, surveillance system, stakeholder interviews (thematic analysis), RE-AIM framework
- Multicentre
- Surveillance system
- Stakeholder interviews (thematic analysis)
- RE-AIM framework
Main finding
As reported in the abstract
Median age
77 years
T2D
84.4%
Median hospital stay
10.3 days
Mortality rate
16.1%
Observational data: associations, not effects.
Further findings
Implementation of DEKODE-HHS model
- Feasibility, high user engagement and potential for integration into routine quality improvement
- Barriers to adoption incl. diagnostic misclassification and resource constraints; educational impact and system usability once adopted
Original publication
Identifying interhospital variation in hyperosmolar hyperglycemic syndrome (HHS) care: development and outcomes of the DEKODE HHS model. BMJ Open Diabetes Res Care. Published 7 December 2025. doi:10.
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