Identifying interhospital variation in hyperosmolar hyperglycemic syndrome (HHS) care: development and outcomes of the DEKODE HHS model.
Kew, Tania M Manta, Aspasia Sawlani, Jhanvi Pravesh Ling Jie Yee, Amanda Mann, Amar Narayanan, Lakshmi Armeni, Eleni Rayman, Gerry Dhatariya, Ketan Kempegowda, Punith
Kew, Tania M
Manta, Aspasia
Sawlani, Jhanvi Pravesh
Ling Jie Yee, Amanda
Mann, Amar
Narayanan, Lakshmi
Armeni, Eleni
Rayman, Gerry
Dhatariya, Ketan
Kempegowda, Punith
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Publication date
2025-12-07
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Abstract
INTRODUCTION: Hyperosmolar hyperglycemic state (HHS) is a life-threatening metabolic emergency with high mortality rate. Yet, there is no national system in the UK to monitor clinical practice or outcomes. To address this, we implemented and evaluated a multicenter surveillance system for HHS, assessing interhospital variations in management, outcomes, and barriers to guideline implementation.
RESEARCH DESIGN AND METHODS: This mixed-methods observational study was conducted across 12 NHS hospitals between 2021 and 2024. A standardized data collection tool was developed, capturing demographics, biochemistry, treatment, and outcomes of HHS care. Adults meeting the Joint British Diabetes Societies criteria for HHS were included. Quantitative analyses were conducted to investigate care variations compared with guidelines among centers and identify predictors of HHS outcomes. In parallel, stakeholder interviews were analyzed thematically to explore implementation experiences. The Reach, Effectiveness, Adoption, Implementation, Maintenance framework guided evaluation.
RESULTS: In our cohort, a total of 218 HHS episodes were included. Median patient age was 77 years; 84.4% had type 2 diabetes, with a high comorbidity burden. The median hospital stay was 10.3 days, and the mortality rate was 16.1%. Significant interhospital variation was observed in insulin dosing, glucose monitoring, and time to discharge. Multivariate analysis identified older age and elevated sodium as independent predictors of mortality. The Digital Evaluation of Ketosis and Other Diabetes Emergencies (DEKODE)-HHS model demonstrated feasibility, high user engagement, and potential for integration into routine quality improvement structures. Qualitative findings revealed barriers, including diagnostic misclassification and resource constraints, to the adoption of the DEKODE-HHS model. However, they also highlighted the educational impact and system usability once the model was adopted.
CONCLUSIONS: 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.
Citation
Kew TM, Manta A, Sawlani JP, Ling Jie Yee A, Mann A, Narayanan L, Armeni E, Rayman G, Dhatariya K, Kempegowda P; DEVI Collaboration. Identifying interhospital variation in hyperosmolar hyperglycemic syndrome (HHS) care: development and outcomes of the DEKODE HHS model. BMJ Open Diabetes Res Care. 2025 Dec 7;13(6):e005489. doi: 10.1136/bmjdrc-2025-005489.
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Article