Establishment Of The Singhealth Diabetes Registry

CLINICAL EPIDEMIOLOGY(2021)

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Abstract
Purpose: To describe the inception and structure of the SingHealth Diabetes Registry (SDR) as well as the methodology used to set up the registry. The SDR was established to facilitate systematic and standardized data collection for diabetes mellitus within Singapore Health Services (SingHealth), which is an Academic Medical Center (AMC) and Singapore's largest group of healthcare institutions. The diabetes casemix and outcome variables within the registry cohort are also provided.Materials and Methods: The SDR is built from SingHealth's electronic medical records (EMR) and clinical databases. It covers all individuals aged 18 and above with diabetes mellitus, excluding those with pre-diabetes. Cases are annually ascertained using criteria that include diagnosis codes, prescription records and laboratory test records. Data collection of casemix and outcome variables for the period 2013 to 2019 is complete.Results: The SDR stands at 208,102 ascertained individuals, distributed across 8 healthcare sites within the AMC. The cohort is broadly reflective of the local gender and ethnic compositions but has a high proportion of older individuals with a mean age of 65.8 +/- 13.7 years. Majority (>99%) have type 2 diabetes mellitus, with multiple other comorbidities (hypertension 84.1%, hyperlipidemia 86.2%, established cardiovascular disease 34.1%). At present, majority of individuals are able to meet key process indicators and 52.7% have a mean HbAlc of <7% (53 mmol/mol). Areas of potential improvement include increasing eye and foot screening rates, as well as glycemic control for the 19.5% of individuals with mean HbA1c >8% (64 mmol/mol).Conclusion: The SDR is a large-scale, comprehensive, and representative diabetes registry that incorporates EMR data across the primary and hospital-based care continuum, in a major AMC in Singapore. The SDR has identified areas of improvement in diabetes processes and outcomes. It will support future quality assessment and improvements in diabetes care.
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Key words
diabetes mellitus, electronic data processing, epidemiology
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