Using electronic health records to quantify and stratify the severity of type 2 diabetes in primary care in England: rationale and cohort study design

Zghebi, Salwa S.; Rutter, Martin K.; Ashcroft, Darren M.; Salisbury, Chris; Mallen, Christian; Chew-Graham, Carolyn A.; Reeves, David; Van marwijk, Harm; Qureshi, Nadeem; Weng, Stephen; Peek, Niels; Planner, Claire

Abstract

Introduction: The increasing prevalence of type 2 diabetes (T2DM) presents a significant burden on affected individuals and health-care systems internationally. There is, however, no agreed validated measure to infer diabetes severity from electronic health records (EHRs). We aim to quantify T2DM severity and validate it using clinical adverse outcomes.
Methods and Analysis: Primary care data from the Clinical Practice Research Datalink (CPRD), linked hospitalisation and mortality records between April-2007 and March-2017 for T2DM patients in England will be used to develop a clinical algorithm to grade T2DM severity. The EHR-based algorithm will incorporate main risk factors (severity domains) for adverse outcomes to stratify T2DM cohorts by baseline and longitudinal severity scores. Provisionally, T2DM severity domains, identified through a systematic review and expert opinion are: diabetes duration, HbA1c, microvascular complications, comorbidities, and co-prescribed treatments. Severity scores will be developed by two approaches: i) calculating a count score of severity domains; ii) through hierarchical stratification of complications. Regression models estimates will be used to calculate domains weights. Survival analysis for the association between weighted severity scores and future outcomes: cardiovascular events; hospitalisation (diabetes-related, cardiovascular); and mortality (diabetes-related, cardiovascular, all-cause mortality) will be performed as a statistical validation. The proposed EHR-based approach will quantify the T2DM severity for primary care performance management and inform the methodology for measuring severity of other primary care-managed chronic conditions. We anticipate that the developed algorithm will be a practical tool for practitioners, aid clinical management decision-making, inform stratified medicine, support future clinical trials and contribute to more effective service-planning and policy-making.
Ethics and Dissemination: The study protocol was approved by the Independent Scientific Advisory Committee (ISAC). Some data were presented at the NIHR SPCR Showcase, September-2017, Oxford,UK; the Diabetes UK Professional Conference March-2018, London,UK. The study findings will be disseminated in relevant academic conferences and peer-reviewed journals.

Citation

Zghebi, S. S., Rutter, M. K., Ashcroft, D. M., Salisbury, C., Mallen, C., Chew-Graham, C. A., Reeves, D., Van marwijk, H., Qureshi, N., Weng, S., Peek, N., & Planner, C. (2018). Using electronic health records to quantify and stratify the severity of type 2 diabetes in primary care in England: rationale and cohort study design. BMJ Open, 8(6), Article e020926

• Journal Article Type: Article
• Acceptance Date: May 9, 2018
• Publication Date: Jun 30, 2018
• Deposit Date: May 16, 2018
• Publicly Available Date: Jun 30, 2018
• Journal: BMJ Open
• Electronic ISSN: 2044-6055
• Publisher: BMJ Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 6
• Article Number: e020926
• Keywords: Electronic health records; Type 2 Diabetes; Primary Care
• Public URL: https://nottingham-repository.worktribe.com/output/944392
• Publisher URL: https://bmjopen.bmj.com/content/8/6/e020926
• Contract Date: May 16, 2018