Imperial College Healthcare NHS Trust

Government Agency (Health and Adult Social Care)

Neil Hill

Unknown

No

NIBDAPC_2022_0010

Diabetes is a common disease which affects up to 20% of patients in hospital. High blood glucose levels (hyperglycaemia) is common in patients with diabetes. Despite being preventable, patients still suffer from severe hyperglycaemia whilst in hospital. If left untreated, hyperglycaemia can cause an increased risk of other serious clinical complications such as infection, can lead to patients staying longer in hospital, and can also increase a patient’s risk of death. Therefore, further research is needed to support clinicians in better managing hyperglycaemia in hospitalised patients with diabetes. This research will look to make use of routinely collected data from Imperial College Healthcare NHS Trust’s (ICHT) electronic health record EHR, Cerner, to predict characteristcs of patients who are at greater risk of severe hyperglycaemia. This model may then be used in practice to inform clinicians whether a patient is at greater risk of severe hyperglycaemia and support clinicians in implementing preventative clinical interventions to avoid patients developing severe hyperglycaemia in hospital.

It is estimated that 4.8 million people in the UK have diabetes, and this figure is predicted to continue to increase in parallel with the UK’s aging population (Diabetes UK, 2020). As such, diabetes is one of the most prevalent chronic diseases and, along with its related risk factors and comorbidities, places huge strains on the current healthcare landscape. The importance of improving outcomes for patients with diabetes in hospital settings is fundamental to relieving pressure on other areas of the healthcare system and enabling a more sustainable healthcare system. One in ten acute hospital beds are occupied by patients with diabetes (NDA, 2019). High blood glucose levels (hyperglycaemia) commonly occurs in people with diabetes. Diabetic ketoacidosis (DKA) and hyperglycaemic hyperosmolar state (HHS) are complications of hyperglycaemia that a particular concern for inpatients with diabetes. Poorly managed hyperglycaemia in hospital settings is associated with increased risk of complications (both in hospital as well as post discharge ), longer length of stay, and mortality (Dhatariya et al., 2020, Pasquel et al., 2021, Pratiwi et al., 2021, Umpierrez et al., 2002). Whilst some areas of inpatient diabetes management have improved since the first National Diabetes Audit in 2010, the management of hyperglycaemia and its related complications remains unchanged. Although preventable, 1 in 25 inpatients with Type 1 diabetes developed DKA in 2019 (NDA, 2019). Therefore, inpatient management of hyperglycaemia continues to present a significant area of concern for patient outcomes and the wider healthcare landscape. Furthermore, the NHS Long Term Plan places digital development at the heart of measures to improve health and care, and to deliver services more sustainably (NHS, 2019). A key aspect of this requires the use of healthcare data to generate evidence that enables transformation and improvement of services. A ‘learning health system’ (LHS) continuously analyses data collected as part of routine care, to monitor outcomes, identify improvements in care, and implement changes on the basis of evidence (Foley and Fairmichael, 2015, Foley et al., 2021). This research will use data to support clinical monitoring, and encourage earlier intervention of hospitalised patients with diabetes, and is therefore closely aligned with LHS principles. Furthermore, the output of this research will present an opportunity to implement a LHS into practice and, in doing so, directly addresses aims and objectives stipulated within the NHS Long Term Plan.

Public Health Research

06/04/2022

11/02/2022

De-Personalised

Not applicable

Not applicable

One-off

06/04/2022

TRE