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The objective of this scoping review was to survey the literature on the use of AI/ML applications in analyzing inpatient EHR data to identify bundles of care (groupings of interventions). If evidence suggested AI/ML models could determine bundles, the review aimed to explore whether implementing these interventions as bundles reduced practice pattern variance and positively impacted patient care outcomes for inpatients with T2DM. Six databases were searched for articles published from January 1, 2000, to January 1, 2024. Nine studies met criteria and were summarized by aims, outcome measures, clinical or practice implications, AI/ML model types, study variables, and AI/ML model outcomes. A variety of AI/ML models were used. Multiple data sources were leveraged to train the models, resulting in varying impacts on practice patterns and outcomes. Studies included aims across 4 thematic areas to address: therapeutic patterns of care, analysis of treatment pathways and their constraints, dashboard development for clinical decision support, and medication optimization and prescription pattern mining. Multiple disparate data sources (i.e., prescription payment data) were leveraged outside of those traditionally available within EHR databases. Notably missing was the use of holistic multidisciplinary data (i.e., nursing and ancillary) to train AI/ML models. AI/ML can assist in identifying the appropriateness of specific interventions to manage diabetic care and support adherence to efficacious treatment pathways if the appropriate data are incorporated into AI/ML design. Additional data sources beyond the EHR are needed to provide more complete data to develop AI/ML models that effectively discern meaningful clinical patterns. Further study is needed to better address nursing care using AI/ML to support effective inpatient diabetes management.
The prevalence of gestational diabetes mellitus (GDM) is rising in the UK and is associated with maternal and neonatal complications. National Institute for Health and Care Excellence guidance advises first-line management with healthy eating and physical activity which is only moderately effective for achieving glycaemic targets. Approximately 30% of women require medication with metformin and/or insulin. There is currently no strong evidence base for any particular dietary regimen to improve outcomes in GDM. Intermittent low-energy diets (ILEDs) are associated with improved glycaemic control and reduced insulin resistance in type 2 diabetes and could be a viable option in the management of GDM. This study aims to test the safety, feasibility and acceptability of an ILED intervention among women with GDM compared with best National Health Service (NHS) care.
We aim to recruit 48 women with GDM diagnosed between 24 and 30 weeks gestation from antenatal clinics at Wythenshawe and St Mary’s hospitals, Manchester Foundation Trust, over 13 months starting in November 2022. Participants will be randomised (1:1) to ILED (2 low-energy diet days/week of 1000 kcal and 5 days/week of the best NHS care healthy diet and physical activity advice) or best NHS care 7 days/week until delivery of their baby. Primary outcomes include uptake and retention of participants to the trial and adherence to both dietary interventions. Safety outcomes will include birth weight, gestational age at delivery, neonatal hypoglycaemic episodes requiring intervention, neonatal hyperbilirubinaemia, admission to special care baby unit or neonatal intensive care unit, stillbirths, the percentage of women with hypoglycaemic episodes requiring third-party assistance, and significant maternal ketonaemia (defined as ≥1.0 mmol/L). Secondary outcomes will assess the fidelity of delivery of the interventions, and qualitative analysis of participant and healthcare professionals’ experiences of the diet. Exploratory outcomes include the number of women requiring metformin and/or insulin.
Ethical approval has been granted by the Cambridge East Research Ethics Committee (22/EE/0119). Findings will be disseminated via publication in peer-reviewed journals, conference presentations and shared with diabetes charitable bodies and organisations in the UK, such as Diabetes UK and the Association of British Clinical Diabetologists.
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