TY  - JOUR
AU  - Patel, Dipen
AU  - Msosa, Yamiko Joseph
AU  - Wang, Tao
AU  - Williams, Julie
AU  - Mustafa, Omar G
AU  - Gee, Siobhan
AU  - Arroyo, Barbara
AU  - Larkin, Damian
AU  - Tiedt, Trevor
AU  - Roberts, Angus
AU  - Dobson, Richard J B
AU  - Gaughran, Fiona
PY  - 2024
DA  - 2024/4/5
TI  - Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial
JO  - JMIR Res Protoc
SP  - e49548
VL  - 13
KW  - blood sugar
KW  - CDSS
KW  - clinical decision support system
KW  - decision support
KW  - diabetes
KW  - diabetic
KW  - dysglycemia
KW  - electronic clinical decision support
KW  - hyperglycemia
KW  - hypoglycemia
KW  - implementation
KW  - medical informatics
KW  - mental health
KW  - mental healthcare
KW  - mental illness
KW  - metabolic health
KW  - randomized controlled trial
KW  - RCT
AB  - Background: Severe mental illnesses (SMIs), including schizophrenia, bipolar affective disorder, and major depressive disorder, are associated with an increased risk of physical health comorbidities and premature mortality from conditions including cardiovascular disease and diabetes. Digital technologies such as electronic clinical decision support systems (eCDSSs) could play a crucial role in improving the clinician-led management of conditions such as dysglycemia (deranged blood sugar levels) and associated conditions such as diabetes in people with a diagnosis of SMI in mental health settings. Objective: We have developed a real-time eCDSS using CogStack, an information retrieval and extraction platform, to automatically alert clinicians with National Health Service Trust–approved, guideline-based recommendations for dysglycemia monitoring and management in secondary mental health care. This novel system aims to improve the management of dysglycemia and associated conditions, such as diabetes, in SMI. This protocol describes a pilot study to explore the acceptability, feasibility, and evaluation of its implementation in a mental health inpatient setting. Methods: This will be a pilot hybrid type 3 effectiveness-implementation randomized controlled cluster trial in inpatient mental health wards. A ward will be the unit of recruitment, where it will be randomly allocated to receive either access to the eCDSS plus usual care or usual care alone over a 4-month period. We will measure implementation outcomes, including the feasibility and acceptability of the eCDSS to clinicians, as primary outcomes, alongside secondary outcomes relating to the process of care measures such as dysglycemia screening rates. An evaluation of other implementation outcomes relating to the eCDSS will be conducted, identifying facilitators and barriers based on established implementation science frameworks. Results: Enrollment of wards began in April 2022, after which clinical staff were recruited to take part in surveys and interviews. The intervention period of the trial began in February 2023, and subsequent data collection was completed in August 2023. Data are currently being analyzed, and results are expected to be available in June 2024. Conclusions: An eCDSS can have the potential to improve clinician-led management of dysglycemia in inpatient mental health settings. If found to be feasible and acceptable, then, in combination with the results of the implementation evaluation, the system can be refined and improved to support future successful implementation. A larger and more definitive effectiveness trial should then be conducted to assess its impact on clinical outcomes and to inform scalability and application to other conditions in wider mental health care settings. Trial Registration: ClinicalTrials.gov NCT04792268; https://clinicaltrials.gov/study/NCT04792268 International Registered Report Identifier (IRRID): DERR1-10.2196/49548 
SN  - 1929-0748
UR  - https://www.researchprotocols.org/2024/1/e49548
UR  - https://doi.org/10.2196/49548
UR  - http://www.ncbi.nlm.nih.gov/pubmed/38578666
DO  - 10.2196/49548
ID  - info:doi/10.2196/49548
ER  -