1
|
Patel D, Msosa YJ, Wang T, Williams J, Mustafa OG, Gee S, Arroyo B, Larkin D, Tiedt T, Roberts A, Dobson RJB, Gaughran F. 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. JMIR Res Protoc 2024; 13:e49548. [PMID: 38578666 PMCID: PMC11031689 DOI: 10.2196/49548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 11/03/2023] [Accepted: 12/17/2023] [Indexed: 04/06/2024] Open
Abstract
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.
Collapse
Affiliation(s)
- Dipen Patel
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Yamiko Joseph Msosa
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Tao Wang
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Julie Williams
- Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, United Kingdom
| | - Omar G Mustafa
- Department of Diabetes, King's College Hospital National Health Service Foundation Trust, London, United Kingdom
- Centre for Education, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Siobhan Gee
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Barbara Arroyo
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Damian Larkin
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Trevor Tiedt
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Angus Roberts
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Richard J B Dobson
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Institute for Health Informatics, University College London, London, United Kingdom
- Health Data Research UK, University College London, London, United Kingdom
| | - Fiona Gaughran
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
- South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| |
Collapse
|