Electronic Clinical Decision Support for Diabetes and Dysglycaemia in Secondary Mental Healthcare

Summary

People with serious mental illness (SMI) such as schizophrenia, schizoaffective disorder and bipolar affective disorder have a significantly reduced life expectancy, caused in part by increased incidences of mortality from physical health conditions such as cardiovascular disease (CVD) and diabetes.

Electronic clinical decision support systems (eCDSS) offer clinicians patient-specific advice and recommendations based on clinical guidelines, theoretically overcoming obstacles in the use of existing paper-based guidelines. Adoption of eCDSS to address CVD risk in people with SMI presents a unique opportunity for research, but requires evidence of acceptability and feasibility before scaling up of research.

The key objective of this study is to establish the feasibility and acceptability of an eCDSS (CogStack @ Maudsley) compromising a real-time electronic health record powered alerting and clinical decision support system for diabetes management in secondary inpatient mental healthcare settings. End-users of the eCDSS will be clinicians only.

Firstly we will conduct initial surveys and interviews with clinicians on inpatient wards to scope experiences of managing diabetes in secondary mental healthcare settings and attitudes towards use of digital technologies to aid in clinical decision making.

A feasibility study will then be run to evaluate the acceptability and feasibility of implementing eCDSS on inpatient wards. This will involve a cluster RCT on inpatient general adult psychiatry wards, where 4 months of eCDSS use by clinicians on intervention wards will be compared to 4 months of treatment as usual on control wards. All clinicians on recruited wards will be eligible to participate.

At the end of the study, participating clinicians on intervention wards will be invited to take part in a survey and interview which will explore their experiences and attitudes towards using the eCDSS, and an implementation science framework will be applied to inform future implementation of eCDSS. Group level pseudonymised outcome data will be gathered through a separate study.

Conditions

• Severe Mental Disorder
• Diabetes Mellitus
• Dysglycemia
• Staff Attitude

Interventions

OTHER

Access to eCDSS on wards

Electronic clinical decision support (eCDSS) will be available to clinicians on wards recruited to this arm. An eCDSS is a health information technology system designed to assist clinicians and other health care professionals in clinical decision-making. The key digital tool to be used for eCDSS in this study is CogStack. This eCDSS has been developed to alert clinicians automatically regarding patients admitted under their care, triggered by the presence of new, old or absent HbA1c pathology reports on the electronic health record (EHR).

Sponsors & Collaborators

• National Institute for Health Research, United Kingdom

  collaborator OTHER_GOV

• South London and Maudsley NHS Foundation Trust

  collaborator OTHER

• King's College London

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

OTHER

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

80 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2022-05-01

Primary Completion

2023-08-01

Completion

2023-12-01

Countries

• United Kingdom

Study Locations