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Accepted for/Published in: JMIR Diabetes

Date Submitted: Apr 28, 2020
Date Accepted: Oct 27, 2020

The final, peer-reviewed published version of this preprint can be found here:

Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study

Alhodaib HI, Antza C, Chandan JS, Hanif W, Sankar S, Paul S, Sutcliffe P, Nirantharakumar K

Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study

JMIR Diabetes 2020;5(4):e19650

DOI: 10.2196/19650

PMID: 33206055

PMCID: 7710444

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Design, Development and Evaluation of a Mobile-based Clinical Decision Support Application for the Management of Patients with Diabetes and Kidney Disease: A feasibility Study

  • Hala Ibrahim Alhodaib; 
  • Christina Antza; 
  • Joht Singh Chandan; 
  • Wasim Hanif; 
  • Sailesh Sankar; 
  • Sunjay Paul; 
  • Paul Sutcliffe; 
  • Krishnarajah Nirantharakumar

ABSTRACT

Background:

Attempts to utilise eHealth in diabetes mellitus (DM) management have shown promising outcomes mostly targeted at patients, however few have been designed for healthcare providers.

Objective:

The purpose of this study was to describe a feasibility project developing and evaluating a mobile clinical decision support (CDSS) tool for the management of chronic kidney disease (CKD) in patients with DM exclusively for health care providers.

Methods:

The design process is based on the three key stages of the User-Centred Design (UCD) framework. Firstly, an exploratory qualitative study collected the experiences and views of diabetic specialist nurses (DSNs) regarding the use of mobile apps in clinical practice. Secondly, a CDSS tool was developed for the management of patients with DM and CKD. Finally, a randomized controlled trial examined the acceptability and impact of the tool.

Results:

DSNs were not currently using eHealth solutions in their clinical practice, while most nurses were not even aware of the existing medical applications. However, they appreciated the potential benefits that applications may bring to their clinical practice. Taking into consideration the needs and preferences of end-users, a new mobile CDSS application, the ‘Diabetes & CKD’, was developed based on guidelines. The evaluation of this application showed that there was no significant difference between the application and the paper-based version of the application’s algorithm [mean=7.24, SD=2.46 for intervention group, mean=7.39, SD=2.56 for control group; t (37) = -0.19, P=.85 (maximum score is 13)]. However, 82.4% of the participants were satisfied with using the application.

Conclusions:

The findings will guide the design of future CDSS applications in the management of DM, aiming to help healthcare providers with a personalised approach depending on patients’ comorbidities, specifically CKD, in accordance to guidelines.


 Citation

Please cite as:

Alhodaib HI, Antza C, Chandan JS, Hanif W, Sankar S, Paul S, Sutcliffe P, Nirantharakumar K

Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study

JMIR Diabetes 2020;5(4):e19650

DOI: 10.2196/19650

PMID: 33206055

PMCID: 7710444

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