Towards optimising chronic kidney disease detection and management in primary care: Underlying theory and protocol for technology development using an Integrated Knowledge Translation approach. (April 2021)

• Record Type: Journal Article
• Authors: Manski-Nankervis, Jo-Anne; Alexander, Karyn; Biezen, Ruby; Jones, Julia; Hunter, Barbara; Emery, Jon; Lumsden, Natalie; Boyle, Douglas; Gunn, Jane; McMorrow, Rita; Prictor, Megan; Taylor, Mark; Hallinan, Christine; Chondros, Patty; Janus, Edward; McIntosh, Jennifer; Nelson, Craig
• Is Part Of: Health informatics journal. Volume 27:Number 2(2021)
• Publication Date: 2021-04
• Subjects: technology -- Knowledge to Action framework -- chronic kidney disease -- primary care -- protocol -- clinical decision support -- clinical audit; Medical informatics -- Periodicals; 610.285
• DOI: 10.1177/14604582211008227
• Languages: English
• ISSNs: 1460-4582

Abstract

Worldwide, Chronic Kidney Disease (CKD), directly or indirectly, causes more than 2.4 million deaths annually with symptoms generally presenting late in the disease course. Clinical guidelines support the early identification and treatment of CKD to delay progression and improve clinical outcomes. This paper reports the protocol for the codesign, implementation and evaluation of a technological platform called Future Health Today (FHT), a software program that aims to optimise early detection and management of CKD in general practice. FHT aims to optimise clinical decision making and reduce practice variation by translating evidence into practice in real time and as a part of quality improvement activities. This protocol describes the co-design and plans for implementation and evaluation of FHT in two general practices invited to test the prototype over 12 months. Service design thinking has informed the design phase and mixed methods will evaluate outcomes following implementation of FHT. Through systematic application of co-design with service users, clinicians and digital technologists, FHT attempts to avoid the pitfalls of past studies that have failed to accommodate the complex requirements and dynamics that can arise between researchers and service users and improve chronic disease management through use of health information technology.