A systems approach using the functional resonance analysis method to support fluoride varnish application for children attending general dental practice. (April 2018)

• Record Type: Journal Article
• Authors: Ross, Al; Sherriff, Andrea; Kidd, Jamie; Gnich, Wendy; Anderson, Janet; Deas, Leigh; Macpherson, Lorna
• Is Part Of: Applied ergonomics. Volume 68(2018)
• Page Start: 294
• Page End: 303
• Publication Date: 2018-04
• Subjects: Sociotechnical systems -- Complexity -- Healthcare -- Dentistry; Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2017.12.005
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: Background: All children attending General Dental Practice in Scotland are recommended to receive twice-yearly applications of sodium fluoride varnish to prevent childhood caries, yet application is variable. Development of complex interventions requires theorizing and modelling to understand context. This study applies the Functional Resonance Analysis Method (FRAM) to produce a sociotechnical systems model and identify opportunities for intervention to support application. Methods: The FRAM was used to synthesise data which were: routine monitoring of fluoride varnish application in 2015/16; a longitudinal survey with practitioners (n = 1090); in-depth practitioner and key informant interviews (n = 43); and a 'world café' workshop (n = 56). Results: We describe a detailed model of functions linked to application, and use this to make recommendations for system-wide intervention. Conclusions: Rigorous research is required to produce accessible models of complex systems in healthcare. This novel paper shows how careful articulation of the functions associated with fluoride varnish application can support future improvement efforts. Highlights: Fluoride varnish is safe and effective for caries prevention. Varnish application takes place in a complex organisational system. Intervening in healthcare requires system level theorizing and modelling. The Functional Resonance Analysis Method allows for accessible systems models. Intervention that takes into account system variability is more likely to succeed.