Health Research, Teaching and Provision Of Care: Applying A New Approach Based on Complex Systems and A Knowledge Translation Complexity Network Model

Health Research, Teaching and Provision Of Care: Applying A New Approach Based on Complex Systems and A Knowledge Translation Complexity Network Model

A.H Brook H.M Liversidge D Wilson Z Jordan G Harvey R.J Marshall A.L Kitson 

School of Dentistry, University of Adelaide

Institute of Dentistry, Queen Mary University of London

School of Medicine, University of Adelaide

The Joanna Briggs Institute, University of Adelaide

School of Nursing, University of Adelaide

Manchester Business School, University of Manchester

Green Templeton College, University of Oxford

| |
| | Citation



Despite increased emphasis on the translation of research-based knowledge into practice, studies in the U.S.A. and Australia have found that up to 50 per cent of health care delivered does not accord with evidence-based guidelines. Health research, teaching and practice have traditionally emphasised defined inputs to produce specific, linear outputs and changes in teaching and practice may suffer delays in implementation when required to overcome barriers around spheres of interest. We are exploring a new approach based on the principles of complex systems and networks. In this paper, we used a successful knowledge translation project and a case study of a natural disaster, to model the effective application of these principles to a new health knowledge translation model, the Knowledge Translation Complexity Network. Following the Indian Ocean Tsunami of

2004, there were major challenges in identifying many of the dead. Research identified that Dental Age could be used to estimate the chronological age of unidentified victims up to 20 years of age. However, at the time the existing data were insufficient for this purpose and one author (HL) undertook to lead a knowledge creation and synthesis project. The research was evaluated by peer review, published in a leading journal and was subsequently implemented into practice as an identification tool in both paper and electronic forms. Subsequently the data charts and instructions have been translated into 18 languages and are used internationally in university teaching courses as well as in disaster identifications, with feedback evaluation from users providing further refinement. In conclusion, the development of the dentitions showed the characteristics of a complex adaptive system; of emergence, self-organisation, dynamic interactions, robustness and co-evolution. Further, the Dental Atlas incorporated elements of the key sub-networks of the new Knowledge Translation Complexity Network of problem identification (PI), knowledge creation (KC), knowledge synthesis (KS), implementation (I) and evaluation (E). Investigating real-world examples in this way can both highlight key aspects for future planning and identify gaps for development.


complex systems, complexity network, health research, knowledge translation


[1] Schuster, M., McGlynn, E. & Brook, R., How good is the quality of health care in the United States? The Milbank Quarterly, 76, pp. 517–563, 1998.

[2] Resnicow, K. & Page, S.E., Embracing chaos and complexity: a quantum change for public health. American Journal Public Health, 98, pp. 1382–1389, 2008.

[3] Sadia, R., The relationship between employee health, quality culture and organisational  effectiveness: findings from the literature. International Journal of Design & Nature and  Ecodynamics, 11, pp. 1–9, 2016.

[4] Kitson, A.L., Jordan, Z., Wilson, D., Harvey, G., Marshall, R. & Brook, A.H., Complexity, chaos and the changing discourse of knowledge translation. University of Adelaide, Faculty of Health Science, Working Paper, 2016.

[5] Liversidge, H.M., Lyons, F. & Hector, M.P., The accuracy of three methods of age estimation using radiographic measurements of developing teeth. Forensic Science International, 131, pp. 22–29, 2003.

[6] Liversidge, H.M., Accuracy of age estimation from developing teeth in a population of known age (0-5.4 years). International Journal of Osteoarchaeology, 4, pp. 37–45, 1994.

[7] Liversidge, H.M. & Molleson, T.I., Developing permanent tooth length as an estimate of age. 

Journal of Forensic Sciences, 44, pp. 917–920, 1999.

[8] AlQahatani, S.J., Hector, M.P. & Liversidge, H.M., Brief communication: the London Atlas of human tooth development and eruption. American Journal of Physical Anthropology, 142, pp. 481–490, 2010, available at

[9] AlQahtani, SJ., The London Atlas: developing an atlas of tooth development and testing its quality and performance measures. Queen Mary University of London 2012; PhD Thesis, available at

[10] AlQahtani, S.J., Hector, M.P. & Liversidge, H.M., Accuracy of dental age estimation charts Schour and Massler, Ubelaker and the London Atlas. American Journal of Physical  Anthropology, 154, pp. 70–78, 2014.

[11] Liversidge, H.M., Similarity in dental maturation in two ethnic groups of London children. Annals of Human Biology, 38, pp. 702–715, 2011.

[12] Elamin, F. & Liversidge, H.M., Malnutrition has no effect on the timing of human tooth formation. PLoS ONE, 8, e72274, 2013.

[13] Webpage

[14] Downloadable app

[15] Training video JSE8G0aOmtL1oYWGueSVg