Towards safer, better healthcare: harnessing the natural properties of complex sociotechnical systems

Abstract

Objectives: To sustain an argument that harnessing the natural properties of sociotechnical systems is necessary to promote safer, better healthcare.

Methods: Triangulated analyses of discrete literature sources, particularly drawing on those from mathematics, sociology, marketing science and psychology.

Results: Progress involves the use of natural networks and exploiting features such as their scale-free and small world nature, as well as characteristics of group dynamics like natural appeal (stickiness) and propagation (tipping points). The agenda for change should be set by prioritising problems in natural categories, addressed by groups who self select on the basis of their natural interest in the areas in question, and who set clinical standards and develop tools, the use of which should be monitored by peers. This approach will facilitate the evidence-based practice that most agree is now overdue, but which has not yet been realised by the application of conventional methods.

Conclusion: A key to health system transformation may lie under-recognised under our noses, and involves exploiting the naturally-occurring characteristics of complex systems. Current strategies to address healthcare problems are insufficient. Clinicians work best when their expertise is mobilised, and they flourish in groupings of their own interests and preference. Being invited, empowered and nurtured rather than directed, micro-managed and controlled through a hierarchy is preferable.

Figure 1. Friendship clusters in a US school. Reprinted with permission from Moody J. Peer influence groups: identifying dense clusters in large networks. Soc Netw 2001;23:261–83.

Figure 2. Structural typology of the internet. Reprinted with permission from Carmi S, Havlin S, Kirkpatrick S, et al. A model of Internet typology using k-shell decomposition. Proc Natl Acad Sci U S A 2007;104:11150–4.

Figure 3. Framingham Heart Study and obesity networks. Reprinted with permission from Christakis N, Fowler J. The spread of obesity in a large social network over 32 years N Engl J Med 2007;357:370–9.