TY - JOUR
T1 - Using Complexity and Network Concepts to Inform Healthcare Knowledge Translation
AU - Kitson, Alison
AU - Brook, Alan
AU - Harvey, Gill
AU - Jordan, Zoe
AU - Marshall, Rhianon
AU - O'Shea, Rebekah
AU - Wilson, David
PY - 2018/3
Y1 - 2018/3
N2 - Many representations of the movement of healthcare knowledge through society exist, and multiple models tor the translation of evidence into policy and practice have been articulated. Most are linear or cyclical and very few come close to reflecting the dense and intricate relationships, systems and politics of organizations and the processes required to enact sustainable improvements. We illustrate how using complexity and network concepts can better inform knowledge translation (KT) and argue that changing the way we think and talk about KT could enhance the creation and movement of knowledge throughout those systems needing to develop and utilise it. From our theoretical refinement, we propose that KT is a complex network composed of five interdependent sub-networks, or clusters, of key processes (problem identification [PI], knowledge creation [KC], knowledge synthesis [KS], implementation [I], and evaluation [E]) that interact dynamically in different ways at different times across one or more sectors (community; health; government; education; research tor example). We call this the KT Complexity Network, defined as a network that optimises the effective, appropriate and timely creation and movement of knowledge to those who need it in order to improve what they do. Activation within and throughout any one of these processes and systems depends upon the agents promoting the change, successfully working across and between multiple systems and clusters. The case is presented tor moving to a way of thinking about KT using complexity and network concepts. This extends the thinking that is developing around integrated KT approaches. There are a number of policy and practice implications that need to be considered in light of this shift in thinking.
AB - Many representations of the movement of healthcare knowledge through society exist, and multiple models tor the translation of evidence into policy and practice have been articulated. Most are linear or cyclical and very few come close to reflecting the dense and intricate relationships, systems and politics of organizations and the processes required to enact sustainable improvements. We illustrate how using complexity and network concepts can better inform knowledge translation (KT) and argue that changing the way we think and talk about KT could enhance the creation and movement of knowledge throughout those systems needing to develop and utilise it. From our theoretical refinement, we propose that KT is a complex network composed of five interdependent sub-networks, or clusters, of key processes (problem identification [PI], knowledge creation [KC], knowledge synthesis [KS], implementation [I], and evaluation [E]) that interact dynamically in different ways at different times across one or more sectors (community; health; government; education; research tor example). We call this the KT Complexity Network, defined as a network that optimises the effective, appropriate and timely creation and movement of knowledge to those who need it in order to improve what they do. Activation within and throughout any one of these processes and systems depends upon the agents promoting the change, successfully working across and between multiple systems and clusters. The case is presented tor moving to a way of thinking about KT using complexity and network concepts. This extends the thinking that is developing around integrated KT approaches. There are a number of policy and practice implications that need to be considered in light of this shift in thinking.
KW - Complex adaptive systems (CASs)
KW - Complexity
KW - Evidence-based practice
KW - Implementation science
KW - Integrated knowledge translation
KW - Knowledge translation (KT)
KW - Networks
UR - http://www.ijhpm.com/article_3385.html
UR - http://www.scopus.com/inward/record.url?scp=85043575057&partnerID=8YFLogxK
U2 - 10.15171/ijhpm.2017.79
DO - 10.15171/ijhpm.2017.79
M3 - Article
VL - 7
SP - 231
EP - 243
JO - International Journal of Health Policy and Management
JF - International Journal of Health Policy and Management
SN - 2322-5939
IS - 3
ER -