Health systems, systems thinking and innovation

Datos Bibliográficos

ID11490764
AutoresRifat Atun (0000-0002-1531-5983, Imperial College London, autor de correspondencia)
Año2012
Volumen27
Númerosuppl 4
Páginasiv4-iv8
Fecha de publicación2012-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaHealth Policy and Planning (JOURNAL)
Identificadores de la revistaISSN: 0268-1080 • E-ISSN: 1460-2237
EditorialOxford University Press (PUBLISHER • GB)
DOI10.1093/heapol/czs088
PMID23014152
OpenAlexW2144353967
IdiomaEN
Citas recibidas39
Referencias citadas46

Health systems play a critically important role in improving health. Well-functioning health systems enable achievement of good health with efficient use of available resources. Effective health systems also enable responsiveness to legitimate expectations of citizens and fairness of financing. By helping produce good health effectively, health systems also contribute to economic growth (McKee et al. 2009). Well-functioning health systems are critical in mounting effective responses to emerging public health emergencies, and addressing burden of disease, ill health and poverty due to communicable (Coker et al. 2004) and non-communicable diseases and cancers (Farmer et al. 2010; Samb et al. 2010). A number of factors influence ways in which health systems achieve good health efficiently. These factors include the capacity of both individuals and institutions within health systems, continuity of stewardship, ability to seize opportunities, and contextual characteristics such as path-dependency, sociocultural beliefs, economic set up, and history of the country concerned (Balabanova et al. 2011). However, ‘linking good health and successful health systems, in particular how health systems might be distinguished from other determinants of health, or ultimately how health systems are linked to good health, has proved challenging’ (Chen 2012). A further challenge relates to understanding how innovations (such as new policies, new knowledge and novel technologies) can be effectively introduced in health systems and how these innovations interact with health system variables to influence health outcomes. Resource scarcity, coupled with global economic crisis, has necessitated adoption of innovations in health systems to sustain effective responses and improvements in health outcomes. Yet, weak health systems hinder adoption and diffusion of innovations. Evidence-informed guidance and policies are needed to strengthen health systems and improve their receptiveness to innovations. However, there is limited understanding on how best to develop health system guidance and to translate it to policy while accounting for the complexity of health systems and varied contexts in which health systems are embedded (Lavis et al. 2012). There is also limited understanding of why many well-intentioned policies and managerial decisions aimed at improving health systems do not achieve desired outcomes, but lead to unexpected or unintended consequences. One explanation for this phenomenon is that too often the tools used for analysing health systems and the heuristics used to generate managerial decisions are too simplistic for health systems that are complex. Inadequately considered interventions often upset the equilibrium within complex systems to resist such interventions, leading to ‘policy resistance’. This paper briefly discusses health systems and dynamic complexity. It examines complex adaptive systems created through the dynamic interaction of evolving contexts, health systems and institutions within health systems. The paper explores, through illustrative case studies, how adoption and diffusion of innovations are influenced in complex adaptive systems created through interaction between innovations, institutions, health systems and contexts, using a framework that helps unpack complexity, and enables systems thinking when developing solutions to address factors that hinder or enable adoption and diffusion of innovations in health systems.

Business · Knowledge management · Process management · Systems thinking · Artificial Intelligence · Computer Science · Global Health Care Issues · Health Systems, Economic Evaluations, Quality of Life · Healthcare Systems and Reforms