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Building clinical networks: a developmental evaluation framework
  1. Peter Carswell1,
  2. Benjamin Manning2,
  3. Janet Long2,
  4. Jeffrey Braithwaite2
  1. 1School of Population Health, University of Auckland, Auckland, New Zealand
  2. 2Centre for Clinical Governance Research, Australian Institute of Health Innovation, University of New South Wales, Sydney, New South Wales, Australia
  1. Correspondence to Dr Peter Carswell, School of Population Health, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand; p.carswell{at}


Background Clinical networks have been designed as a cross-organisational mechanism to plan and deliver health services. With recent concerns about the effectiveness of these structures, it is timely to consider an evidence-informed approach for how they can be developed and evaluated.

Objective To document an evaluation framework for clinical networks by drawing on the network evaluation literature and a 5-year study of clinical networks.

Method We searched literature in three domains: network evaluation, factors that aid or inhibit network development, and on robust methods to measure network characteristics. This material was used to build a framework required for effective developmental evaluation.

Results The framework's architecture identifies three stages of clinical network development; partner selection, network design and network management. Within each stage is evidence about factors that act as facilitators and barriers to network growth. These factors can be used to measure progress via appropriate methods and tools. The framework can provide for network growth and support informed decisions about progress.

Conclusions For the first time in one place a framework incorporating rigorous methods and tools can identify factors known to affect the development of clinical networks. The target user group is internal stakeholders who need to conduct developmental evaluation to inform key decisions along their network's developmental pathway.

  • Evaluation methodology
  • Healthcare quality improvement
  • Implementation science

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