*2.4.6 Recommendations*

For those interested in implementing a CLN to support TSOs, there are several recommendations based on this project's findings. Firstly, recording high-quality data is crucial to this model. Securing high-quality data helps support the network and aggregate learning by effectively threading the client voice throughout all stakeholder levels. Promoting client engagement in the process of measurement is an effective strategy for enhancing data quality and building the opportunities for clinical application [9, 31, 47]. Because of this, it is important that implementation teams do not underestimate the infrastructure necessary to support practitioners working to deliver these innovations [15, 32, 35, 46]. While pooling resources can help overcome challenges relating to cost and access to expertise, without a shared framework and understanding of the key concepts, a CLN and its associated analyses are likely to be impacted. In keeping with the wider literature, access to expertise and committed project team can be beneficial for supporting the network [2, 3, 5, 6, 9]. Focusing on distinct areas of service delivery through iterative improvement cycles and acknowledging their interdependency can help achieve cumulative benefits through the combination of smaller gains [6, 21, 25]. For TSOs, the role of leadership and effects of turnover cannot be understated. While it might not be feasible in TSOs to ensure a local champion is always in place, it is valuable to build a system that enables receptiveness towards continual practice

innovation. A broader involvement and contribution among the workforce through wider supportive feedback mechanisms represents one effective strategy to overcome this.
