Joey Elias is a PhD candidate currently investigating the implementation of a novel, nurse-led and distance-delivered program aimed at re-engaging survivors of childhood cancer back into lifelong care. He completed his honours degree in Psychology at the University of Sydney, where he explored a preclinical microbiome targeted treatment for cognitive challenges induced by chemotherapy. Joey’s research interest has shifted to exploring the psychosocial challenges faced by cancer survivors, with a focus on the factors influencing implementation of new innovations within health systems.
Advances in complex genomic sequencing (CGS) raise the possibility of personalised care for advanced cancer patients. However, oncologists report many challenges to use of CGS, particularly outside academic centres of excellence. Implementation science methods can inform the design of service interventions to improve the incorporation of CGS within care pathways. Our study aimed to develop an Implementation Research Logic Model (IRLM) to represent the optimal pathways for CGS implementation.
Phase 1: Interviewed oncologists (n=11) who delivered CGS to advanced cancer patients. Barriers were coded to the CFIR, and implementation strategies were matched using the CFIR/ERIC tool. Three service model interventions emerged through intuitive coding (centralised experts, local superusers, and point of care resources), and were well-aligned with ERIC strategies. Phase 2: Conducted virtual focus groups with oncologists (n=10), facilitated by an online quantitative data collection tool, to gather preferences for the operationalisation of each service model. CFIR/ERIC was used to generate a suite of service model-specific implementation strategies. Data collected across both phases was inputted into an IRLM.
The IRLM represents a number of hypothesised relationships between implementation factors for each service intervention. For example, the IRLM describes the local superuser (LSU) (ERIC: identify/prepare champions) as a service intervention that can address oncologists’ low confidence to discuss germline findings during patient consenting (CFIR: self-efficacy). The IRLM also represents operational challenges such as difficulties recruiting superusers at regional/rural sites (CFIR: available resources) and proposes identifying site-specific barriers/facilitators (ERIC: assess for readiness) to enable sites to train appropriate LSU’s and plan for continuity/redundancy (hypothesised mechanism).
IRLMs offer a framework for describing causal pathways and complex relationships between implementation determinants, interventions, and outcomes. Ultimately, these assumed relationships can be theoretically or empirically evaluated to aid in the development of more effective implementation/service interventions.