Aims
Healthcare utilisation data are increasingly used to identify inequities in cancer care; however, observed variation alone cannot distinguish clinically appropriate variation from implementation-relevant underuse. This study developed and applied the Healthcare Utilisation and Underuse Determination (HUD) Framework, an implementation-informed approach for translating routinely collected healthcare utilisation data into implementation priorities, using supportive care utilisation among culturally and linguistically diverse (CALD) and non-CALD cancer populations as an exemplar.
Methods
The HUD Framework was developed through a three-phase sequential mixed-methods study. Phase 1 analysed routinely collected electronic medical record and administrative data to quantify supportive care utilisation across referral, service uptake and sustained engagement. Phase 2 used stakeholder-informed appropriateness assessment, applying a modified RAND/UCLA Appropriateness Method and Nominal Group Technique, to distinguish clinically appropriate variation from implementation-relevant underuse and prioritise tumour streams for further investigation. Phase 3 will investigate determinants underpinning prioritised implementation gaps and co-design implementation strategies using implementation science methods.
Results
Phase 1 identified variation in supportive care utilisation between CALD and non-CALD populations across gynae-oncology, haematology, lung/thoracic and lower gastrointestinal tumour streams, all of which progressed to stakeholder review. However, structured appropriateness assessment demonstrated that tumour streams exhibiting the greatest variation in healthcare utilisation were not necessarily those representing the highest implementation priority. Clinical interpretation integrated disease-specific context, expected supportive care needs, patient preferences and health service factors to distinguish clinically appropriate variation from implementation-relevant underuse. Following appropriateness assessment, one tumour stream was prioritised for determinant analysis and co-design of implementation strategies.
Conclusions
The HUD Framework provides a practical approach for translating healthcare utilisation data into targeted health service improvement. By integrating multi-indicator utilisation measurement with stakeholder-informed appropriateness assessment before determinant analysis and strategy co-design, the framework enables health services to prioritise implementation efforts where they are most likely to improve equitable access to supportive care.