Evaluation of US/European Deprivation Indices Applications in Oncological, Health Economics, and Outcomes Research (HEOR) Studies

OBJECTIVES: To review use of area-level deprivation indices for detecting social inequalities in oncology-focused HEOR studies.

METHODS: This conceptual paper will present a Venn-Diagram visualization demonstrating the intersection of the deprivation indices for illuminating health disparities in oncology and potential coordinated care models.

RESULTS: Numerous deprivation indices are in circulation at various geographic levels in the HEOR research; these indices are aimed at characterizing an individual’s socioeconomic and neighborhood-level risk-factor exposures. In Europe, examples of area-level deprivation indices in the UK, France, and Ireland include the Townsend Deprivation index, Carstairs index, municipality-level deprivation indices, and Pobal HP Deprivation Index; in the US, examples include Area Deprivation Index (ADI), Social Deprivation Index, and Social Vulnerability Index. Composite indices allow for coverage of multiple socioeconomic domains and comprehensive representation of neighborhood-level determinants, protect privacy, and promote study efficiency. Area-level deprivation indices help clarify the narrative of disparities throughout cancer care from screening, diagnosis, time to treatment, maintenance, and follow-up. While area-level deprivation or social determinants of health (SDOH) may be helpful for monitoring inequalities, area-level deprivation measures may vary in their usefulness depending on the exposure, size of the area, and heterogeneity within the area. Additionally, use of area-level measures may still not capture the individualized patient experience, such as SDOH risk exposure and barriers to care. Researchers are not adequately assessing the social and cultural behaviors driving disparities in oncological outcomes. This oversimplification may be exacerbating observed disparities in oncology care and outcomes.

CONCLUSIONS: HEOR research in administrative claims database presents numerous challenges in conducting studies aimed at identifying cancer disparities. Deprivation indices facilitate examination of health inequality questions in the real-world evidence space. However, the inclusion of newly added Z ICD-10 diagnosis codes at the individual-level (e.g.,Z60.5:Target-of-(perceived)-adverse-discrimination-and-persecution) can more robustly capture patient experience outside of race and area-level SDOH.