Unmet social needs and diverticulitis: a phenotyping algorithm and cross-sectional analysis

To validate a phenotyping algorithm for gradations of diverticular disease severity and investigate relationships between unmet social needs and disease severity.

An algorithm was designed in the All of Us Research Program to identify diverticulosis, mild diverticulitis, and operative or recurrent diverticulitis requiring multiple inpatient admissions. This was validated in an independent institution and applied to a cohort in the All of Us Research Program. Distributions of individual-level social barriers were compared across quintiles of an area-level index through fold enrichment of the barrier in the fifth (most deprived) quintile relative to the first (least deprived) quintile. Social needs of food insecurity, housing instability, and care access were included in logistic regression to assess association with disease severity.

Across disease severity groups, the phenotyping algorithm had positive predictive values ranging from 0.87 to 0.97 and negative predictive values ranging from 0.97 to 0.99. Unmet social needs were variably distributed when comparing the most to the least deprived quintile of the area-level deprivation index (fold enrichment ranging from 0.53 to 15). Relative to a reference of diverticulosis, an unmet social need was associated with greater odds of operative or recurrent inpatient diverticulitis (OR [95% CI] 1.61 [1.19-2.17]).

Understanding the landscape of social barriers in disease-specific cohorts may facilitate a targeted approach when addressing these needs in clinical settings.

Using a validated phenotyping algorithm for diverticular disease severity, unmet social needs were found to be associated with greater severity of diverticulitis presentation.