Response to letter to the Editor on "Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services"

We on our recent article. 1 We wholeheartedly agree that the health informatics community should not conclude that social determinants of health (SDH) are not valuable. The literature in this area is growing, and we believe that SDH will continue to play an increasingly significant role in influencing population health. While the specific elements and local context of our work failed to demonstrate clear benefit, our study represented a single community with a novel outcome. As we noted in our article: a more diverse population or geography may have yielded different results; our results may not be generalizable to different outcomes; and that our SDH and public health measures were contextual. This last point is important, as individual and area level measures are different constructs entirely and an analysis, such as ours, is not subject to the ecological fallacy. 2 Correlation between predictors is a significant problem; we believe that this was mitigated by our use of Random Forest, which selects random subsets of fea-tures to build an ensemble of trees. 3 Consistent with the SDH perspec-tive of social, political, and environmental settings, we endeavored to measure, and account for, patient context. We further agree that context is a frequently changing construct and that regularly updated measures are always better. We also believe that more individual level SDH measures would be an improvement. We applaud the