Health-related social needs screening bias as a health equity measurement problem

Health systems have invested heavily in expanding health-related social needs (HRSN) screening to more systematically identify unmet needs, yet emerging evidence shows that the very process designed to uncover inequity is being shaped by inequitable structures. In this issue of JAMA Health Forum, Vest and colleagues demonstrate that screening practices reflect clinician assumptions, patient fears, and structural barriers, such as language access, producing data that underrepresent the very populations screening is meant to identify.Bias in any measurement tool inherently exists, and the problem of several sources of bias is not unique to HRSN screening efforts. However, understanding the sources of bias and how it manifests in clinical settings is helpful in taking steps to mitigate these biases. HRSN data inform operational and policy decisions, meaning that when screening omits those with the greatest need, the resulting estimates underestimate prevalence and weaken the rationale for investment in affected communities. These gaps are not simply missing data points; they alter the empirical foundation on which resource decisions are made. The patient who is not handed the screener because she looks affluent, the patient who does not disclose housing instability because she fears losing custody of her children: these individuals are precisely whom screening aims to identify. A measurement bias that aligns with existing social disparities does more than degrade data quality: it distorts resource allocation and weakens policy arguments for communities with the least capacity to absorb its consequences.