Mobility surveillance as a public health blind spot in long-term care

Public health surveillance in long-term care has appropriately prioritized acute adverse events that are discrete, reportable, and survey-sensitive, including falls, infections, pressure injuries, and hospital transfers (1, 2). These indicators capture immediate harm and regulatory risk, yet they only partially reflect resident trajectories. Functional mobility decline is common in institutional settings and is consistently associated with reduced community discharge, higher rehospitalization risk, and longer-term dependency (3–7). Although long-term care systems routinely collect functional data through standardized instruments such as the Minimum Data Set (MDS) 3.0 and the Continuity Assessment Record and Evaluation (CARE) Item Set (8–10), these data are rarely aggregated and interpreted as population-level surveillance signals. The problem is not assessment. It is the absence of surveillance-oriented use of existing function data. This perspective argues that mobility decline should be treated as an underrecognized public health signal in long-term care. It proposes a conservative path forward focused on feasibility, risk adjustment, ethics, and non-punitive use, so mobility trajectories can complement, not replace, current surveillance frameworks.