Post-Acute and Long-Term Care Patients Account for a Disproportionately High Number of Adverse Events in the Emergency Department

Objectives: High rates of adverse events (AEs) are reported for post-acute and long-term care settings (PA/LTC: skilled nursing facilities, inpatient rehabilitation centers, long-term acute care facilities, and home health). However, emergency department (ED)-based studies in this area are lacking. We describe all-cause harm among patients from PA/LTC settings seen in the ED. Design: Retrospective observational study using the ED Trigger Tool, with dual independent nurse reviews of 5582 ED records with triggers (findings increasing the likelihood of an AE) and confirmatory physician review of putative AEs. Setting and Participants: We captured data for all adult patients at an urban, academic ED over a 13-month period (92,859 visits). PA/LTC patients were identified using a computerized ED Trigger Tool and manual review (κ = 0.85). Measures: We characterize the AEs identified by severity and type using the ED Taxonomy of Adverse Events, and whether the AE occurred in the ED or was present on arrival. We estimate population AE rates using inverse probability weighting. Results: Compared with non-PA/LTC patients, PA/LTC patients (4.4% of population; 8.2% of our sample) tended to be older (median age 69 vs 50 years), with comparable sex ratios (54% female overall). PA/LTC patients accounted for 21% of all AEs (26% present on arrival; 13% in ED). Rates of AEs occurring in the ED were comparable after matching on age. Present on arrival AEs from a PA/LTC setting were most commonly related to patient care (39%), medication (34%), and infections (16%). Conclusions and Implications: PA/LTC patients account for a small proportion of ED visits but experience a disproportionate number of AEs that are primarily present on arrival and patient-care related, and contribute to an admission rate double that for non-PA/LTC patients. Arguably, this cohort represents PA/LTC patients with the most severe AEs. Understanding these AEs may help identify high-yield targets for quality improvement.