Abstract
Long-term care residents worldwide frequently require emergency medical care due to multimorbidity, frailty, and functional impairment. After returning to long-term care facilities, many experience rapid health changes, leading to preventable adverse events, reduced care quality, and safety concerns. Identifying predictors of such events is essential to inform risk stratification and proactive nursing surveillance in long-term care settings. This study aimed to examine predictors of adverse events after emergency transfers, using Taiwan as a population-level case context.
A secondary data analysis was conducted using medical records from 19 long-term care facilities in northern Taiwan between October 2022 and September 2023. A total of 874 residents were included (mean age 84.84 years; 94.4 percent had two or more chronic conditions). Adverse events occurred in 38.67 percent of cases, including 24.49 percent care quality-related and 19.22 percent patient safety-related events. Multivariate logistic regression showed that deterioration in consciousness after return, increased wound numbers, and lower staff-to-resident ratios during day and night shifts were significant predictors (Cox and Snell R2 = 0.075; Nagelkerke R2 = 0.102). Predictors of care quality-related events included fall-related transfers, respiratory and cardiovascular symptoms, worsening activities of daily living and cognition, increased pressure injuries, and inadequate night staffing (Cox and Snell R2 = 0.084; Nagelkerke R2 = 0.126). Predictors of patient safety-related events included fall-related transfers, worsening activities of daily living, increased tube use, facility characteristics, and insufficient day-shift staffing (Cox and Snell R2 = 0.099; Nagelkerke R2 = 0.158).
Findings indicate that functional decline and insufficient staffing are key contributors to post-transfer adverse events. Early detection, particularly monitoring changes in consciousness, and optimization of staffing may reduce preventable harm and strengthen safety practices in long-term care settings internationally.
Notes
References:
Simon, E., Deshmukh, A., Marcus, C., Wolfe, J., & Krizo, J. (2024). Optimizing care pathways: A study of the urgent dispatch program and its impact on emergency department visits. The American journal of emergency medicine, 85, 186-189. https://doi.org/10.1016/j.ajem.2024.09.017
Wu, L., Chen, X., Khalemsky, A., Li, D., Zoubeidi, T., Lauque, D., Alsabri, M., Boudi, Z., Kumar, V. A., Paxton, J., Tsilimingras, D., Kurland, L., Schwartz, D., Hachimi-Idrissi, S., Camargo, C. A., Jr., Liu, S. W., Savioli, G., Intas, G., Soni, K. D., . . . Bellou, A. (2023). The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning: An Observational Cohort Study. Journal Clinical Medicine, 12(14). https://doi.org/10.3390/jcm12144750
Cetin-Sahin, D., Karanofsky, M., Cummings, G. G., Vedel, I., & Wilchesky, M. (2023). Measuring Potentially Avoidable Acute Care Transfers From Long-Term Care Homes in Quebec: a Cross Sectional Study. Canadian Geriatrics Journal 26(3), 339-349. https://doi.org/10.5770/cgj.26.620
Kristensen, G. S., Søndergaard, J., Andersen-Ranberg, K., & Mogensen, C. B. (2025). Acute readmissions among care home residents aged over 65years: a register-based study. European Geriatric Medicine. https://doi.org/10.1007/s41999-025-01162-7
Sigma Membership
Lambda Beta at-Large
Type
Poster
Format Type
Text-based Document
Study Design/Type
Secondary Analysis
Research Approach
Quantitative Research
Keywords:
Long-Term Care, Public and Community Health, Sub-Acute Care, Emergency Medical Services, Adverse Health Care Events, Long-Term Health Care
Recommended Citation
Chen, Yu-Chi and Liao, Yi-Ru, "Predictors of Adverse Events After Emergency Transfers in Long-Term Care: A Secondary Analysis" (2026). International Nursing Research Congress (INRC). 67.
https://www.sigmarepository.org/inrc/2026/posters_2026/67
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2026-08-06
Predictors of Adverse Events After Emergency Transfers in Long-Term Care: A Secondary Analysis
Toronto, Ontario, Canada
Long-term care residents worldwide frequently require emergency medical care due to multimorbidity, frailty, and functional impairment. After returning to long-term care facilities, many experience rapid health changes, leading to preventable adverse events, reduced care quality, and safety concerns. Identifying predictors of such events is essential to inform risk stratification and proactive nursing surveillance in long-term care settings. This study aimed to examine predictors of adverse events after emergency transfers, using Taiwan as a population-level case context.
A secondary data analysis was conducted using medical records from 19 long-term care facilities in northern Taiwan between October 2022 and September 2023. A total of 874 residents were included (mean age 84.84 years; 94.4 percent had two or more chronic conditions). Adverse events occurred in 38.67 percent of cases, including 24.49 percent care quality-related and 19.22 percent patient safety-related events. Multivariate logistic regression showed that deterioration in consciousness after return, increased wound numbers, and lower staff-to-resident ratios during day and night shifts were significant predictors (Cox and Snell R2 = 0.075; Nagelkerke R2 = 0.102). Predictors of care quality-related events included fall-related transfers, respiratory and cardiovascular symptoms, worsening activities of daily living and cognition, increased pressure injuries, and inadequate night staffing (Cox and Snell R2 = 0.084; Nagelkerke R2 = 0.126). Predictors of patient safety-related events included fall-related transfers, worsening activities of daily living, increased tube use, facility characteristics, and insufficient day-shift staffing (Cox and Snell R2 = 0.099; Nagelkerke R2 = 0.158).
Findings indicate that functional decline and insufficient staffing are key contributors to post-transfer adverse events. Early detection, particularly monitoring changes in consciousness, and optimization of staffing may reduce preventable harm and strengthen safety practices in long-term care settings internationally.
Description
This secondary analysis identified predictors of adverse events among long-term care residents after emergency transfers. Functional decline, changes in consciousness, increased wound burden, and inadequate staffing were key contributors. Early monitoring and staffing optimization may reduce preventable harm and improve safety in long-term care.