Perceptions of optimal end-of-life care in hospitals: A cross-sectional study of nurses in three locations

Aim: To examine whether nurses' location of employment, demographics, or training influences their perceptions of what constitutes optimal care for dying patients in hospital. Design: Questionnaire-based, cross-sectional study. Methods: Between December 2016–June 2018, 582 registered or enrolled nurses from Australia (N = 153), South Korea (N = 241), and Hong Kong (N = 188) employed in a variety of hospital care units rated the extent to which they agreed with 29 indicators of optimal end-of-life care across four domains: patient, family, healthcare team, and healthcare system. Latent class analysis identified classes of respondents with similar responses. Results: Top five indicators rated by participants included: ‘physical symptoms managed well’; ‘private rooms and unlimited visiting hours’; ‘spend as much time with the patient as families wish’; 'end-of-life care documents stored well and easily accessed’ and ‘families know and follow patient's wishes’. Four latent classes were generated: ‘Whole system/holistic’ (Class 1); ‘Patient/provider-dominated’ (Class 2); ‘Family-dominated’ (Class 3) and ‘System-dominated’ (Class 4). Class 1 had the highest proportion of nurses responding positively for all indicators. Location was an important correlate of perceptions, even after controlling for individual characteristics. Conclusion: Nurses' perceptions of optimal end-of-life care are associated with location, but perhaps not in the direction that stereotypes would suggest. Findings highlight the importance of developing and implementing location-specific approaches to optimize end-of-life care in hospitals. Impact: The findings may be useful to guide education and policy initiatives in Asian and Western countries that stress that end-of-life care is more than symptom management. Indicators can be used to collect data that help quantify differences between optimal care and the care actually being delivered, thereby determining where improvements might be made.