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Background: The concept of end of life (EOL), as in the term end-of-life care, is used synonymously in both palliative and terminal care. Practitioners and researchers both require a clearer specification of the end-of-life concept to be able to provide appropriate care in this phase of life and to conduct robust research on a well-described theoretical basis., Aims: The aim of this study was to critically analyse the end-of-life concept and its associated terminology., Method: A concept analysis was performed by applying Rodgers' evolutionary concept analysis method., Findings: Time remaining, clinical status/physical symptoms, psychosocial symptoms and dignity were identified as the main attributes of the concept. Transition into the end-of-life phase and its recognition were identified as antecedents. This study demonstrates that end-of-life care emerged following the application of the 'end-of-life concept' to clinical practice., Conclusion: The early recognition of the end-of-life phase seems to be crucial to ensuring an individual has well-managed symptoms and a dignified death.

Background: Comparing inpatient fall rates can serve as a benchmark for quality improvement. To improve the comparability of performance between hospitals, adjustments for patient-related fall risk factors that are not modifiable by care are recommended. Thereafter, the remaining variability in risk-adjusted fall rates can be attributed to differences in quality of care provided by a hospital. Research on risk-adjusted fall rates and their impact on hospital comparisons is currently sparse. Therefore, the aims of this study were to develop an inpatient fall risk adjustment model based on patient-related fall risk factors, and to analyse the impact of applying this model on comparisons of inpatient fall rates in acute care hospitals in Switzerland., Methods: Data on inpatient falls in Swiss acute care hospitals were collected on one day in 2017, 2018 and 2019, as part of an annual multicentre cross-sectional survey. After excluding maternity and outpatient wards, all inpatients older than 18 years were included. Two-level logistic regression models were used to construct unadjusted and risk-adjusted caterpillar plots to compare inter-hospital variability in inpatient fall rates., Results: One hundred thirty eight hospitals and 35,998 patients were included in the analysis. Risk adjustment showed that the following factors were associated with a higher risk of falling: increasing care dependency (to a great extent care dependent, odds ratio 3.43, 95% confidence interval 2.78-4.23), a fall in the last 12 months (OR 2.14, CI 1.89-2.42), the intake of sedative and or psychotropic medications (OR 1.74, CI 1.54-1.98), mental and behavioural disorders (OR 1.55, CI 1.36-1.77) and higher age (OR 1.01, CI 1.01-1.02). With odds ratios between 1.26 and 0.67, eight further ICD-10 diagnosis groups were included. Female sex (OR 0.78, CI 0.70-0.88) and postoperative patients (OR 0.83, CI 0.73-0.95) were associated with a lower risk of falling. Unadjusted caterpillar plots identified 20 low- and 3 high-performing hospitals. After risk adjustment, 2 low-performing hospitals remained., Conclusions: Risk adjustment of inpatient fall rates could reduce misclassification of hospital performance and enables a fairer basis for decision-making and quality improvement measures. Patient-related fall risk factors such as care dependency, history of falls and cognitive impairment should be routinely assessed., (© 2022. The Author(s).)