Background: Given the progressive demographic ageing of the population and the National Health System reforms affecting care at the bedside, a periodic re-evaluation of in-hospital mortality rates and associated factors is recommended.
Aims: To describe the occurrence of in-hospital mortality among patients admitted to acute medical units and associated factors. Two hypotheses (H) were set as the basis of the study: patients have an increased likelihood to die H1: at the weekend when less nursing care is offered; H2: when they receive nursing care with a skill-mix in favour of Nursing Aides instead of Registered Nurses.
Methods: Secondary analysis of a prospective study of patients >65 years consecutively admitted in 12 Italian medical units. Data on individual and nursing care variables were collected and its association with in-hospital mortality was analysed by stepwise logistic regression analysis.
Results: In-hospital mortality occurrence was 6.8 %, and 37 % of the patients died during the weekend. The logistic regression model explained 34.3 % (R 2) of the variance of in-hospital mortality: patients were six times (95 % CI = 3.632-10.794) more likely at risk of dying at weekends; those with one or more AEDs admissions in the last 3 months were also at increased risk of dying (RR 1.360, 95 % CI = 1.024-1.806) as well as those receiving more care from family carers (RR = 1.017, 95 % CI = 1.009-1.025). At the nursing care level, those patient receiving less care by RNs at weekends were at increased risk of dying (RR = 2.236, 95 % CI = 1.270-3.937) while those receiving a higher skill-mix, thus indicating that more nursing care was offered by RNs instead of NAs were at less risk of dying (RR = 0.940, 95 % CI = 0.912-0.969).
Conclusions: Within the limitations of this secondary analysis, in addition to the role of some clinical factors, findings suggest redesigning acute care at weekends ensuring consistent care both at the hospital and at the nursing care levels.
Keywords: Elderly; Hospital mortality; Internal medicine; Longitudinal studies; Risk factors.