Patient diagnoses and causes of death explained 65% of the variability in hospital admissions during the last 12 months of life, with 50.8% of patients dying in the hospital.
Cohort (n=1,223,859)
Yes
Diagnoses and causes of death are the primary drivers of variability in hospital admissions at the end of life, while hospital provider variables have a larger impact on total bed days.
OBJECTIVE: To identify the relative importance of factors influencing hospital use at the end of life. DESIGN: Retrospective cohort study of person and health system effects on hospital use in the past 12 months modelling differences in admissions, bed days and whether a person died in hospital. SETTING: Residents in England for the period 2009/2010 to 2011/2012 using Hospital Episodes Statistics (HES) data from all acute care hospitals in England funded by the National Health Service (NHS). PARTICIPANTS: 1 223 859 people registered with a GP in England who died (decedents) in England (April 2009-March 2012) with a record of NHS hospital care. MAIN OUTCOME MEASURES: Hospital admissions, and hospital bed days and place of death (in or out of hospital) in the past 12 months of life. RESULTS: The mean number of admissions in the past 12 months of life averaged 2.28 occupying 30.05 bed days-excluding 9.8% of patients with no hospital history. A total of 50.8% of people died in hospital. Difference in hospital use was associated with a range of patient descriptors (age, gender and ethnicity). The variables with the greatest 'explanatory power' were those that described the diagnoses and causes of death. So, for example, 65% of the variability in the model of hospital admissions was explained by diagnoses. Only moderate levels of variation were explained by the hospital provider variables for admissions and deaths in hospital, though the impacts on total bed days was large. CONCLUSIONS: Comparative analyses of hospital utilisation should standardise for a range of patient specific variables. Though the models indicated some degree of variability associated with individual providers, the scale of this was not great for admissions and death in hospital but the variability associated with length of stay differences suggests that attempts to optimise hospital use should look at differences in lengths of stay and bed use. This study adds important new information about variability in admissions by diagnostic group, and variability in bed days by diagnostic group and eventual cause of death.
Bardsley et al. (Thu,) conducted a cohort in End of life (n=1,223,859). Patient diagnoses and causes of death explained 65% of the variability in hospital admissions during the last 12 months of life, with 50.8% of patients dying in the hospital.