Patient and hospital-level characteristics associated with the use of do-not-resuscitate orders in patients hospitalized for sepsis
Background: Identifying factors associated with do-not-resuscitate (DNR) orders is an informative step in developing strategies to improve their use. As such, a descriptive analysis of the factors associated with the use of DNR orders in the early and late phases of hospitalizations for sepsis was performed.
Methods: A retrospective cohort of adult patients hospitalized for sepsis was identified using a statewide administrative database. DNR orders placed within 24 hours of hospitalization (early DNR) and after 24 hours of hospitalization (late DNR) were the primary outcome variables. Multivariable logistic regression analysis was used to identify patient, hospital, and healthcare system-related factors associated with the use of early and late DNR orders.
Results: Among 77,329 patients hospitalized for sepsis, 27.5% had a DNR order during their hospitalization. Among the cases with a DNR order, 75.5% had the order within 24 hours of hospitalization. Smaller hospital size and the absence of a teaching program increased the likelihood of an early DNR order being written. Additionally, greater patient age, female gender, White race, more medical co-morbidities, Medicare payer status and admission from a skilled nursing facility were all significantly associated with the likelihood of having an early DNR. The strength of association between these factors and the use of late DNR orders was weaker. In contrast, the greater the burden of medical co-morbidities the more likely a patient was to receive a late DNR order.
Conclusion: Multiple patient, hospital, and healthcare system-related factors are associated with the use of DNR orders in sepsis, many of which appear to be independent of a patient's clinical status. Over the course of the hospitalization, the burden of medical illness shows a stronger association relative to other variables. Strategies to improve the use of DNR orders need to recognize the influence of these multi-level factors.