Background

Multiple scoring systems have been developed for both the intensive care unit (ICU) and the emergency department (ED) to risk stratify patients and predict mortality. However, it remains unclear whether the additional data needed to compute ICU scores improves mortality prediction for critically ill patients compared to the simpler ED scores.

Methods

We studied a prospective observational cohort of 227 critically ill patients admitted to the ICU directly from the ED at an academic, tertiary care medical center. We compared Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE III, Simplified Acute Physiology Score (SAPS) II, Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), Prince of Wales Emergency Department Score (PEDS), and a pre-hospital critical illness prediction score developed by Seymour et al. (JAMA 2010, 304(7):747-754). The primary endpoint was 60-day mortality. We compared the receiver operating characteristic (ROC) curves of the different scores and their calibration using the Hosmer-Lemeshow goodness-of-fit test and visual assessment.

Results

The ICU scores outperformed the ED scores with higher area under the curve (AUC) values (p = 0.01). There were no differences in discrimination among the ED-based scoring systems (AUC 0.698 to 0.742; p = 0.45) or among the ICU-based scoring systems (AUC 0.779 to 0.799; p = 0.60). With the exception of the Seymour score, the ED-based scoring systems did not discriminate as well as the best-performing ICU-based scoring system, APACHE III (p = 0.005 to 0.01 for comparison of ED scores to APACHE III). The Seymour score had a superior AUC to other ED scores and, despite a lower AUC than all the ICU scores, was not significantly different than APACHE III (p = 0.09). When data from the first 24 h in the ICU was used to calculate the ED scores, the AUC for the ED scores improved numerically, but this improvement was not statistically significant. All scores had acceptable calibration.

Conclusions

In contrast to prior studies of patients based in the emergency department, ICU scores outperformed ED scores in critically ill patients admitted from the emergency department. This difference in performance seemed to be primarily due to the complexity of the scores rather than the time window from which the data was derived.

Background

Many advances in health care fail to reach patients. Implementation science is the study of novel approaches to mitigate this evidence-to-practice gap.

Methods

The American Thoracic Society (ATS) created a multidisciplinary ad hoc committee to develop a research statement on implementation science in pulmonary, critical care, and sleep medicine. The committee used an iterative consensus process to define implementation science and review the use of conceptual frameworks to guide implementation science for the pulmonary, critical care, and sleep community and to explore how professional medical societies such as the ATS can promote implementation science.

Results

The committee defined implementation science as the study of the mechanisms by which effective health care interventions are either adopted or not adopted in clinical and community settings. The committee also distinguished implementation science from the act of implementation. Ideally, implementation science should include early and continuous stakeholder involvement and the use of conceptual frameworks (i.e., models to systematize the conduct of studies and standardize the communication of findings). Multiple conceptual frameworks are available, and we suggest the selection of one or more frameworks on the basis of the specific research question and setting. Professional medical societies such as the ATS can have an important role in promoting implementation science. Recommendations for professional societies to consider include: unifying implementation science activities through a single organizational structure, linking front-line clinicians with implementation scientists, seeking collaborations to prioritize and conduct implementation science studies, supporting implementation science projects through funding opportunities, working with research funding bodies to set the research agenda in the field, collaborating with external bodies responsible for health care delivery, disseminating results of implementation science through scientific journals and conferences, and teaching the next generation about implementation science through courses and other media.

Conclusions

Implementation science plays an increasingly important role in health care. Through support of implementation science, the ATS and other professional medical societies can work with other stakeholders to lead this effort.