Dong, Yue

Abstract Rationale Respiratory failure represents a major risk for morbidity and mortality. Although generally managed in the intensive care unit (ICU), respiratory failure often begins elsewhere. Checklists of care processes to minimize the duration of mechanical ventilation and adverse events are routinely used in the ICU, but are uncommonly used outside the ICU. Objectives To develop consensus among a multidisciplinary expert panel on care practices to include in a checklist of best practices for critically ill patients with respiratory failure before and after ICU admission. Methods A multidisciplinary expert panel was assembled. The panel was tasked with creating a checklist of care processes aimed at decreasing progression to respiratory failure, duration of mechanical ventilation, mortality in mechanical ventilation, and adverse events. Over the course of multiple teleconferences and e-mail communications, the Prevention of Organ Failure Checklist list was reviewed, refined, and voted upon. Items that received greater than 75% of the vote were included in the final checklist. Measurements and Main Results: Using a modified Delphi process, the expert panel was able to compile Prevention of Organ Failure Checklist into 20 items that aimed to decrease mechanical ventilation by assessing the causes of acute respiratory failure, ventilation strategies, sedation, and general critical care processes, as well as to avoid unwanted or nonbeneficial interventions. Conclusions The modified Delphi process identified readily available preventative interventions suitable for checklist implementation in patients with or progressing to respiratory failure even before ICU admission.

The outcome of critical illness depends not only on life threatening pathophysiologic disturbances, but also on several complex “system” dimensions: health care providers’ performance, organizational factors, environmental factors, family preferences and the interactions between each component. Systems engineering tools offer a novel approach which can facilitate a “systems understanding” of patient-environment interactions enabling advances in the science of healthcare delivery. Due to the complexity of operations in critical care medicine, certain assumptions are needed in order to understand system behavior. Patient variation and uncertainties underlying these assumptions present a challenge to investigators wishing to model and improve health care delivery processes. In this chapter we present a systems engineering approach to modeling critical care delivery using sepsis resuscitation as an example condition.

BACKGROUND: Many patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) have had recent healthcare interventions prior to developing ALI/ARDS. OBJECTIVE: To determine the timing of ALI/ARDS onset in relation to hospital admission and other healthcare interventions. METHODS: We conducted a population-based observational cohort study with a validated electronic surveillance tool, and identified patients with possible ALI/ARDS among critically ill adults at Mayo Clinic hospitals that provide critical care services for Olmsted County, Minnesota, in 2006. Trained investigators independently reviewed electronic medical records and confirmed the presence and timing of ALI/ARDS based on the American-European consensus definition. RESULTS: Of 124 episodes of ALI in 118 patients, only 5 did not fulfill the ARDS criteria. The syndrome developed a median 30 hours (IQR 10–82 h) after hospital admission in 79 patients (67%). ARDS was present on admission in 39 patients (33%), of whom 14 had recent hospitalization, 6 were transferred from nursing homes, and 3 had recent out-patient contact (1 antibiotic prescription, 1 surgical intervention, and 1 chemotherapy). Only 16 ARDS patients (14%) did not have known recent contact with a healthcare system. Compared to ARDS on admission, hospital-acquired ARDS was more likely to occur in surgery patients (54% vs 15%, P < .001), and had longer adjusted hospital stay (mean difference 8.9 d, 95% CI 0.3–17.4, P = .04). CONCLUSIONS: ARDS in the community most often develops either during hospitalization or in patients who recently had contact with a healthcare system. These findings have important implications for potential preventive strategies.