Vukoja, Marija

Background Adherence to evidence-based care processes and patient outcomes in intensive care units (ICUs) can be influenced by staffing and resource availability. We aimed to evaluate if there is a weekend effect on adherence to evidence-based care processes, and hospitalization outcomes and whether a checklist implementation could mitigate potential differences. Methods Post hoc analysis of the Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) study dataset collected before and after checklist implementation in 34 ICUs across 15 countries (2013-2017). Admission days were classified as ‘weekend/holidays’ or ‘weekdays’ according to local work schedules and public holidays. The primary outcome was the omission of 10 evidence-based care processes addressed in the checklist. Mortality and length of stay differences between weekend/holiday and weekday admissions were evaluated as secondary outcomes. Results 4256 patients contributed 1141 weekend versus 3501 weekday observation days pre-intervention, and 2014 versus 6507 post-intervention. Pre-intervention, peptic ulcer prophylaxis was omitted more frequently on weekends/holidays than weekdays (adjusted rate ratio [aRR], 0.58 [95%–confidence interval [CI] 0.38-0.88), whereas head-of-bed elevation was omitted more often on weekdays than on weekends/holidays (aRR, 3.17 [1.14-8.86]). Post-intervention, peptic ulcer prophylaxis omission rates became similar (aRR, 1.03 [0.68-1.56], but head-of-bed elevation became omitted more often on weekends than on weekdays (aRR, 0.63 [0.45-0.88]). Post-intervention, oral care was omitted more frequently on weekends/holidays than in weekdays (aRR, 0.63 [0.45-0.9]), and central catheter removal was more frequent on weekdays than in weekends/holidays (aRR, 1.11 [1.02-1.21]). No significant differences in mortality or length of stay were found. Conclusion A weekend effect influenced adherence to some care processes. While checklist implementation improved overall adherence, some disparities diminished, while new ones emerged. Organizational, cultural, and temporal factors should be further studied to optimize care delivery across all times and settings. Clinical Trial Registration Number NCT01973829

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education. Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ 2 test was performed to determine the association between gender and different violence forms. Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with >1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance. Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction.

OBJECTIVES: To determine whether the “Checklist for Early Recognition and Treatment of Acute Illness and Injury” decision support tool during ICU admission and rounding is associated with improvements in nonadherence to evidence-based daily care processes and outcomes in variably resourced ICUs. DESIGN, SETTINGS, PATIENTS: This before-after study was performed in 34 ICUs (15 countries) from 2013 to 2017. Data were collected for 3 months before and 6 months after Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation. INTERVENTIONS: Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation using remote simulation training. MEASUREMENTS AND MAIN RESULTS: The coprimary outcomes, modified from the original protocol before data analysis, were nonadherence to 10 basic care processes and ICU and hospital length of stay. There were 1,447 patients in the preimplementation phase and 2,809 patients in the postimplementation phase. After adjusting for center effect, Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation was associated with reduced nonadherence to care processes (adjusted incidence rate ratio [95% CI]): deep vein thrombosis prophylaxis (0.74 [0.68–0.81), peptic ulcer prophylaxis (0.46 [0.38–0.57]), spontaneous breathing trial (0.81 [0.76–0.86]), family conferences (0.86 [0.81–0.92]), and daily assessment for the need of central venous catheters (0.85 [0.81–0.90]), urinary catheters (0.84 [0.80–0.88]), antimicrobials (0.66 [0.62–0.71]), and sedation (0.62 [0.57–0.67]). Analyses adjusted for baseline characteristics showed associations of Checklist for Early Recognition and Treatment of Acute Illness and Injury implementation with decreased ICU length of stay (adjusted ratio of geometric means [95% CI]) 0.86 [0.80–0.92]), hospital length of stay (0.92 [0.85–0.97]), and hospital mortality (adjusted odds ratio [95% CI], 0.81 (0.69–0.95). CONCLUSIONS: A quality-improvement intervention with remote simulation training to implement a decision support tool was associated with decreased nonadherence to daily care processes, shorter length of stay, and decreased mortality.

Abstract Background: The Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) study is a before-and-after clinical quality improvement study involving 20 countries. Our aim was to describe the challenges and solutions for study implementation across various intensive care units.Methods: After local institutional review board approval, each study center had a setup period before patient data were collected. Each center was required to accomplish 4 stages: baseline data collection, remote simulation training, local implementation, and postimplementation data collection and maintenance of process of care. We measured the time required to complete each study stage and used the Define, Measure, Analyze, Improve, and Control (DMAIC) framework to identify the challenges encountered during each stage and guide improvement strategies to facilitate implementation of CERTAIN.Results: Between June 2012 and December 2017, 55 centers from 20 countries were recruited to participate. The time to complete each stage at different centers varied significantly. The most common domains in which challenges occurred were 1) leadership support and team building, 2) communication, 3) work environment culture, 4) language barriers, 5) infrastructure and technology, and 6) sustainability. Obstacles in these 6 areas delayed reaching major milestones of the study. Different strategies were deployed to overcome these barriers: engaging leadership for support, using native-speaking clinicians during training sessions, using various communication platforms, providing personal computers to local hospitals, making in-person site visits, offering flexible training time, and supporting local centers’ grant applications. Centers that enrolled during the control phase, compared with those that enrolled earlier, had significantly shorter times and less variation in times for each study stage and for the total study time.Conclusions: By using the DMAIC method, we identified the predominant 6 domains in which challenges occurred during implementation of the global CERTAIN study and developed targeted strategies to overcome the challenges and shorten the duration of the study. The DMAIC method would be useful in improving the efficiency of other large-scale multinational quality improvement projects.

BACKGROUND: An increasing number of patients require prolonged mechanical ventilation (PMV), which is associated with high morbidity and poor long-term survival, but there are few data regarding the incidence and outcome of PMV patients from a community perspective. METHODS: We retrospectively reviewed the electronic medical records of adult Olmsted county, Minnesota, residents admitted to the intensive care units at the 2 Mayo Clinic Rochester hospitals from January 1, 2003, to December 31, 2007, who underwent tracheostomy for PMV. RESULTS: Sixty-five patients, median age 68 years (interquartile range [IQR] 49–80 y), 39 male, underwent tracheostomy for PMV, resulting in an age-adjusted incidence of 13 (95% CI 10–17) per 100,000 patient-years at risk. The median number of days on mechanical ventilation was 24 days (IQR 18–37 d). Forty-six patients (71%) survived to hospital discharge, and 36 (55%) were alive at 1-year follow-up. After adjusting for age and baseline severity of illness, the presence of COPD was independently associated with 1-year mortality (hazard ratio 3.4, 95% CI 1.4–8.2%). CONCLUSIONS: There was a considerable incidence of tracheostomy for PMV. The presence of COPD was an independent predictor of 1-year mortality.

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.