Structured Mobilization for Critically Ill Patients: A Pragmatic Cluster-randomized Trial.

Rationale: Small trials and professional recommendations support mobilization interventions to improve recovery among critically ill patients, but their real-world effectiveness is unknown. Objective: To evaluate a low-cost, multifaceted mobilization intervention. Methods: We conducted a stepped-wedge cluster-randomized trial across 12 ICUs with diverse case mixes. The primary and secondary samples included patients mechanically ventilated for ⩾48 hours who were ambulatory before admission, and all patients with ICU stays ⩾48 hours, respectively. The mobilization intervention included 1) designation and posting of daily mobilization goals; 2) interprofessional closed-loop communication coordinated by each ICU's facilitator; and 3) performance feedback. Measurements and Main Results: From March 4, 2019 through March 15, 2020, 848 and 1,069 patients were enrolled in the usual care and intervention phases in the primary sample, respectively. The intervention did not increase the primary outcome, patient's maximal Intensive Care Mobility Scale (range, 0-10) score within 48 hours before ICU discharge (estimated mean difference, 0.16; 95% confidence interval, -0.31 to 0.63; P = 0.51). More patients in the intervention (37.2%) than usual care (30.7%) groups achieved the prespecified secondary outcome of ability to stand before ICU discharge (odds ratio, 1.48; 95% confidence interval, 1.02 to 2.15; P = 0.04). Similar results were observed among the 7,115 patients in the secondary sample. The percentage of days on which patients received physical therapy mediated 90.1% of the intervention effect on standing. ICU mortality (31.5% vs. 29.0%), falls (0.7% vs. 0.4%), and unplanned extubations (2.0% vs. 1.8%) were similar between groups (all P > 0.3). Conclusions: A low-cost, multifaceted mobilization intervention did not improve overall mobility but improved patients' odds of standing and was safe. Clinical trial registered with www.clinicaltrials.gov (NCT03863470).

A Survey of Implementation of ABCDE Protocols.

BACKGROUND: Spontaneous awakening trials (SATs), spontaneous breathing trials (SBTs), delirium assessment/management, early mobility have been termed the ABCDE bundle. The ABCDE bundle has been proven to improve patient outcomes. However, there is often a long gap in dissemination and implementation of evidence-based medicine. OBJECTIVES: To determine the prevalent implementation of and determinants for ABCDE protocol adoption in Pennsylvania. METHODS: We developed a survey of ABCDE bundle protocols. We surveyed factors around implementation including written protocol presence, standardized assessments to guide protocols, timing of creation of protocols, and estimated adherence to protocols. We also collected data on factors that might be determinants for protocol adoption including ICU staffing models, hospital and ICU level factors. We validated the survey tool using the Michigan Health and Hospital Association Keystone ICU collaborative. We then administered the validated survey to a leader of the medical ICU or mixed medical-surgical ICU of all Pennsylvania Hospitals. Multivariable logistic and ordinal regression were used to determine associations between ICU staffing models and hospital and ICU level factors with the presence of ABCDE bundle protocols. RESULTS: In the study cohort of Pennsylvania ICUs (n = 144), we had 100 respondents (69% response). The median number of hospital beds among the respondents was 185 (IQR 111-355) with a median of 14 ICU beds (IQR 10-20). 86% reported spontaneous awakening trial protocols, 60% reported spontaneous breathing trial protocols, 43% reported delirium assessment/management protocols, and 27% reported early mobility protocols. Being a medical ICU compared to a mixed medical-surgical ICU (OR 3.48, 95% CI 1.19-10.21, P = .02) and presence of multidisciplinary rounds (OR 4.97, 95% CI 2.07-11.94, P < .001) were associated with increasing number of ABCDE bundle protocol components. CONCLUSIONS: Variable implementation of ABCDE bundle protocols was present across Pennsylvania. Team communication is important to implementation of these protocols.

A Survey to Assess Primary Care Physician Awareness of Complications Following Critical Illness.

Background: Survivors of critical illness are at risk for post-intensive care syndrome (PICS, comprised of physical dysfunction, cognitive impairment, and neuropsychiatric disorders including anxiety, depression, and post-traumatic stress). Their family members and caregivers are at risk for PICS-F (PICS-family, comprised of anxiety, depression, post-traumatic stress). PICS and PICS-F are increasingly recognized in critical care; however, the awareness among primary providers of the domains and the terms of PICS/PICS-F is unknown. Objectives: To determine current practice patterns and knowledge among primary care physicians in regards to patients recovering from critical illness; to determine barriers to care of post-critically ill patients. Methods: A paper and electronic survey were developed and randomly distributed to a subset of North Carolina primary care physicians. Survey questions consisted of the following domains: demographics, current practice, barriers to providing care, knowledge of common issues/complications following critical illness, and interest in changing care for survivors of critical illness. Results: One hundred and ninety-six surveys were delivered and 77 completed surveys (39% response rate) were analyzed. Respondents confirmed significant barriers to care of post-critically ill patients including lack of awareness of PICS/PICS-F terminology, insufficient time to spend with patients, and inadequate education of patients/families about recovery after critical illness. Fifty-seven percent of respondents thought a specialized transitional post-ICU clinic would be helpful. Sixty-two percent reported feeling comfortable caring for patients after a critical illness and 75% felt they were aware of common problems encountered after critical illness. However, 84% also thought more education about PICS/PICS-F would be helpful as would a list of common problems seen after critical illness (91%). Conclusions: Significant gaps and barriers to providing optimal post-ICU care by PCPs exist. Providers identified time constraints and educational gaps as domains needing attention. Dedicated post-ICU clinics might provide a bridge to transition care post-critical illness back to primary care providers.

Characteristics, Outcomes, and Trends of Patients With COVID-19-Related Critical Illness at a Learning Health System in the United States.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to surge in the United States and globally. OBJECTIVE: To describe the epidemiology of COVID-19-related critical illness, including trends in outcomes and care delivery. DESIGN: Single-health system, multihospital retrospective cohort study. SETTING: 5 hospitals within the University of Pennsylvania Health System. PATIENTS: Adults with COVID-19-related critical illness who were admitted to an intensive care unit (ICU) with acute respiratory failure or shock during the initial surge of the pandemic. MEASUREMENTS: The primary exposure for outcomes and care delivery trend analyses was longitudinal time during the pandemic. The primary outcome was all-cause 28-day in-hospital mortality. Secondary outcomes were all-cause death at any time, receipt of mechanical ventilation (MV), and readmissions. RESULTS: Among 468 patients with COVID-19-related critical illness, 319 (68.2%) were treated with MV and 121 (25.9%) with vasopressors. Outcomes were notable for an all-cause 28-day in-hospital mortality rate of 29.9%, a median ICU stay of 8 days (interquartile range [IQR], 3 to 17 days), a median hospital stay of 13 days (IQR, 7 to 25 days), and an all-cause 30-day readmission rate (among nonhospice survivors) of 10.8%. Mortality decreased over time, from 43.5% (95% CI, 31.3% to 53.8%) to 19.2% (CI, 11.6% to 26.7%) between the first and last 15-day periods in the core adjusted model, whereas patient acuity and other factors did not change. LIMITATIONS: Single-health system study; use of, or highly dynamic trends in, other clinical interventions were not evaluated, nor were complications. CONCLUSION: Among patients with COVID-19-related critical illness admitted to ICUs of a learning health system in the United States, mortality seemed to decrease over time despite stable patient characteristics. Further studies are necessary to confirm this result and to investigate causal mechanisms. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Haloperidol and Ziprasidone for Treatment of Delirium in Critical Illness.

BACKGROUND: There are conflicting data on the effects of antipsychotic medications on delirium in patients in the intensive care unit (ICU). METHODS: In a randomized, double-blind, placebo-controlled trial, we assigned patients with acute respiratory failure or shock and hypoactive or hyperactive delirium to receive intravenous boluses of haloperidol (maximum dose, 20 mg daily), ziprasidone (maximum dose, 40 mg daily), or placebo. The volume and dose of a trial drug or placebo was halved or doubled at 12-hour intervals on the basis of the presence or absence of delirium, as detected with the use of the Confusion Assessment Method for the ICU, and of side effects of the intervention. The primary end point was the number of days alive without delirium or coma during the 14-day intervention period. Secondary end points included 30-day and 90-day survival, time to freedom from mechanical ventilation, and time to ICU and hospital discharge. Safety end points included extrapyramidal symptoms and excessive sedation. RESULTS: Written informed consent was obtained from 1183 patients or their authorized representatives. Delirium developed in 566 patients (48%), of whom 89% had hypoactive delirium and 11% had hyperactive delirium. Of the 566 patients, 184 were randomly assigned to receive placebo, 192 to receive haloperidol, and 190 to receive ziprasidone. The median duration of exposure to a trial drug or placebo was 4 days (interquartile range, 3 to 7). The median number of days alive without delirium or coma was 8.5 (95% confidence interval [CI], 5.6 to 9.9) in the placebo group, 7.9 (95% CI, 4.4 to 9.6) in the haloperidol group, and 8.7 (95% CI, 5.9 to 10.0) in the ziprasidone group (P=0.26 for overall effect across trial groups). The use of haloperidol or ziprasidone, as compared with placebo, had no significant effect on the primary end point (odds ratios, 0.88 [95% CI, 0.64 to 1.21] and 1.04 [95% CI, 0.73 to 1.48], respectively). There were no significant between-group differences with respect to the secondary end points or the frequency of extrapyramidal symptoms. CONCLUSIONS: The use of haloperidol or ziprasidone, as compared with placebo, in patients with acute respiratory failure or shock and hypoactive or hyperactive delirium in the ICU did not significantly alter the duration of delirium. (Funded by the National Institutes of Health and the VA Geriatric Research Education and Clinical Center; MIND-USA ClinicalTrials.gov number, NCT01211522 .).

Sleep and Work in ICU Physicians During a Randomized Trial of Nighttime Intensivist Staffing.

OBJECTIVES: To compare sleep, work hours, and behavioral alertness in faculty and fellows during a randomized trial of nighttime in-hospital intensivist staffing compared with a standard daytime intensivist model. DESIGN: Prospective observational study. SETTING: Medical ICU of a tertiary care academic medical center during a randomized controlled trial of in-hospital nighttime intensivist staffing. PATIENTS: Twenty faculty and 13 fellows assigned to rotations in the medical ICU during 2012. INTERVENTIONS: As part of the parent study, there was weekly randomization of staffing model, stratified by 2-week faculty rotation. During the standard staffing model, there were in-hospital residents, with a fellow and faculty member available at nighttime by phone. In the intervention, there were in-hospital residents with an in-hospital nighttime intensivist. Fellows and faculty completed diaries detailing their sleep, work, and well-being; wore actigraphs; and performed psychomotor vigilance testing daily. MEASUREMENTS AND MAIN RESULTS: Daily sleep time (mean hours [SD]) was increased for fellows and faculty in the intervention versus control (6.7 [0.3] vs 6.0 [0.2]; p < 0.001 and 6.7 [0.1] vs 6.4 [0.2]; p < 0.001, respectively). In-hospital work duration did not differ between the models for fellows or faculty. Total hours of work done at home was different for both fellows and faculty (0.1 [< 0.1] intervention vs 1.0 [0.1] control; p < 0.001 and 0.2 [< 0.1] intervention vs 0.6 [0.1] control; p < 0.001, respectively). Psychomotor vigilance testing did not demonstrate any differences. Measures of well-being including physical exhaustion and alertness were improved in faculty and fellows in the intervention staffing model. CONCLUSIONS: Although no differences were measured in patient outcomes between the two staffing models, in-hospital nighttime intensivist staffing was associated with small increases in total sleep duration for faculty and fellows, reductions in total work hours for fellows only, and improvements in subjective well-being for both groups. Staffing models should consider how work duration, sleep, and well-being may impact burnout and sustainability.

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0). DESIGN: Prospective observational study. SETTING: Tertiary teaching hospital in Philadelphia, PA. PATIENTS: Non-ICU admissions November-December 2016. INTERVENTIONS: During a 6-week study period conducted 5 months after Early Warning System 2.0 alert implementation, nurses and providers were surveyed twice about their perceptions of the alert's helpfulness and impact on care, first within 6 hours of the alert, and again 48 hours after the alert. MEASUREMENTS AND MAIN RESULTS: For the 362 alerts triggered, 180 nurses (50% response rate) and 107 providers (30% response rate) completed the first survey. Of these, 43 nurses (24% response rate) and 44 providers (41% response rate) completed the second survey. Few (24% nurses, 13% providers) identified new clinical findings after responding to the alert. Perceptions of the presence of sepsis at the time of alert were discrepant between nurses (13%) and providers (40%). The majority of clinicians reported no change in perception of the patient's risk for sepsis (55% nurses, 62% providers). A third of nurses (30%) but few providers (9%) reported the alert changed management. Almost half of nurses (42%) but less than a fifth of providers (16%) found the alert helpful at 6 hours. CONCLUSIONS: In general, clinical perceptions of Early Warning System 2.0 were poor. Nurses and providers differed in their perceptions of sepsis and alert benefits. These findings highlight the challenges of achieving acceptance of predictive and machine learning-based sepsis alerts.

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes. DESIGN: Retrospective cohort for algorithm derivation and validation, pre-post impact evaluation. SETTING: Tertiary teaching hospital system in Philadelphia, PA. PATIENTS: All non-ICU admissions; algorithm derivation July 2011 to June 2014 (n = 162,212); algorithm validation October to December 2015 (n = 10,448); silent versus alert comparison January 2016 to February 2017 (silent n = 22,280; alert n = 32,184). INTERVENTIONS: A random-forest classifier, derived and validated using electronic health record data, was deployed both silently and later with an alert to notify clinical teams of sepsis prediction. MEASUREMENT AND MAIN RESULT: Patients identified for training the algorithm were required to have International Classification of Diseases, 9th Edition codes for severe sepsis or septic shock and a positive blood culture during their hospital encounter with either a lactate greater than 2.2 mmol/L or a systolic blood pressure less than 90 mm Hg. The algorithm demonstrated a sensitivity of 26% and specificity of 98%, with a positive predictive value of 29% and positive likelihood ratio of 13. The alert resulted in a small statistically significant increase in lactate testing and IV fluid administration. There was no significant difference in mortality, discharge disposition, or transfer to ICU, although there was a reduction in time-to-ICU transfer. CONCLUSIONS: Our machine learning algorithm can predict, with low sensitivity but high specificity, the impending occurrence of severe sepsis and septic shock. Algorithm-generated predictive alerts modestly impacted clinical measures. Next steps include describing clinical perception of this tool and optimizing algorithm design and delivery.

Caring for Critically Ill Patients with the ABCDEF Bundle: Results of the ICU Liberation Collaborative in Over 15,000 Adults.

OBJECTIVE: Decades-old, common ICU practices including deep sedation, immobilization, and limited family access are being challenged. We endeavoured to evaluate the relationship between ABCDEF bundle performance and patient-centered outcomes in critical care. DESIGN: Prospective, multicenter, cohort study from a national quality improvement collaborative. SETTING: 68 academic, community, and federal ICUs collected data during a 20-month period. PATIENTS: 15,226 adults with at least one ICU day. INTERVENTIONS: We defined ABCDEF bundle performance (our main exposure) in two ways: 1) complete performance (patient received every eligible bundle element on any given day) and 2) proportional performance (percentage of eligible bundle elements performed on any given day). We explored the association between complete and proportional ABCDEF bundle performance and three sets of outcomes: patient-related (mortality, ICU and hospital discharge), symptom-related (mechanical ventilation, coma, delirium, pain, restraint use), and system-related (ICU readmission, discharge destination). All models were adjusted for a minimum of 18 a priori determined potential confounders. MEASUREMENTS AND RESULTS: Complete ABCDEF bundle performance was associated with lower likelihood of seven outcomes: hospital death within 7 days (adjusted hazard ratio, 0.32; CI, 0.17-0.62), next-day mechanical ventilation (adjusted odds ratio [AOR], 0.28; CI, 0.22-0.36), coma (AOR, 0.35; CI, 0.22-0.56), delirium (AOR, 0.60; CI, 0.49-0.72), physical restraint use (AOR, 0.37; CI, 0.30-0.46), ICU readmission (AOR, 0.54; CI, 0.37-0.79), and discharge to a facility other than home (AOR, 0.64; CI, 0.51-0.80). There was a consistent dose-response relationship between higher proportional bundle performance and improvements in each of the above-mentioned clinical outcomes (all p < 0.002). Significant pain was more frequently reported as bundle performance proportionally increased (p = 0.0001). CONCLUSIONS: ABCDEF bundle performance showed significant and clinically meaningful improvements in outcomes including survival, mechanical ventilation use, coma, delirium, restraint-free care, ICU readmissions, and post-ICU discharge disposition.

An Official American Thoracic Society/American College of Chest Physicians Clinical Practice Guideline: Liberation from Mechanical Ventilation in Critically Ill Adults. Rehabilitation Protocols, Ventilator Liberation Protocols, and Cuff Leak Tests.

BACKGROUND: Interventions that lead to earlier liberation from mechanical ventilation can improve patient outcomes. This guideline, a collaborative effort between the American Thoracic Society and the American College of Chest Physicians, provides evidence-based recommendations to optimize liberation from mechanical ventilation in critically ill adults. METHODS: Two methodologists performed evidence syntheses to summarize available evidence relevant to key questions about liberation from mechanical ventilation. The methodologists appraised the certainty in the evidence (i.e., the quality of evidence) using the Grading of Recommendations, Assessment, Development, and Evaluation approach and summarized the results in evidence profiles. The guideline panel then formulated recommendations after considering the balance of desirable consequences (benefits) versus undesirable consequences (burdens, adverse effects, and costs), the certainty in the evidence, and the feasibility and acceptability of various interventions. Recommendations were rated as strong or conditional. RESULTS: The guideline panel made four conditional recommendations related to rehabilitation protocols, ventilator liberation protocols, and cuff leak tests. The recommendations were for acutely hospitalized adults mechanically ventilated for more than 24 hours to receive protocolized rehabilitation directed toward early mobilization, be managed with a ventilator liberation protocol, be assessed with a cuff leak test if they meet extubation criteria but are deemed high risk for postextubation stridor, and be administered systemic steroids for at least 4 hours before extubation if they fail the cuff leak test. CONCLUSIONS: The American Thoracic Society/American College of Chest Physicians recommendations are intended to support healthcare professionals in their decisions related to liberating critically ill adults from mechanical ventilation.

Official Executive Summary of an American Thoracic Society/American College of Chest Physicians Clinical Practice Guideline: Liberation from Mechanical Ventilation in Critically Ill Adults.

BACKGROUND: This clinical practice guideline addresses six questions related to liberation from mechanical ventilation in critically ill adults. It is the result of a collaborative effort between the American Thoracic Society and the American College of Chest Physicians. METHODS: A multidisciplinary panel posed six clinical questions in a Population, Intervention, Comparator, and Outcomes format. A comprehensive literature search and evidence synthesis was performed for each question, which included appraising the certainty in the evidence (i.e., the quality of evidence) using the Grading of Recommendations, Assessment, Development, and Evaluation approach. The Evidence-to-Decision framework was applied to each question, requiring the panel to evaluate and weigh the importance of the problem, the confidence in the evidence, the certainty about how much the public values the main outcomes, the magnitude and balance of desirable and undesirable outcomes, the resources and costs associated with the intervention, the impact on health disparities, and the acceptability and feasibility of the intervention. RESULTS: Evidence-based recommendations were formulated and graded initially by subcommittees and then modified after full-panel discussions. The recommendations were confirmed by confidential electronic voting; approval required that at least 80% of the panel members agree with the recommendation. CONCLUSIONS: The panel provides recommendations regarding liberation from mechanical ventilation. The details regarding the evidence and rationale for each recommendation are presented in the American Journal of Respiratory and Critical Care Medicine and Chest.

Improving Health Care for Critically Ill Patients Using an Evidence-Based Collaborative Approach to ABCDEF Bundle Dissemination and Implementation.

BACKGROUND: Patients admitted to intensive care units (ICUs) often experience pain, oversedation, prolonged mechanical ventilation, delirium, and weakness. These conditions are important in that they often lead to protracted physical, neurocognitive, and mental health sequelae now termed postintensive care syndrome. Changing current ICU practice will not only require the adoption of evidence-based interventions but the development of effective and reliable teams to support these new practices. OBJECTIVES: To build on the success of bundled care and bridge an ongoing evidence-practice gap, the Society of Critical Care Medicine (SCCM) recently launched the ICU Liberation ABCDEF Bundle Improvement Collaborative. The Collaborative aimed to foster the bedside application of the SCCM's Pain, Agitation, and Delirium Guidelines via the ABCDEF bundle. The purpose of this paper is to describe the history of the Collaborative, the evidence-based implementation strategies used to foster change and teamwork, and the performance and outcome metrics used to monitor progress. METHODS: Collaborative participants were required to attend four in-person meetings, monthly colearning calls, database training sessions, an e-Community listserv, and select in-person site visits. Teams submitted patient-level data and completed pre- and postimplementation questionnaires focused on the assessment of teamwork and collaboration, work environment, and overall ICU care. Faculty shared the evidence used to derive each bundle element as well as team-based implementation strategies for improvement and sustainment. RESULTS: Retention in the Collaborative was high, with 67 of 69 adult and eight of nine pediatric ICUs fully completing the program. Baseline and prospective data were collected on over 17,000 critically ill patients. A variety of evidence-based professional behavioral change interventions and novel implementation techniques were utilized and shared among Collaborative members. LINKING EVIDENCE TO ACTION: Hospitals and health systems can use the Collaborative structure, strategies, and tools described in this paper to help successfully implement the ABCDEF bundle in their ICUs.

A randomized trial of nighttime physician staffing in an intensive care unit.

BACKGROUND: Increasing numbers of intensive care units (ICUs) are adopting the practice of nighttime intensivist staffing despite the lack of experimental evidence of its effectiveness. METHODS: We conducted a 1-year randomized trial in an academic medical ICU of the effects of nighttime staffing with in-hospital intensivists (intervention) as compared with nighttime coverage by daytime intensivists who were available for consultation by telephone (control). We randomly assigned blocks of 7 consecutive nights to the intervention or the control strategy. The primary outcome was patients' length of stay in the ICU. Secondary outcomes were patients' length of stay in the hospital, ICU and in-hospital mortality, discharge disposition, and rates of readmission to the ICU. For length-of-stay outcomes, we performed time-to-event analyses, with data censored at the time of a patient's death or transfer to another ICU. RESULTS: A total of 1598 patients were included in the analyses. The median Acute Physiology and Chronic Health Evaluation (APACHE) III score (in which scores range from 0 to 299, with higher scores indicating more severe illness) was 67 (interquartile range, 47 to 91), the median length of stay in the ICU was 52.7 hours (interquartile range, 29.0 to 113.4), and mortality in the ICU was 18%. Patients who were admitted on intervention days were exposed to nighttime intensivists on more nights than were patients admitted on control days (median, 100% of nights [interquartile range, 67 to 100] vs. median, 0% [interquartile range, 0 to 33]; P<0.001). Nonetheless, intensivist staffing on the night of admission did not have a significant effect on the length of stay in the ICU (rate ratio for the time to ICU discharge, 0.98; 95% confidence interval [CI], 0.88 to 1.09; P=0.72), ICU mortality (relative risk, 1.07; 95% CI, 0.90 to 1.28), or any other end point. Analyses restricted to patients who were admitted at night showed similar results, as did sensitivity analyses that used different definitions of exposure and outcome. CONCLUSIONS: In an academic medical ICU in the United States, nighttime in-hospital intensivist staffing did not improve patient outcomes. (Funded by University of Pennsylvania Health System and others; ClinicalTrials.gov number, NCT01434823.).

An Environmental Scan for Early Mobilization Practices in U.S. ICUs.

OBJECTIVE: Early mobilization improves patient outcomes. However, diffusion of this intervention into standard ICU practice is unknown. Dissemination and implementation efforts may be guided by an environmental scan to detail readiness for early mobilization, current practice, and barriers to early mobilization. DESIGN: A telephone survey. SETTING: U.S. ICUs. SUBJECTS: Five hundred randomly selected U.S. ICUs stratified by regional hospital density and hospital size. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We surveyed 687 ICUs for a 73% response rate (500 ICUs); 99% of respondents were nursing leadership. Fifty-one percent of hospitals reported an academic affiliation. Surveyed ICUs were most often mixed medical/surgical (58%) or medical (22%) with a median of 16 beds (12-24). Thirty-four percent reported presence of a dedicated physical and/or occupational therapy team for the ICU. Overall, 45% of ICUs reported early mobilization practice; two thirds of ICUs with early mobilization practice reported using a written early mobilization protocol. In ICUs with early mobilization practice, 52% began the intervention at admission and 74% enacted early mobilization for both ventilated and nonventilated patients. Early mobilization was provided a median of 6 days per week, twice daily. Factors independently associated with early mobilization protocols include dedicated physical/occupational therapy (odds ratio, 3.34; 95% CI, 2.13-5.22; p<0.01), American Hospital Association region 2 (odds ratio, 3.33; 95% CI, 1.04-10.64; p=0.04), written sedation protocol (odds ratio, 2.36; 95% CI, 1.25-4.45; p<0.01), daily multidisciplinary rounds (odds ratio, 2.31; 95% CI, 1.29-4.15; p<0.01), and written daily goals for patients (odds ratio, 2.17; 95% CI, 1.02-4.64; p=0.04). Commonly cited barriers included equipment, staffing, patient and caregiver safety, and competing priorities. In ICUs without early mobilization adoption, 78% have considered implementation but cite barriers including competing priorities and need for further planning. CONCLUSIONS: Diffusion regarding benefits of early mobilization has occurred, but adoption into practice is lagging. Mandates for multidisciplinary rounds and formal sedation protocols may be necessary strategies to increase the likelihood of successful early mobilization implementation. Methods to accurately assess and compare institutional performance via practice audit are needed.

Blueprint for Implementing New Processes in Acute Care: Rescuing Adult Patients With Intraosseous Access.

The intraosseous (IO) access initiative at an urban university adult level 1 trauma center began from the need for a more expeditious vascular access route to rescue patients in extremis. The goal of this project was a multidisciplinary approach to problem solving to increase access of IO catheters to rescue patients in all care areas. The initiative became a collaborative effort between nursing, physicians, and pharmacy to embark on an acute care endeavor to standardize IO access. This is a descriptive analysis of processes to effectively develop collaborative strategies to navigate hospital systems and successfully implement multilayered initiatives. Administration should empower nurse to advance their practice to include IO for patient rescue. Intraosseous access may expedite resuscitative efforts in patients in extremis who lack venous access or where additional venous access is required for life-saving therapies. Limiting IO dwell time may facilitate timely definitive venous access. Continued education and training by offering IO skill laboratory refreshers and annual e-learning didactic is optimal for maintaining proficiency and knowledge. More research opportunities exist to determine medication safety and efficacy in adult patients in the acute care setting.

Long-term outcomes after treatment of delirium during critical illness with antipsychotics (MIND-USA): a randomised, placebo-controlled, phase 3 trial.

BACKGROUND: Delirium is common during critical illness and is associated with long-term cognitive impairment and disability. Antipsychotics are frequently used to treat delirium, but their effects on long-term outcomes are unknown. We aimed to investigate the effects of antipsychotic treatment of delirious, critically ill patients on long-term cognitive, functional, psychological, and quality-of-life outcomes. METHODS: This prespecified, long-term follow-up to the randomised, double-blind, placebo-controlled phase 3 MIND-USA Study was conducted in 16 hospitals throughout the USA. Adults (aged ≥18 years) who had been admitted to an intensive care unit with respiratory failure or septic or cardiogenic shock were eligible for inclusion in the study if they had delirium. Participants were randomly assigned-using a computer-generated, permuted-block randomisation scheme with stratification by trial site and age-in a 1:1:1 ratio to receive intravenous placebo, haloperidol, or ziprasidone for up to 14 days. Investigators and participants were masked to treatment group assignment. 3 months and 12 months after randomisation, we assessed survivors' cognitive, functional, psychological, quality-of-life, and employment outcomes using validated telephone-administered tests and questionnaires. This trial was registered with ClinicalTrials.gov, NCT01211522, and is complete. FINDINGS: Between Dec 7, 2011, and Aug 12, 2017, we screened 20 914 individuals, of whom 566 were eligible and consented or had consent provided to participate. Of these 566 patients, 184 were assigned to the placebo group, 192 to the haloperidol group, and 190 to the ziprasidone group. 1-year survival and follow-up rates were similar between groups. Cognitive impairment was common in all three treatment groups, with a third of survivors impaired at both 3-month and 12-month follow-up in all groups. More than half of the surveyed survivors in each group had cognitive or physical limitations (or both) that precluded employment at both 3-month and 12-month follow-up. At both 3 months and 12 months, neither haloperidol (adjusted odds ratio 1·22 [95% CI 0·73-2.04] at 3 months and 1·12 [0·60-2·11] at 12 months) nor ziprasidone (1·07 [0·59-1·96] at 3 months and 0·94 [0·62-1·44] at 12 months) significantly altered cognitive outcomes, as measured by the Telephone Interview for Cognitive Status T score, compared with placebo. We also found no evidence that functional, psychological, quality-of-life, or employment outcomes improved with haloperidol or ziprasidone compared with placebo. INTERPRETATION: In delirious, critically ill patients, neither haloperidol nor ziprasidone had a significant effect on cognitive, functional, psychological, or quality-of-life outcomes among survivors. Our findings, along with insufficient evidence of short-term benefit and frequent inappropriate continuation of antipsychotics at hospital discharge, indicate that antipsychotics should not be used routinely to treat delirium in critically ill adults. FUNDING: National Institutes of Health and the US Department of Veterans Affairs.

Use of therapeutic hypothermia after in-hospital cardiac arrest.

OBJECTIVES: Formal guidelines recommend that therapeutic hypothermia be considered after in-hospital cardiac arrest. The rate of therapeutic hypothermia use after in-hospital cardiac arrest and details about its implementation are unknown. We aimed to determine the use of therapeutic hypothermia for adult in-hospital cardiac arrest, whether use has increased over time, and to identify factors associated with its use. DESIGN: Multicenter, prospective cohort study. SETTING: A total of 538 hospitals participating in the Get With the Guidelines-Resuscitation database (2003-2009). PATIENTS: A total of 67,498 patients who had return of spontaneous circulation after in-hospital cardiac arrest. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the initiation of therapeutic hypothermia. We measured the proportion of therapeutic hypothermia patients who achieved target temperature (32-34 °C) and were overcooled. Of 67,498 patients, therapeutic hypothermia was initiated in 1,367 patients (2.0%). The target temperature (32-34 °C) was not achieved in 44.3% of therapeutic hypothermia patients within 24 hours and 17.6% were overcooled. The use of therapeutic hypothermia increased from 0.7% in 2003 to 3.3% in 2009 (p < 0.001). We found that younger age (p < 0.001) and occurrence in a non-ICU location (p < 0.001), on a weekday (p = 0.005), and in a teaching hospital (p = 0.001) were associated with an increased likelihood of therapeutic hypothermia being initiated. CONCLUSIONS: After in-hospital cardiac arrest, therapeutic hypothermia was used rarely. Once initiated, the target temperature was commonly not achieved. The frequency of use increased over time but remained low. Factors associated with therapeutic hypothermia use included patient age, time and location of occurrence, and type of hospital.