Jin H. Han

Delirium in Older Emergency Department Patients: Recognition, Risk Factors, and Psychomotor Subtypes

OBJECTIVES Missing delirium in the emergency department (ED) has been described as a medical error, yet this diagnosis is frequently unrecognized by emergency physicians (EPs). Identifying a subset of patients at high risk for delirium may improve delirium screening compliance by EPs. The authors sought to determine how often delirium is missed in the ED and how often these missed cases are detected by admitting hospital physicians at the time of admission, to identify delirium risk factors in older ED patients, and to characterize delirium by psychomotor subtypes in the ED setting. METHODS This cross-sectional study was a convenience sample of patients conducted at a tertiary care, academic ED. English-speaking patients who were 65 years and older and present in the ED for less than 12 hours at the time of enrollment were included. Patients were excluded if they refused consent, were previously enrolled, had severe dementia, were unarousable to verbal stimuli for all delirium assessments, or had incomplete data. Delirium status was determined by using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) administered by trained research assistants (RAs). Recognition of delirium by emergency and hospital physicians was determined from the medical record, blinded to CAM-ICU status. Multivariable logistic regression was used to identify independent delirium risk factors. The Richmond Agitation and Sedation Scale was used to classify delirium by its psychomotor subtypes. RESULTS Inclusion and exclusion criteria were met in 303 patients, and 25 (8.3%) presented to the ED with delirium. The vast majority (92.0%, 95% confidence interval [CI] = 74.0% to 99.0%) of delirious patients had the hypoactive psychomotor subtype. Of the 25 patients with delirium, 19 (76.0%, 95% CI = 54.9% to 90.6%) were not recognized to be delirious by the EP. Of the 16 admitted delirious patients who were undiagnosed by the EPs, 15 (93.8%, 95% CI = 69.8% to 99.8%) remained unrecognized by the hospital physician at the time of admission. Dementia, a Katz Activities of Daily Living (ADL) < or = 4, and hearing impairment were independently associated with presenting with delirium in the ED. Based on the multivariable model, a delirium risk score was constructed. Dementia, Katz ADL < or = 4, and hearing impairment were weighed equally. Patients with higher risk scores were more likely to be CAM-ICU positive (area under the receiver operating characteristic [ROC] curve = 0.82). If older ED patients with one or more delirium risk factors were screened for delirium, 165 (54.5%, 95% CI = 48.7% to 60.2%) would have required a delirium assessment at the expense of missing 1 patient with delirium, while screening 141 patients without delirium. CONCLUSIONS Delirium was a common occurrence in the ED, and the vast majority of delirium in the ED was of the hypoactive subtype. EPs missed delirium in 76% of the cases. Delirium that was missed in the ED was nearly always missed by hospital physicians at the time of admission. Using a delirium risk score has the potential to improve delirium screening efficiency in the ED setting.

Diagnosing delirium in older emergency department patients: validity and reliability of the delirium triage screen and the brief confusion assessment method.

STUDY OBJECTIVE Delirium is a common form of acute brain dysfunction with prognostic significance. Health care professionals caring for older emergency department (ED) patients miss delirium in approximately 75% of cases. This error results from a lack of available measures that can be performed rapidly enough to be incorporated into clinical practice. Therefore, we developed and evaluated a novel 2-step approach to delirium surveillance for the ED. METHODS This prospective observational study was conducted at an academic ED in patients aged 65 years or older. A research assistant and physician performed the Delirium Triage Screen (DTS), designed to be a highly sensitive rule-out test, and the Brief Confusion Assessment Method (bCAM), designed to be a highly specific rule-in test for delirium. The reference standard for delirium was a comprehensive psychiatrist assessment using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. All assessments were independently conducted within 3 hours of one another. Sensitivities, specificities, and likelihood ratios with their 95% confidence intervals (95% CIs) were calculated. RESULTS Of 406 enrolled patients, 50 (12.3%) had delirium diagnosed by the psychiatrist reference standard. The DTS was 98.0% sensitive (95% CI 89.5% to 99.5%), with an expected specificity of approximately 55% for both raters. The DTSs negative likelihood ratio was 0.04 (95% CI 0.01 to 0.25) for both raters. As the complement, the bCAM had a specificity of 95.8% (95% CI 93.2% to 97.4%) and 96.9% (95% CI 94.6% to 98.3%) and a sensitivity of 84.0% (95% CI 71.5% to 91.7%) and 78.0% (95% CI 64.8% to 87.2%) when performed by the physician and research assistant, respectively. The positive likelihood ratios for the bCAM were 19.9 (95% CI 12.0 to 33.2) and 25.2 (95% CI 13.9 to 46.0), respectively. If the research assistant DTS was followed by the physician bCAM, the sensitivity of this combination was 84.0% (95% CI 71.5% to 91.7%) and specificity was 95.8% (95% CI 93.2% to 97.4%). If the research assistant performed both the DTS and bCAM, this combination was 78.0% sensitive (95% CI 64.8% to 87.2%) and 97.2% specific (95% CI 94.9% to 98.5%). If the physician performed both the DTS and bCAM, this combination was 82.0% sensitive (95% CI 69.2% to 90.2%) and 95.8% specific (95% CI 93.2% to 97.4%). CONCLUSION In older ED patients, this 2-step approach (highly sensitive DTS followed by highly specific bCAM) may enable health care professionals, regardless of clinical background, to efficiently screen for delirium. Larger, multicenter trials are needed to confirm these findings and to determine the effect of these assessments on delirium recognition in the ED.

Decreasing Lab Turnaround Time Improves Emergency Department Throughput and Decreases Emergency Medical Services Diversion: A Simulation Model

BACKGROUND The effect of decreasing lab turnaround times on emergency department (ED) efficiency can be estimated through system-level simulation models and help identify important outcome measures to study prospectively. Furthermore, such models may suggest the advantage of bedside or point-of-care testing and how they might affect efficiency measures. OBJECTIVES The authors used a sophisticated simulation model in place at an adult urban ED with an annual census of 55,000 patient visits. The effect of decreasing turnaround times on emergency medical services (EMS) diversion, ED patient throughput, and total ED length of stay (LOS) was determined. METHODS Data were generated by using system dynamics analytic modeling and simulation approach on 90 separate days from December 2, 2007, through February 29, 2008. The model was a continuous simulation of ED flow, driven by real-time actual patient data, and had intrinsic error checking to assume reasonable goodness-of-fit. A return of complete laboratory results incrementally at 120, 100, 80, 60, 40, 20, and 10 minutes was compared. Diversion calculation assumed EMS closure when more than 10 patients were in the waiting room and 100% ED bed occupancy had been reached for longer than 30 minutes, as per local practice. LOS was generated from data insertion into the patient flow stream and calculation of time to specific predefined gates. The average accuracy of four separate measurement channels (waiting room volume, ED census, inpatient admit stream, and ED discharge stream), all across 24 hours, was measured by comparing the area under the simulated curve against the area under the measured curve. Each channels accuracy was summed and averaged for an overall accuracy rating. RESULTS As lab turnaround time decreased from 120 to 10 minutes, the total number of diversion days (maximum 57 at 120 minutes, minimum 29 at 10 minutes), average diversion hours per day (10.8 hours vs. 6.0 hours), percentage of days with diversion (63% vs. 32%), and average ED LOS (2.77 hours vs. 2.17 hours) incrementally decreased, while average daily throughput (104 patients vs. 120 patients) increased. All runs were at least 85% accurate. CONCLUSIONS This simulation model suggests compelling improvement in ED efficiency with decreasing lab turnaround time. Outcomes such as time on EMS diversion, ED LOS, and ED throughput represent important but understudied areas that should be evaluated prospectively. EDs should consider processes that will improve turnaround time, such as point-of-care testing, to obtain these goals.

The Effect of Physician Triage on Emergency Department Length of Stay

BACKGROUND Emergency Department (ED) overcrowding is a serious public health issue, but few solutions exist. OBJECTIVES We sought to determine the impact of physician triage on ED length of stay for discharged and admitted patients, left-without-being-seen (LWBS) rates, and ambulance diversion. METHODS This was a pre-post study performed using retrospective data at an urban, academic tertiary care, Level I trauma center. On July 11, 2005, physician triage was initiated from 1:00 p.m. to 9:00 p.m., 7 days a week. An additional physician was placed in triage so that the ED diagnostic evaluation and treatment could be started in waiting room patients. Using the hospital information system, we obtained individual patient data, ED and waiting room statistics, and diversion status data from a 9-week pre-physician triage (May 11, 2005 to July 10, 2005) and a 9-week physician triage (July 11, 2005 to September 9, 2005) period. RESULTS We observed that overall ED length of stay decreased by 11 min, but this decrease was entirely attributed to non-admitted patients. No difference in ED length of stay was observed in admitted patients. LWBS rates decreased from 4.5% to 2.5%. Total time spent on ambulance diversion decreased from 5.6 days per month to 3.2 days per month. CONCLUSION Physician triage was associated with a decrease in LWBS rates, and time spent on ambulance diversion. However, its effect on ED LOS was modest in non-admitted ED patients and negligible in admitted patients.

Epidemiology and risk factors for delirium across hospital settings.

Delirium is one of the most common causes of acute end-organ dysfunction across hospital settings, occurring in as high as 80% of critically ill patients that require intensive care unit (ICU) care. The implications of this acute form of brain injury are profound. Across many hospital settings (emergency department, general medical ward, postoperative and ICU), a patient who experiences delirium is more likely to experience increased short- and long-term mortality, decreases in long-term cognitive function, increases in hospital length of stay and increased complications of hospital care. With the development of reliable setting-specific delirium-screening instruments, researchers have been able to highlight the predisposing and potentially modifiable risk factors that place patients at highest risk. Among the large number of risk factors discovered, administration of potent sedative medications, most notably benzodiazepines, is most consistently and strongly associated with an increased burden of delirium. Alternatively, in both the hospital and ICU, delirium can be prevented with the application of protocols that include early mobility/exercise. Future studies must work to understand the epidemiology across settings and focus upon modifiable risk factors that can be integrated into existing delirium prevention and treatment protocols.

Implementing Delirium Screening in the ICU: Secrets to Success

Objective:To review delirium screening tools available for use in the adult ICU and PICU, to review evidence-based delirium screening implementation, and to discuss common pitfalls encountered during delirium screening in the ICU. Data Sources:Review of delirium screening literature and expert opinion. Results:Over the past decade, tools specifically designed for use in critically ill adults and children have been developed and validated. Delirium screening has been effectively implemented across many ICU settings. Keys to effective implementation include addressing barriers to routine screening, multifaceted training such as lectures, case-based scenarios, one-on-one teaching, and real-time feedback of delirium screening, and interdisciplinary communication through discussion of a patient’s delirium status during bedside rounds and through documentation systems. If delirium is present, clinicians should search for reversible or treatable causes because it is often multifactorial. Conclusion:Implementation of effective delirium screening is feasible but requires attention to implementation methods, including a change in the current ICU culture that believes delirium is inevitable or a normal part of a critical illness, to a future culture that views delirium as a dangerous syndrome which portends poor clinical outcomes and which is potentially modifiable depending on the individual patients circumstances.

Delirium in the Older Emergency Department Patient – A Quiet Epidemic

Delirium is defined as an acute change in cognition that cannot be better accounted for by a preexisting or evolving dementia. This form of organ dysfunction commonly occurs in older patients in the emergency department (ED) and is associated with a multitude of adverse patient outcomes. Consequently, delirium should be routinely screened for in older ED patients. Once delirium is diagnosed, the ED evaluation should focus on searching for the underlying cause. Infection is one of the most common precipitants of delirium, but multiple causes may exist concurrently.

Delirium in Older Emergency Department Patients Is an Independent Predictor of Hospital Length of Stay

OBJECTIVES The consequences of delirium in the emergency department (ED) remain unclear. This study sought to determine if delirium in the ED was an independent predictor of prolonged hospital length of stay (LOS). METHODS This prospective cohort study was conducted at a tertiary care, academic ED from May 2007 to August 2008. The study included English-speaking patients aged 65 and older who were in the ED for less than 12 hours at enrollment. Patients were excluded if they refused consent, were previously enrolled, were unable to follow simple commands at baseline, were comatose, or did not have a delirium assessment performed by the research staff. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) was used to determine delirium status. Patients who were discharged directly from the ED were considered to have a hospital LOS of 0 days. To determine if delirium in the ED was independently associated with time to discharge, Cox proportional hazard regression was performed adjusted for age, comorbidity burden, severity of illness, dementia, functional impairment, nursing home residence, and surgical procedure. A sensitivity analysis, which included admitted patients only, was also performed. RESULTS A total of 628 patients met enrollment criteria. The median age was 75 years (interquartile range [IQR] = 69-81), 365 (58%) patients were female, 111 (18%) were nonwhite, 351 (56%) were admitted to the hospital, and 108 (17%) were delirious in the ED. Median LOS was 2 days (IQR = 0-5.5) for delirious ED patients and 1 day (IQR = 0-3) for nondelirious ED patients (p < 0.001). The hazard ratio (HR) of delirium for time to discharge was 0.71 (95% confidence interval [CI] = 0.57 to 0.89) after adjusting for confounders, and indicated that ED patients with delirium were more likely to have prolonged hospital LOS compared with those without delirium. For the sensitivity analysis, which included only hospitalized patients, the adjusted HR was 0.76 (95% CI = 0.58 to 0.99). CONCLUSIONS   Delirium in older ED patients has negative consequences and is an independent predictor of prolonged hospitalizations.

Statins and Delirium during Critical Illness: A Multicenter, Prospective Cohort Study

Objective:Since statins have pleiotropic effects on inflammation and coagulation that may interrupt delirium pathogenesis, we tested the hypotheses that statin exposure is associated with reduced delirium during critical illness, whereas discontinuation of statin therapy is associated with increased delirium. Design:Multicenter, prospective cohort study. Setting:Medical and surgical ICUs in two large tertiary care hospitals in the United States. Patients:Patients with acute respiratory failure or shock. Interventions:None. Measurements and Main Results:We measured statin exposure prior to hospitalization and daily during the ICU stay, and we assessed patients for delirium twice daily using the Confusion Assessment Method for the ICU. Of 763 patients included, whose median (interquartile range) age was 61 years (51–70 yr) and Acute Physiology and Chronic Health Evaluation II was 25 (19–31), 257 (34%) were prehospital statin users and 197 (26%) were ICU statin users. Overall, delirium developed in 588 patients (77%). After adjusting for covariates, ICU statin use was associated with reduced delirium (p < 0.01). This association was modified by sepsis and study day; for example, statin use was associated with reduced delirium among patients with sepsis on study day 1 (odds ratio, 0.22; 95% CI, 0.10–0.49) but not among patients without sepsis on day 1 (odds ratio, 0.92; 95% CI, 0.46–1.84) or among those with sepsis later, for example, on day 13 (odds ratio, 0.70; 95% CI, 0.35–1.41). Prehospital statin use was not associated with delirium (odds ratio, 0.86; 95% CI, 0.44–1.66; p = 0.18), yet the longer a prehospital statin user’s statin was held in the ICU, the higher the odds of delirium (overall p < 0.001 with the odds ratio depending on sepsis status and study day due to significant interactions). Conclusions:In critically ill patients, ICU statin use was associated with reduced delirium, especially early during sepsis; discontinuation of a previously used statin was associated with increased delirium.

Inappropriate Medication Prescriptions in Elderly Adults Surviving an Intensive Care Unit Hospitalization

To determine types of potentially (PIMs) and actually inappropriate medications (AIMs), which PIMs are most likely to be considered AIMs, and risk factors for PIMs and AIMs at hospital discharge in elderly intensive care unit (ICU) survivors.