Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to identify and provide individuals at risk for developing PTSD with timely interventions. The present study seeks to identify a minimal set of trauma-related symptoms, assessed during the weeks following traumatic exposure, that can accurately predict PTSD. Participants were 2185 adults (Mean age=36.4 years; 64% women; 50% Black) presenting for emergency care following traumatic exposure. Participants received a 'flash survey' with 6-8 varying symptoms (from a pool of 26 trauma symptoms) several times per week for eight weeks following the trauma exposure (each symptom assessed ∼6 times). Features (mean, sd, last, worst, peak-end scores) from the repeatedly assessed symptoms were included as candidate variables in a CART machine learning analysis to develop a pragmatic predictive algorithm. PTSD (PCL-5 ≥38) was present for 669 (31%) participants at the 8-week follow-up. A classification tree with three splits, based on mean scores of nervousness, rehashing, and fatigue, predicted PTSD with an Area Under the Curve of 0.836. Findings suggest feasibility for a 3-item assessment protocol, delivered once per week, following traumatic exposure to assess and potentially facilitate follow-up care for those at risk.

Developing Safe Harbors to Address Malpractice Liability and Wasteful Health Care Spending.

This Viewpoint discusses the feasibility of developing safe harbors that account for the role of medical malpractice liability and go beyond generic guidelines discouraging the overuse of health care resources.

Utility of Wrist-Wearable Data for Assessing Pain, Sleep, and Anxiety Outcomes After Traumatic Stress Exposure.

Importance: Adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure are common and have higher incidence among socioeconomically disadvantaged populations. Pain, depression, avoidance of trauma reminders, reexperiencing trauma, anxiety, hyperarousal, sleep disruption, and nightmares have been reported. Wrist-wearable devices with accelerometers capable of assessing 24-hour rest-activity characteristics are prevalent and may have utility in measuring these outcomes. Objective: To evaluate whether wrist-wearable devices can provide useful biomarkers for recovery after traumatic stress exposure. Design, Setting, and Participants: Data were analyzed from a diverse cohort of individuals seen in the emergency department after experiencing a traumatic stress exposure, as part of the Advancing Understanding of Recovery After Trauma (AURORA) study. Participants recruited from 27 emergency departments wore wrist-wearable devices for 8 weeks, beginning in the emergency department, and completed serial assessments of neuropsychiatric symptoms. A total of 19 019 patients were screened. Of these, 3040 patients met study criteria, provided informed consent, and completed baseline assessments. A total of 2021 provided data from wrist-wearable devices, completed the 8-week assessment, and were included in this analysis. The data were randomly divided into 2 equal parts (n = 1010) for biomarker identification and validation. Data were collected from September 2017 to January 2020, and data were analyzed from May 2020 to November 2022. Exposures: Participants were recruited for the study after experiencing a traumatic stress exposure (most commonly motor vehicle collision). Main Outcomes and Measures: Rest-activity characteristics were derived and validated from wrist-wearable devices associated with specific self-reported symptom domains at a point in time and changes in symptom severity over time. Results: Of 2021 included patients, 1257 (62.2%) were female, and the mean (SD) age was 35.8 (13.0) years. Eight wrist-wearable device biomarkers for symptoms of adverse posttraumatic neuropsychiatric sequelae exceeded significance thresholds in the derivation cohort. One of these, reduced 24-hour activity variance, was associated with greater pain severity (r = -0.14; 95% CI, -0.20 to -0.07). Changes in 6 rest-activity measures were associated with changes in pain over time, and changes in the number of transitions between sleep and wake over time were associated with changes in pain, sleep, and anxiety. Simple cutoffs for these biomarkers identified individuals with good recovery for pain (positive predictive value [PPV], 0.85; 95% CI, 0.82-0.88), sleep (PPV, 0.63; 95% CI, 0.59-0.67, and anxiety (PPV, 0.76; 95% CI, 0.72-0.80) with high predictive value. Conclusions and Relevance: These findings suggest that wrist-wearable device biomarkers may have utility as screening tools for pain, sleep, and anxiety symptom outcomes after trauma exposure in high-risk populations.

Measuring Emergency Department Acuity.

BACKGROUND: Emergency department (ED) acuity is the general level of patient illness, urgency for clinical intervention, and intensity of resource use in an ED environment. The relative strength of commonly used measures of ED acuity is not well understood. METHODS: We performed a retrospective cross-sectional analysis of ED-level data to evaluate the relative strength of association between commonly used proxy measures with a full spectrum measure of ED acuity. Common measures included the percentage of patients with Emergency Severity Index (ESI) scores of 1 or 2, case mix index (CMI), academic status, annual ED volume, inpatient admission rate, percentage of Medicare patients, and patients seen per attending-hour. Our reference standard for acuity is the proportion of high-acuity charts (PHAC) coded and billed according to the Centers for Medicare and Medicaid Service's Ambulatory Payment Classification (APC) system. High-acuity charts included those APC 4 or 5 or critical care. PHAC was represented as a fractional response variable. We examined the strength of associations between common acuity measures and PHAC using Spearman's rank correlation coefficients (rs ) and regression models including a quasi-binomial generalized linear model and linear regression. RESULTS: In our univariate analysis, the percentage of patients ESI 1 or 2, CMI, academic status, and annual ED volume had statistically significant associations with PHAC. None explained more than 16% of PHAC variation. For regression models including all common acuity measures, academic status was the only variable significantly associated with PHAC. CONCLUSION: Emergency Severity Index had the strongest association with PHAC followed by CMI and annual ED volume. Academic status captures variability outside of that explained by ESI, CMI, annual ED volume, percentage of Medicare patients, or patients per attending per hour. All measures combined only explained only 42.6% of PHAC variation.

A National Study of U.S. Emergency Departments: Racial Disparities in Hospitalizations for Heart Failure.

INTRODUCTION: Racial disparities in heart failure hospitalizations are well documented. The majority of heart failure hospitalizations originate from emergency departments, but emergency department hospitalization patterns for heart failure and the factors that influence hospitalization are poorly understood. This gap in knowledge was examined using a nationally representative sample of emergency department visits for heart failure. METHODS: National Hospital Ambulatory Medicare Care Survey data on 2001-2010 emergency department visits were analyzed in 2015-2017 to examine age-related racial differences in hospitalization patterns for heart failure, using multivariable modified Poisson regression models. RESULTS: More than 12million adult visits for heart failure to U.S. emergency departments occurred from 2001 to 2010, with 23% of visits by blacks. Overall, 71% of visits resulted in hospitalization (57% to floor beds and 14% to intensive care units). Among floor admissions for higher clinical acuity visits, whites were more likely than blacks to be hospitalized. Whites with higher clinical acuity were more likely to be hospitalized than those with lower clinical acuity (71% vs 63%, p=0.005). This expected pattern was not observed in blacks, particularly those aged ≥65years, who were hospitalized in 71% of lower clinical acuity visits, but only 61% of higher acuity visits. Among adults aged ≥65years, there was a significant interaction between clinical acuity Xrace with regard to hospitalization (p=0.037). CONCLUSIONS: These results suggest age and racial disparities in hospitalization rates for emergency department patients with heart failure. The reasons for these disparities in hospitalization are unclear. Further studies on emergency department hospitalization decisions, and the impact of emergency department clinical factors, may help clarify this finding. SUPPLEMENT INFORMATION: This article is part of a supplement entitled African American Men's Health: Research, Practice, and Policy Implications, which is sponsored by the National Institutes of Health.

Systolic Blood Pressure and Biochemical Assessment of Adherence: A Cross-Sectional Analysis in the Emergency Department.

Elevated blood pressure (BP) is common in the emergency department (ED), but the relationship between antihypertensive medication adherence and BP in the ED is unclear. This cross-sectional study tested the hypothesis that higher antihypertensive adherence is associated with lower systolic BP (SBP) in the ED among adults with hypertension who sought ED care at an academic hospital from July 2012 to April 2013. Biochemical assessment of antihypertensive adherence was performed using a mass spectrometry blood assay, and the primary outcome was average ED SBP. Analyses were stratified by number of prescribed antihypertensives (<3, ≥3) and adjusted for age, sex, race, insurance, literacy, numeracy, education, body mass index, and comorbidities. Among 85 patients prescribed ≥3 antihypertensives, mean SBP for adherent patients was 134.4 mm Hg (±26.1 mm Hg), and in adjusted analysis was -20.8 mm Hg (95% confidence interval, -34.2 to -7.4 mm Hg; P=0.003) different from nonadherent patients. Among 176 patients prescribed <3 antihypertensives, mean SBP was 135.5 mm Hg (±20.6 mm Hg) for adherent patients, with no difference by adherence in adjusted analysis (+2.9 mm Hg; 95% confidence interval, -4.7 to 10.5 mm Hg; P=0.45). Antihypertensive nonadherence identified by biochemical assessment was common and associated with higher SBP in the ED among patients who had a primary care provider and health insurance and who were prescribed ≥3 antihypertensives. Biochemical assessment of antihypertensives could help distinguish medication nonadherence from other contributors to elevated BP and identify target populations for intervention.

Role of Health Insurance Status in Interfacility Transfers of Patients With ST-Elevation Myocardial Infarction.

Lack of health insurance is associated with interfacility transfer from emergency departments for several nonemergent conditions, but its association with transfers for ST-elevation myocardial infarction (STEMI), which requires timely definitive care for optimal outcomes, is unknown. Our objective was to determine whether insurance status is a predictor of interfacility transfer for emergency department visits with STEMI. We analyzed data from the 2006 to 2011 Nationwide Emergency Department Sample examining all emergency department visits for patients age 18 years and older with a diagnosis of STEMI and a disposition of interfacility transfer or hospitalization at the same institution. For emergency department visits with STEMI, our multivariate logistic regression model included emergency department disposition status (interfacility transfer vs hospitalization at the same institution) as the primary outcome, and insurance status (none vs any [including Medicare, Medicaid, and private insurance]) as the primary exposure. We found that among 1,377,827 emergency department STEMI visits, including 249,294 (18.1%) transfers, patients without health insurance (adjusted odds ratio 1.6, 95% CI 1.5 to 1.7) were more likely to be transferred than those with insurance. Lack of health insurance status was also an independent risk factor for transfer compared with each subcategory of health insurance, including Medicare, Medicaid, and private insurance. In conclusion, among patients presenting to United States emergency departments with STEMI, lack of insurance was an independent predictor of interfacility transfer. In conclusion, because interfacility transfer is associated with longer delays to definitive STEMI therapy than treatment at the same facility, lack of health insurance may lead to important health disparities among patients with STEMI.

Assessment of dyspnea early in acute heart failure: patient characteristics and response differences between likert and visual analog scales.

BACKGROUND: Dyspnea is the most common symptom in acute heart failure (AHF), yet how to best measure it has not been well defined. Prior studies demonstrate differences in dyspnea improvement across various measurement scales, yet these studies typically enroll patients well after the emergency department (ED) phase of management. OBJECTIVES: The aim of this study was to determine predictors of early dyspnea improvement for three different, commonly used dyspnea scales (i.e., five-point absolute Likert scale, 10-cm visual analog scale [VAS], or seven-point relative Likert scale). METHODS: This was a post hoc analysis of URGENT Dyspnea, an observational study of 776 patients in 17 countries enrolled within 1 hour of first physician encounter. Inclusion criteria were broad to reflect real-world clinical practice. Prior literature informed the a priori definition of clinically significant dyspnea improvement. Resampling-based multivariable models were created to determine patient characteristics significantly associated with dyspnea improvement. RESULTS: Of the 524 AHF patients, approximately 40% of patients did not report substantial dyspnea improvement within the first 6 hours. Baseline characteristics were similar between those who did or did not improve, although there were differences in history of heart failure, coronary artery disease, and initial systolic blood pressure. For those who did improve, patient characteristics differed across all three scales, with the exception of baseline dyspnea severity for the VAS and five-point Likert scale (c-index ranged from 0.708 to 0.831 for each scale). CONCLUSIONS: Predictors of early dyspnea improvement differ from scale to scale, with the exception of baseline dyspnea. Attempts to use one scale to capture the entirety of the dyspnea symptom may be insufficient.

The burden of acute heart failure on U.S. emergency departments.

OBJECTIVES: The goal of this study was to examine 2006 to 2010 emergency department (ED) admission rates, hospital procedures, lengths of stay, and costs for acute heart failure (AHF). BACKGROUND: Patients with AHF are often admitted and are associated with high readmissions and cost. METHODS: We utilized Nationwide Emergency Department Sample AHF data from 2006 to 2010 to describe admission proportion, hospital length of stay (LOS), and ED charges as a surrogate for resource utilization. Results were compared across U.S. regions, patient insurance status, and hospital characteristics. RESULTS: There were 958,167 mean yearly ED visits for AHF in the United States. Fifty-one percent of the patients were female, and the median age was 75.1 years (interquartile range [IQR]: 62.5 to 83.7 years). Overall, 83.7% (95% confidence interval: 83.1% to 84.2%) were admitted; the median LOS was 3.4 days (IQR: 1.9 to 5.8 days). Comparing 2006 with 2010, there was a small decrease in median LOS (0.09 days), but the proportion admitted did not change. Odds of admission, adjusting for age, sex, hospital characteristic (academic and safety net status), and insurance (Medicare, Medicaid, private, self-pay/no charge) were highest in the Northeast. Median ED charges were $1,075 (IQR: $679 to $1,665) in 2006 and $1,558 (IQR: $1,018 to $2,335) in 2010. Patients without insurance were more likely to be discharged from the ED, but when admitted, were more likely to receive a major diagnostic or therapeutic procedure. CONCLUSIONS: A very high proportion of ED patients with AHF are admitted nationally, with significant variation in disposition and procedural decisions based on region of the country and type of insurance, even after adjusting for potential confounding.

Validation of the Confusion Assessment Method for the Intensive Care Unit in older emergency department patients.

OBJECTIVES: In the emergency department (ED), health care providers miss delirium approximately 75% of the time, because they do not routinely screen for this syndrome. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is a brief (<1 minute) delirium assessment that may be feasible for use in the ED. The study objective was to determine its validity and reliability in older ED patients. METHODS: In this prospective observational cohort study, patients aged 65 years or older were enrolled at an academic, tertiary care ED from July 2009 to February 2012. An emergency physician (EP) and research assistants (RAs) performed the CAM-ICU. The reference standard for delirium was a comprehensive (~30 minutes) psychiatrist assessment using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. All assessments were blinded to each other and were conducted within 3 hours. Sensitivities, specificities, and likelihood ratios were calculated for both the EP and the RAs using the psychiatrist's assessment as the reference standard. Kappa values between the EP and RAs were also calculated to measure reliability. RESULTS: Of 406 patients enrolled, 50 (12.3%) had delirium. The median age was 73.5 years old (interquartile range [IQR] = 69 to 80 years), 202 (49.8%) were female, and 57 (14.0%) were nonwhite. The CAM-ICU's sensitivities were 72.0% (95% confidence interval [CI] = 58.3% to 82.5%) and 68.0% (95% CI = 54.2% to 79.2%) in the EP and RAs, respectively. The CAM-ICU's specificity was 98.6% (95% CI = 96.8% to 99.4%) for both raters. The negative likelihood ratios (LR-) were 0.28 (95% CI = 0.18 to 0.44) and 0.32 (95% CI = 0.22 to 0.49) in the EP and RAs, respectively. The positive likelihood ratios (LR+) were 51.3 (95% CI = 21.1 to 124.5) and 48.4 (95% CI = 19.9 to 118.0), respectively. The kappa between the EP and RAs was 0.92 (95% CI = 0.85 to 0.98), indicating excellent interobserver reliability. CONCLUSIONS: In older ED patients, the CAM-ICU is highly specific, and a positive test is nearly diagnostic for delirium when used by both the EP and RAs. However, the CAM-ICU's sensitivity was modest, and a negative test decreased the likelihood of delirium by a small amount. The consequences of a false-negative CAM-ICU are unknown and deserve further study.

Moving toward comprehensive acute heart failure risk assessment in the emergency department: the importance of self-care and shared decision making.

Nearly 700,000 emergency department (ED) visits were due to acute heart failure (AHF) in 2009. Most visits result in a hospital admission and account for the largest proportion of a projected $70 billion to be spent on heart failure care by 2030. ED-based risk prediction tools in AHF rarely impact disposition decision making. This is a major factor contributing to the 80% admission rate for ED patients with AHF, which has remained unchanged over the last several years. Self-care behaviors such as symptom monitoring, medication taking, dietary adherence, and exercise have been associated with decreased hospital readmissions, yet self-care remains largely unaddressed in ED patients with AHF and thus represents a significant lost opportunity to improve patient care and decrease ED visits and hospitalizations. Furthermore, shared decision making encourages collaborative interaction between patients, caregivers, and providers to drive a care path based on mutual agreement. The observation that "difficult decisions now will simplify difficult decisions later" has particular relevance to the ED, given this is the venue for many such issues. We hypothesize patients as complex and heterogeneous as ED patients with AHF may need both an objective evaluation of physiologic risk as well as an evaluation of barriers to ideal self-care, along with strategies to overcome these barriers. Combining physician gestalt, physiologic risk prediction instruments, an evaluation of self-care, and an information exchange between patient and provider using shared decision making may provide the critical inertia necessary to discharge patients home after a brief ED evaluation.

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 DTS's 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.

Risk stratification in acute heart failure: rationale and design of the STRATIFY and DECIDE studies.

BACKGROUND: A critical challenge for physicians facing patients presenting with signs and symptoms of acute heart failure (AHF) is how and where to best manage them. Currently, most patients evaluated for AHF are admitted to the hospital, yet not all warrant inpatient care. Up to 50% of admissions could be potentially avoided and many admitted patients could be discharged after a short period of observation and treatment. Methods for identifying patients that can be sent home early are lacking. Improving the physician's ability to identify and safely manage low-risk patients is essential to avoiding unnecessary use of hospital beds. METHODS: Two studies (STRATIFY and DECIDE) have been funded by the National Heart Lung and Blood Institute with the goal of developing prediction rules to facilitate early decision making in AHF. Using prospectively gathered evaluation and treatment data from the acute setting (STRATIFY) and early inpatient stay (DECIDE), rules will be generated to predict risk for death and serious complications. Subsequent studies will be designed to test the external validity, utility, generalizability and cost-effectiveness of these prediction rules in different acute care environments representing racially and socioeconomically diverse patient populations. RESULTS: A major innovation is prediction of 5-day as well as 30-day outcomes, overcoming the limitation that 30-day outcomes are highly dependent on unpredictable, post-visit patient and provider behavior. A novel aspect of the proposed project is the use of a comprehensive cardiology review to correctly assign post-treatment outcomes to the acute presentation. CONCLUSIONS: Finally, a rigorous analysis plan has been developed to construct the prediction rules that will maximally extract both the statistical and clinical properties of every data element. Upon completion of this study we will subsequently externally test the prediction rules in a heterogeneous patient cohort.

Assessment of the Framingham risk factors among ED patients with newly diagnosed atrial fibrillation.

STUDY OBJECTIVE: Atrial fibrillation (AF) is often first diagnosed in the emergency department (ED) and accounts for nearly 1% of all emergency department (ED) visits. Our objective was to assess the Framingham Heart Study risk score for AF development in ED patients with newly diagnosed AF. METHODS: We systematically reviewed the electronic medical records of ED patients with newly diagnosed AF between August 2005 and July 2008. We measured the frequency of the Framingham Heart Study predictors and calculated each patient's risk score. RESULTS: During the 3-year study period, 914 patients had 1228 ED visits. New AF was diagnosed in 296 (32%) patients. Among these patients, 107 (36%) were female, 127 (43%) had prior ED visits since 2003, 189 (64%) were taking hypertension medications and 170 (57.4%) had previous electrocardiograms with measurable PR intervals. The median PR interval was 166 ms (151 to 180) and 60% of available PR intervals were 160 ms or greater. The median (interquartile range) age, body mass index, and systolic blood pressure were 66 years (53-77), 27 (23-31), and 134 mm Hg (118-151), respectively. Median risk score was 7 (3-9) indicating high predicted risk. Heart failure and cardiac murmurs were previously diagnosed in 45 (15%) and 32 (11%) of these patients, respectively. CONCLUSIONS: The Framingham risk factors for AF are commonly encountered among ED patients with newly diagnosed AF. The ED might provide an opportunity to identify patients at high risk for AF and refer them for primary prevention interventions.

An evaluation of statewide emergency department utilization following Tennessee Medicaid disenrollment.

OBJECTIVES: During a series of reforms to the Tennessee Medicaid expansion program (TennCare) in 2005, approximately 171,000 adults were disenrolled from Medicaid. The objective of this study was to examine the statewide effect of such a disenrollment on Tennessee emergency department (ED) utilization. METHODS: Administrative data on all ED visits in Tennessee from 2004 through 2006 were obtained from the State Emergency Department Database and State Inpatient Database under the Healthcare Utilization Project. Population statistics and uninsured estimates were obtained from the U.S. Census Bureau, and TennCare enrollment data were obtained from the State of Tennessee Department of TennCare. The proportion and rate of ED visits, assessed separately by payer type, were compared across a predisenrollment period from January 1, 2004, through July 31, 2005, and across a postdisenrollment period from August 1, 2005, through December 31, 2006. The proportion and rate of ED visits resulting in hospital admission, again assessed separately by payer type, were compared across the same disenrollment periods in a similar way. We fitted a series of linear models for the total number of ED visits and each proportion and rate, with various degrees of adjustment for seasonality and time trend. RESULTS: The mean number of ED visits was 45,662 per week during the predisenrollment period and 44,463 per week during the postdisenrollment period (mean difference = -1,199; 95% confidence interval [CI] -1,722 to -676). By payer category, there was a decrease of 3,119 visits per week by TennCare beneficiaries and an increase of 2,203 per week by the uninsured. After disenrollment, the absolute proportion of ED visits by TennCare beneficiaries significantly decreased by 6.2% (95% CI = -6.6% to -5.8%), and the absolute proportion of uninsured ED visits increased by 5.3% (95% CI = 4.9% to 5.7%). The rate of ED visits by TennCare beneficiaries decreased by -0.091 ED visits/person/year (95% CI = -0.136 to -0.046) in the disenrollment period when controlling for time and seasonality. The rate of ED visits among the uninsured increased by 0.038 ED visits/person/year (95% CI = 0.011 to 0.065) in the postdisenrollment period when controlling for cubic time trend. The proportion of all TennCare ED visits that resulted in hospital admission did not change significantly between the two periods after adjusting for time trend and seasonality. The proportion of uninsured ED visits resulting in hospital admission, however, significantly increased after disenrollment by 2.0% (95% CI = 1.8% to 2.2%) and by 0.6% (95% CI = 0.0% to 1.2%) after adjusting for time and seasonality. CONCLUSIONS: The TennCare disenrollment of 2005 was associated with a modest decrease in the number of total ED visits in Tennessee. However, the payer mix among the Tennessee ED population shifted abruptly. The increased rate of ED visits by Tennessee's uninsured and the increased proportion of uninsured ED visits leading to hospital admission suggest an increased burden of illness in this highly vulnerable population.

Cost-effectiveness analysis of ED decision making in patients with non-high-risk heart failure.

BACKGROUND: The ED disposition of patients with non-high-risk acute decompensated heart failure (ADHF) is challenging. To help address this problem, we investigated the cost-effectiveness of different ED disposition strategies. METHODS: We constructed a decision analytic model evaluating the cost-effectiveness of 3 possible ED ADHF disposition strategies in a 60-year-old man: (1) discharge home from the ED; (2) observation unit (OU) admission; (3) inpatient admission. Base case patients had no high-risk features. We used Medicare costs and the national physician fee schedule to capture ED, OU, and hospital costs, including costs of complications and death. All analyses were conducted using Decision Maker software (University of Medicine and Dentistry of New Jersey, Newark, NJ). RESULTS: Compared to ED discharge, OU admission had a reasonable marginal cost-effectiveness ratio ($44 249/quality adjusted life year), whereas hospital admission had an unacceptably high marginal cost-effectiveness ratio ($684 101/quality adjusted life year). Sensitivity analyses demonstrated that as the risk of early (within 5 days) and late (within 30 days) readmission exceeded 36% and 74%, respectively, in those discharged from the ED, OU admission became less costly and more effective than ED discharge. Similarly, an increase in relative risk of both early and late death in those discharged from the ED improves the marginal cost-effectiveness ratio of OU admission. Finally, as postdischarge event rates increase in those discharged from the OU, hospital admission became more cost-effective. CONCLUSION: Observation unit admission for patients with non-high-risk ADHF has a societally acceptable marginal cost-effectiveness ratio compared to ED discharge. However, as ED and OU discharge event rates increase, hospital admission becomes the more cost-effective strategy.

Alignment of emergency medicine research efforts with Clinical and Translational Science Awards.

The Clinical and Translational Science Awards (CTSA) represent a major new funding pathway for health science investigators seeking National Institutes of Health (NIH) funds. This new pathway provides institutional-level support for clinical and translational research and is not tied to one organ system or disease process, fitting well with emergency medicine (EM) research needs. These awards open unique opportunities for advancing EM research. The CTSA mechanism provides institutional support from the NIH to promote both clinical and translational science. Of the 60 expected awards, 38 sites are currently funded. EM investigators can benefit the institutions applying for these awards and simultaneously gain from involvement. Some opportunities for participation provided by the CTSA include research training programs, joining multidisciplinary research teams, seed grant funding, and use of the CTSA-developed research infrastructure. Involvement of EM can benefit institutions by enhancing acute care research collaboration both within and among institutions. Emergency medicine researchers at institutions either planning to submit a CTSA application or with funded CTSA grants are encouraged to become actively involved in CTSA-related research programs.