287: Effect of Admitted Patient Boarder Occupancy Percentage on Emergency Department Length of Stay and Patients Leaving Without Treatment

Research Forum Abstracts Methods: Five emergency physicians (1 fellow, 4 residents) with experience in IVC assessment prospectively enrolled a convenience sample of ED patients with any of the following: chest pain, shortness of breath, abdominal pain, nausea/ vomiting. Two sonologists performed EUS on each patient (phased array probe, SonoSite MicroMaxx), and studies for which adequate views could not be obtained were later excluded. Sonologist 1 (S1) obtained transverse and longitudinal views of the IVC in subxiphoid and intercostal windows, and recorded a gestalt estimate of IVC-CI. In addition, S1 recorded whether the study suggested the patient required fluids, diuretics, or neither. S1 then obtained Mand B-mode clips and images for quantitative IVC-CI measurement. Within 15 minutes, the second sonologist 2 (S2) obtained the same images, blinded to S1 results. S1 and S2’s clips and measurements were independently reviewed by a single expert sonologist who made his own gestalt and quantitative IVC-CI estimates. Paired comparisons were made among sonologist and expert measurements. MedCalc was used to perform statistical analyses. Results: A total of 38 patients were evaluated. 59% were female, with a mean BSA of 1.91 ⫹ 0.32 m2 and heart rate of 88 ⫹ 16 bpm (⫹SD). Analysis using Pearson’s correlation coefficient between S1 and S2 revealed the following values for IVC-CI measurement methods (all values p⬍0.001): B-mode diameter, r⫽0.56; Area, r⫽0.54; Gestalt, r⫽ 0.64. Agreement was improved when comparing sonographers’ gestalt to expert gestalt (r⫽ 0.75). The correlation when asked if the patient should receive fluids or diuretics was r⫽0.64 and r⫽0.76, respectively. Conclusion: Different sonologists achieve a fair interrater reliability in quantitative IVC-CI measurements. Additionally, correlations among different sonologists’ qualitative gestalt estimates and those of an expert sonologist are reasonably good. There was good correlation when deciding the need for fluids or diuretics between the 2 studies based on gestalt IVC assessments. These results suggest that qualitative estimation of IVC-CI may be superior to traditional quantitative measurement when assessing volume status. This is an important finding in view of the time expenditure required for quantitative measurements. Further study is needed to determine whether gestalt IVC estimates are accurate predictors of intravascular volume status in ED patients, as well as to determine reasons for interrater variability with respect to quantitative measurements.

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Abstract Withdrawn

Is the Optic Nerve Sheath Diameter That is Measured by Ultrasonography Useful for Early Detection of Elevated Intracranial Pressure in Adult Patients?

Oh S, Kim S/Chungnam Univ. Hospital, Daejeon, Republic of Korea

Study Objectives: To evaluate the availability of the ONSD (optic nerve sheath diameter) that was measured by US (ultrasonography) to know if the intracranial pressure rose. Methods: This was a prospective study from October, 2007 to March, 2008. We excluded the patients who were less than 18 years, had already gotten ocular or periocular disease recently, had the abnormal Q test (Queckenstedtis test), or wasn‘t cooperative. The ONSDs of patients enrolled were measured by a 312MHz ultrasonographic probe on the closed eyelids. We analyzed the correlation between the CSF (cerebrospinal fluid) pressure and the ONSD. We divided these patients into group A (increased CSF pressure groupⱖ200mmHg) and group B (normal CSF pressure⬍200mmHg) to compare group A with group B and evaluate the availability of the ONSD. Results: There were 21 patients in group A and 70 patients in group B. The CSF pressure was correlated with the ONSD (Correlation Coefficient⫽0.54) (p⬍0.01). The mean of the binocular ONSDs in group A was 5.1⫾0.6mm and in group B, was 4.5⫾0.4mm (p⬍0.01). In the ROC curve (receiver operating characteristic curve) with the ONSD to distinguish group A from group B, AUC was 0.8(95% confidence interval 0.70.9) and the sensitivity was 81.0%, the specificity was 75.7% when we had the cut off value what was 4.7mm. Conclusion: We noticed the ONSD was related to the CSF pressure and there was the difference in the ONSD between group A and group B. The ONSD that was measured by US was useful to predict the high ICP.

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EMF-1

Bedside Emergency Physician Determination of Cardiac Output in Severe Sepsis

Chang J, Hwang J, Moore C/Yale University, New Haven, CT

Study Objective: Prior work has suggested that hyperdynamic function seen on bedside echocardiography (echo) may be predictive of sepsis. Additionally, some work has suggested that depressed myocardial function in sepsis may initially be cardioprotective while a high cardiac output state may indicate more severe sepsis. Assessment of cardiac output in sepsis may have implications for diagnosis, prognosis, or therapy. We sought to determine if there was any relationship between cardiac output determined by bedside emergency physician (EP) performed echo and mortality in patients with severe sepsis. Methods: Patients were enrolled on a convenience basis when one or more EP investigators who had met training criteria were available to enroll patients. Adult patients who presented to our emergency department with at least two of four systemic inflammatory response syndrome (SIRS) criteria, suspected or definite source of infection, and evidence of end-organ damage were eligible for enrollment. Bedside echo was performed using a Philips EnVisor HD11XE ultrasound to determine cardiac output (CO) using the method of stroke volume x heart rate, where stroke volume is determined by left ventricular outflow tract diameter and velocity time integral across the aortic outflow tract. The cardiac package included on the Philips machine was used to calculate cardiac output. Body surface area was used to calculate cardiac index. All echoes were recorded in their entirety on DVD and reviewed for adequacy by the primary investigator. Baseline data was collected including data necessary to calculate APACHE, SOFA, MODS and MEDS scores. Patients were followed to determine mortality during the hospital admission. Results: Sixty patients have been successfully enrolled so far. Mortality rate was 20% (12/60) during the hospital admission. Average age was 63 years (range 29-101), and was not significantly different between survivors and non-survivors. CO averaged 5.34 L/min and CI averaged 2.86 L/min/m2 in all patients, range 1.3-10.6 L/min (0.5-5.4 L/min/m2). CO and CI were slightly lower in patients who survived: 5.25 L/min and 2.85 L/min/m2 for survivors vs. 5.66 L/min and 2.91 L/min/m2 for nonsurvivors but this was not statistically significant (p⫽0.43 for CO, p⫽0.67 for CI). Qualitative assessment of cardiac function demonstrated 50% of non-survivors had a hyperdynamic LV while only 38% of survivors had a hyperdynamic LV (p-value 0.52). Conclusions: Cardiac output determined by bedside emergency physicianperformed echocardiography showed a trend towards being lower in survivors vs. non-survivors but was not statistically significant. A higher percentage of nonsurvivors had a hyperdynamic LV by qualitative assessment, but this was not statistically significant.

287

Effect of Admitted Patient Boarder Occupancy Percentage on Emergency Department Length of Stay and Patients Leaving Without Treatment

Nazziola E/Wilkes-Barre General Hospital, Wilkes-Barre, PA

Study Objectives: Emergency department (ED) crowding is a nationwide crisis. Admitted patient boarding (APB) in the ED has been identified as the main cause of this problem. However, a quantitative analysis of the relationship between admitted patient boarder occupancy percentage (APBOP) and established indicators of ED patient flow such as average length of stay (ALOS) and percentage of patients leaving without treatment (PLWOT) has not been published. This study reports the magnitude of the effect of APBOP on ALOS and PLWOT. Methods: The study setting was a 47,000 annual volume community hospital emergency department. Patient flow (ALOS and PLWOT) and occupancy (APBOP) data were retrospectively acquired from an electronic medical record database (Picis ED Pulse Check®). Data from all patient emergency department visits from January 1, 2007 through March 31, 2008 were included in this analysis. APBOP was recorded on a monthly basis. ALOS and PLWOT were recorded on a daily and monthly basis. APBOP was determined by dividing the total number of hours admitted patients boarded in the ED by the total number of available ED bed hours. ALOS was determined by taking the average of all patient lengths of stay during a defined time period. PLWOT was determined by dividing the number of patients leaving without being seen by the total number of patients presenting to the ED during a defined time period and multiplying by 100%. Statistical analyses including 95% confidence intervals and correlation coefficients were accomplished using QI Macros® 2008 with Microsoft Excel® 2003.

Annals of Emergency Medicine S129

Research Forum Abstracts Results: During the 15-month study period, 56,922 patients presented to the ED. Average daily patient volume was 125 patients (95% CI 124, 126). Average daily PLWOT was 5.3% (95% CI, 3.2%, 7.3%). ALOS of the entire study population was 4:47 (95% CI, 4:45, 4:49). Average monthly APBOP was 31% (95% CI, 8%, 54%). Monthly averages for APBOP, ALOS, and PLWOT are shown in Table 1.

that defining a set of critical data elements to be included in ED consults would promote both improved documentation and clear communication between consultants and emergency physicians. Quality measures will facilitate evaluation of new documentation protocols and QI initiatives around ED consultation elements and consultation quality measures using a modified Delphi process. Participants affirmed that defining a set of critical data elements to be included in ED consults would promote both improved documentation and clear communication between consultants and emergency physicians. Quality measures will facilitate evaluation of new documentation protocols and QI initiatives around ED consultation.

289

Emergency Department Crowding in the Commonwealth of Pennsylvania

Pines JM, Kelly JJ/University of Pennsylvania, Philadelphia, PA; Albert Einstein Medical Center, Philadelphia, PA

Statistical analysis of monthly averages has revealed an 88% correlation between APBOP and ALOS and a 78% correlation between APBOP and PLWOT. Conclusion: APBOP is highly correlated with ALOS and PLWOT. As ALOS and PLWOT are key indicators for ED patient flow, hospital administrative efforts aimed at reducing the admission boarder burden in the ED are likely to result in improved ED patient flow.

288

Defining Critical Data Elements to Improve Emergency Department Consultation Communication

Schuur JD, Qualls M, Moreau JF, Bohan SJ, Nathanson LA, Tibbles CT/Brigham and Women’s Hospital, Boston, MA; Harvard Medical School, Boston, MA; Beth Israel Deaconess Medical Center, Boston, MA

Study Objective: Specialty consultation is a frequently used yet little studied area of emergency care, which is at risk for errors resulting from poor communication. We aimed to bring emergency physicians to consensus about the critical data elements for ED consultations, as well as a set of consultation quality measures for use in ED quality improvement (QI) assessment. Methods: We developed an initial list of consult data elements based on literature review, stakeholder conversations and chart review. We refined the initial list through a modified Delphi Process involving approximately 15 emergency physicians and additional departmentally identified stakeholders from 7 hospitals (3 community and 4 academic medical centers) in a major Northeastern metropolitan area. The modified Delphi Process included a pre-meeting survey that asked participants to rank each data element on a 7-point scale reflecting the importance of each element (1⫽critical to 7⫽unimportant); a three-hour consensus meeting at which consultation care patterns, the data elements, and quality measures were discussed; and a post-meeting survey incorporating feedback from the meeting. We defined consensus as any data element with a median ⱕ2 or ⱖ 6 (IQR ⱕ3 or ⱖ 5). Results: We evaluated 37 consult data elements and 20 quality measures. We grouped the data elements in the following domains (# of elements): Demographic Data (2), Time points (6), Provider Involvement (8), Communication (1), Information Provided by Emergency Physician (3), Consultant Evaluation (3), Consultant Treatment Recommendations (7), Consultant Disposition Recommendations (4) and Procedural issues (3). All 37 elements met our a priori consensus standard. Eleven elements (30%) were deemed critical (rank⫽1) by at least 75% of participants. 17 quality measures met our a priori consensus standards. Two were deemed critical (rank⫽1) by at least 75% of participants: 1) Does hospital policy require attending to staff ED consults (or an explicit policy for each service) and 2) % of consults with documented real-time, closed-loop communication at consultation completion (e.g. “I spoke with consultant/EP about [final recommendations]”). Notably, conference participants also distinguished between two types of consults: 1) “Full Consultation” (when a consultant is asked to perform an in-person evaluation) and 2) “Limited Consultation” (when the clinical question is limited, and full, in-person evaluation is unnecessary; e.g. evaluate ECG for STEMI). They defined the relative importance of all data elements for both consult types. Conclusion: We were able to define critical ED consultation data elements and consultation quality measures using a modified Delphi process. Participants affirmed

S130 Annals of Emergency Medicine

Study Objectives: 1) To determine the prevalence of and trends in emergency department (ED) crowding in Pennsylvania (PA), 2) To query what measures have been used to improve crowding, whether they are working, and barriers to improvement. Methods: We conducted a survey of PA ED medical directors who are members of PA-ACEP about ED crowding; the survey was initiated by the PA-ACEP board of directors. Responses were collected over 6 months (ending 3/08). Results: There were 79 responses (response rate: 69%). The majority of EDs were community (67%), academic with an ED residency (17%), academic without a residency (16%). Yearly ED volume was 50K (24%). EDs were suburban (54%), urban (25%), and rural (21%). A total of 87% reported that ED crowding was a problem in their hospital. When asked what % of time the ED was crowded: 15% reported ⬍10%, 36% - 10-25%, 26% - 26-50%, and 23% - ⬎50%. When asked what happens when it is crowded, 98% agreed that patient satisfaction suffers, 98% staff satisfaction suffers, 81% - admitted patients are boarded for long periods, 77% quality of care suffers, 39% - ED goes on diversion, and 34% - the hospital devotes more resources to the ED. Regarding interventions used when the ED is crowded (most common answers listed): 89% reported that elective surgeries were NEVER cancelled, 82% reported that inpatients were NEVER moved to inpatient hallways, 72% reported that inpatient discharges were SOMETIMES expedited, 69% reported that ED patients were SOMETIMES prioritized over other admission sources, 48% reported that they NEVER stopped accepting hospital-to-hospital transfers. In the past 2 years, 65% thought that ED crowding was worse. Regarding strategies implemented in the past 2 years, 40% had hired more nurses, but 42% reported it had not reduced crowding. In the future, 45% planned to increase the ED size, 47% to increase hospital size, and 29% to open an ED observation unit. 46% had hired physician extenders; 59% had implemented ESI triage, 54% had improved ED operations and 52% had hired an ED bed manager. 80% had tried to board patients on inpatient hallways but were unable to and 47% had tried surgical schedule smoothing but were unable to. Regarding barriers, 61% did not have suitable human resources to improve crowding, 41% lacked suitable financial resources, and 57% stated that hospital administration was the primary barrier to improving crowding. Conclusion: ED crowding appears to a major issue in PA and has worsened over the past 2 years. While most agree on the negative consequences of ED crowding, only a small proportion of hospitals devote more resources to the ED during crowded times. Multiple strategies to improve crowding have been tried, but interventions that involve services outside the ED are largely unsuccessful. Major barriers to improve crowding are the lack of necessary human resources and hospital administration itself.

290

Implementation of a Novel “See and Treat” System Reduces Emergency Department Crowding

Codreanu T, Koenig KL, Bey T/Dr. Gray’s Hospital, Elgin, United Kingdom; University of California at Irvine, Orange, CA

Background: Patients with minor complaints account for a significant portion of emergency department (ED) visits and contribute to crowding. ED crowding has detrimental effects on patient waiting and throughput times. Study Objectives: To study the effects of implementation of a novel patient flow system on time to doctor and total ED times compared with traditional patient triage and treatment methods. Methods: The “See and Treat” (S&T) patient flow system was introduced into an urban ED (annual volume: 22,000) in Scotland in May 2007. Medically untrained receptionists assessed adult patients on arrival. Patients with chief complaints related to their head, chest or abdomen were referred to the waiting room for triage as per

Volume , .  : October 