Emergency departments (ED) worldwide have experienced dramatic increases in crowding over the past 20 years that now have reached critical levels. One consequence of ED crowding has been the routine use of ED hallways for patient care. This includes ED patients who are awaiting care but are considered unstable to remain in the waiting room, patients who are undergoing active medical and trauma treatment, and patients who have been stabilized but await transfer to an inpatient bed (boarding) or another institution. Compared with licensed hospital or standard ED beds, care in ED hallways results in increased patient morbidity and mortality, as well as patient and staff dissatisfaction. Complications experienced by hallway patients include unrecognized sudden respiratory arrest or unstable cardiac arrhythmias, delay in time-sensitive procedures and laboratory testing, delay in receiving important medications, excessive or unrelieved pain, overall increased length of stay, increased disability, and exposure to traumatic psychological events. While much has been published on the general problems of ED crowding, only recently have studies focused exclusively on the issues of providing care in ED hallways. This review summarizes the current issues, challenges, and solutions for hallway care.

John R. Richards

M. Christien van der Linden

Robert W. Derlet

Providing Care in Emergency Department Hallways: Demands, Dangers, and Deaths

Objectives. Emergency departments (EDs) and elective hospitalizations compete for beds. Our aim was to reduce hospital transfers using a queuing-model study. Methods. Macros were created to simulate four priority groups of patients according to hospitalization mode (elective, ED) and age (&#x2265;75 and &#x3c;75 years), with randomization of number of admissions and length of stay (LOS). Those priorities were assigned regarding usual situations (ED admission with less priority than scheduled admission) not regarding clinical contexts. Simulations were based on actual data from an academic hospital. Models simulated ED boarder queue according to different scenarios based on number of hospital beds, LOS, and preventable hospitalizations. Results. Observed hospital-LOS was longer for patients &#x2265;75 years (12.2 &#xb1; 3.6 days versus 11.4 &#xb1; 3.8 days; <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.6617603pt" id="M1" height="9.65971pt" version="1.1" viewBox="-0.0498162 -8.99795 46.7259 9.65971" width="46.7259pt"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g><g transform="matrix(.0135,0,0,-0.0135,12.15,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g><g transform="matrix(.0135,0,0,-0.0135,23.887,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.0135,0,0,-0.0135,30.39,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.0135,0,0,-0.0135,33.48,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,39.983,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g></svg>) and for ED admissions (12.2 &#xb1; 0.6 versus 9.7 &#xb1; 0.6 days; <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.6617603pt" id="M2" height="9.65971pt" version="1.1" viewBox="-0.0498162 -8.99795 46.7259 9.65971" width="46.7259pt"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.0135,0,0,-0.0135,12.15,0)"><use xlink:href="#g117-91"/></g><g transform="matrix(.0135,0,0,-0.0135,23.887,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,30.39,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.0135,0,0,-0.0135,33.48,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,39.983,0)"><use xlink:href="#g113-50"/></g></svg>). In simulation models, two scenarios stabilized the beds demand after admissions: limitation of LOS to 30 days or 20&#x25; decrease in elective admissions among older patients. With these scenarios, the queue would be 25.2 patients for 361 beds (+2&#x25;) and 16.7 patients for 354 beds. Conclusions. Queuing models offer an interesting approach to bed management. A significant reduction in ED transfers is feasible, by limiting LOS to &#x3c;30 days or by reducing elective hospitalizations of patients by 20&#x25;.

M. Wargon

N. Taright

E. Casalino

D. Pateron

B. Guidet

A Simulated Discrete-Event and Queuing Model to Reduce Transfers from the Emergency Department and to Optimize Hospital Bed Management

Introduction. Following the Hillsborough disaster, there is a requirement for crowd doctors to be present during football matches. However, there are little data on long-term trends in utilisation of crowd doctor services at sporting events. Methods. A retrospective service evaluation of presentations to the crowd doctor for 18 consecutive English Football League seasons: 13 seasons at Northampton Town Football Club (NTFC) followed by five seasons at Leicester City Football Club (LCFC). Data were analysed to determine the reason for, and severity of, presentation and the magnitude of the intervention required. Results. There were 429 recorded presentations to the crowd doctor over the 18 seasons. Patients&#x2019; age ranged from 3 to 93 years. 76&#x25; of presentations were due to an injury or illness arising at the match. The majority of presentations were with minor ailments (76&#x25;) requiring only minor intervention (88&#x25;); there were a small number of life-threatening presentations (1&#x25;) including three cardiac arrests. Conclusion. Crowd doctors may see patients in all age groups, presenting in a variety of ways. Most patients will have minor symptoms, but occasionally patients present with life-threatening problems. The crowd doctor must be competent assessing and treating all of these potential patient groups and pathologies.

Thomas P. Heinink

Andrew W. Fogarty

Matthew D. Wiles

Trends in Demand for Acute Medical Care at Two Football Clubs over an Eighteen-Year Period

Background. The Manchester Triage Scale is used in Irish emergency departments. This fails to provide guidance on triaging psychiatric presentations. A Mental Health Triage scale is recommended by the National Institute of Clinical Excellence. Aim. To examine the effectiveness of a Mental Health Triage scale in assessing patients presenting with self-harm. Method. Ten vignettes were created, detailing cases of deliberate self-harm. Nurses (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2130003pt" id="M1" height="8.91176pt" version="1.1" viewBox="-0.0498162 -8.69876 35.534 8.91176" width="35.534pt"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path id="g113-111" d="M495 86L479 114C446 82 419 66 409 66C401 66 401 72 406 97C420 166 436 231 453 297C489 435 454 448 428 448C406 448 384 439 354 422C305 394 222 327 161 247H159L183 345C200 415 194 448 173 448C143 448 82 410 23 351L38 325C64 349 95 371 105 371C111 371 116 365 109 336L25 -4L31 -12C50 -4 77 3 107 9C119 69 132 122 145 168C197 254 321 381 370 381C387 381 393 374 378 305L329 95C309 17 320 -12 345 -12C372 -12 430 19 495 86Z"/></g><g transform="matrix(.0135,0,0,-0.0135,10.586,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g><g transform="matrix(.0135,0,0,-0.0135,22.324,0)"><path id="g113-53" d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z"/></g><g transform="matrix(.0135,0,0,-0.0135,28.828,0)"><path id="g113-58" d="M244 635C114 635 38 519 38 422C38 317 111 240 217 240C236 240 255 244 277 256L345 292C311 140 203 39 59 15L64 -15C89 -15 150 -5 204 17C339 72 440 202 440 386C440 521 368 635 244 635ZM228 602C326 602 352 479 352 390C352 370 351 347 348 324C327 308 293 296 258 296C174 296 124 369 124 458C124 517 152 602 228 602Z"/></g></svg>) were given five vignettes and asked to assign each vignette to a triage category, using The Manchester Triage Scale. Each nurse was subsequently asked to reevaluate the same vignettes using the Mental Health Triage Scale. Triage with each method was deemed safe or unsafe, using the benchmark triage categories assigned by a consultant in psychiatry and a consultant in emergency medicine departments. Results. 245 cases were triaged. There was a significant change in the categories assigned when the Mental Health Triage scale was in use, <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.6617603pt" id="M2" height="9.65971pt" version="1.1" viewBox="-0.0498162 -8.99795 53.2534 9.65971" width="53.2534pt"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g><g transform="matrix(.0135,0,0,-0.0135,12.15,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g><g transform="matrix(.0135,0,0,-0.0135,23.887,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.0135,0,0,-0.0135,30.39,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.0135,0,0,-0.0135,33.48,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,39.983,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,46.486,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g></svg>. The triage categories assigned using the Mental Health Triage scale were significantly safer than under the Manchester Triage Scale (79% versus 60% safe, respectively, <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.6617603pt" id="M3" height="9.65971pt" version="1.1" viewBox="-0.0498162 -8.99795 53.2534 9.65971" width="53.2534pt"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><use xlink:href="#g113-81"/></g><g transform="matrix(.0135,0,0,-0.0135,12.15,0)"><use xlink:href="#g117-91"/></g><g transform="matrix(.0135,0,0,-0.0135,23.887,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,30.39,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.0135,0,0,-0.0135,33.48,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,39.983,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.0135,0,0,-0.0135,46.486,0)"><use xlink:href="#g113-50"/></g></svg>).

Richard Tanner

Eugene Cassidy

Iomhar O&#x2019;Sullivan

Does Using a Standardised Mental Health Triage Assessment Alter Nurses Assessment of Vignettes of People Presenting with  Deliberate Self-Harm

Objectives. To assess the impact of a scribe program on an academic, tertiary care facility. Methods. A retrospective analysis of emergency department (ED) data, prior to and after scribe program implementation, was used to quantitatively assess the impact of the scribe program on measures of ED throughput. An electronic survey was distributed to all emergency medicine residents and advanced practice providers to qualitatively assess the impact of the scribe program on providers. Results. Several throughput time measures were significantly lower in the postscribe group, compared to prescribe implementation, including time to disposition. The left without being seen (LWBS) decrease was not statistically significant. A total of 30 providers responded to the survey. 100&#x25; of providers indicated scribes are a valuable addition to the department and they enjoy working with scribes. 90&#x25; of providers indicated scribes increase their workplace satisfaction and quality of life. Conclusions. Through evaluation of prescribe and postscribe implementation, the postscribe time period reflects many throughput improvements not present before scribes began. Scribe Program implementation led to improved ED throughput for discharged patients with further system-wide challenges needing to be addressed for admitted patients.

Brandon Allen

Ben Banapoor

Emily C. Weeks

Thomas Payton

An Assessment of Emergency Department Throughput and Provider Satisfaction after the Implementation of a Scribe Program

Objectives. The time emergency department (ED) patients spend from presentation to admittance is known as their length of stay (LOS). This study aimed to quantify the inpatient occupancy rate (InptOcc)/ED LOS relationship and develop a methodology for identifying resource-allocation triggers using InptOcc-LOS association-curve inflection points. Methods. This study was conducted over 200 consecutive days at a 700-bed hospital with an annual ED census of approximately 50,000 using multivariate spline (piecewise) regression to model the InptOcc/LOS relationship while adjusting for confounding covariates. Nonlinear modeling was used to assess for InptOcc/LOS associations and determine the inflection point where InptOcc profoundly impacted LOS. Results. At lower InptOcc, there was no association. Once InptOcc reached &#x2265;88&#x25;, there was a strong InptOcc/LOS association; each 1&#x25; InptOcc increase predicted a 16-minute (95&#x25; CI, 12&#x2013;20 minutes) LOS prolongation, while the confounder-adjusted analysis showed each 1&#x25; InptOcc increase &#x3e;89&#x25; precipitating a 13-minute (95&#x25; CI, 10&#x2013;16 minutes) LOS prolongation. Conclusions. The study hospital&#x2019;s InptOcc was a significant predictor of prolonged ED LOS beyond the identified inflection point. Spline regression analysis identified a clear inflection point in the InptOcc-LOS curve that potentially identified a point at which to optimize inpatient bed availability to prevent increased costs of prolonged LOS.

Lori Whelan

Boyd Burns

Michael Brantley

Tyler Haas

Annette O. Arthur

Stephen H. Thomas

Mathematical Modeling of the Impact of Hospital Occupancy: When Do Dwindling Hospital Beds Cause ED Gridlock?

Aim. The aim of this study was to carry out an audit of healthcare plans in New Zealand and Oman. Methods. The study utilizes a deductive content analysis method. Written plans from New Zealand District Health Boards (DHBs) and the Omani secondary and tertiary hospitals were analyzed. A checklist was used to score the plans against twelve elements which are command and control, hazard analysis, surge capability, communication, standard operating procedures (SOPs), life-line backups, public and media, training, welfare, coordination, and recovery. Results. There were 14 plans from New Zealand and 7 plans from Oman analysed. The overall coverage of New Zealand plans was 67.5&#x25; compared to 53.3&#x25; in Oman. Plans from both countries scored similarly in &#x201C;command and control,&#x201D; &#x201C;hazard analysis,&#x201D; &#x201C;surge,&#x201D; and &#x201C;communication&#x201D; elements. Omani plans scored lower than those of New Zealand in &#x201C;media and the publicv&#x201D; &#x201C;training,&#x201D; &#x201C;coordination,&#x201D; and &#x201C;recovery.&#x201D; Both countries scored very low in addressing the welfare of responders. Conclusion. This study highlighted the value of health emergency plans in New Zealand as reflected by the high score of DHBs&#x2019; coordination. Therefore, a similar approach in Oman will enhance emergency preparedness. Responders&#x2019; welfare is an issue that needs to be addressed by emergency preparedness plans in both countries.

Sultan Al-Shaqsi

Robin Gauld

David McBride

Ammar Al-Kashmiri

Abdullah Al-Harthy

The State of Healthcare Disaster Plans in New Zealand and the Sultanate of Oman: An International Comparative Analysis

Objectives. We sought to validate and refine a decision rule for chest X-ray (CXR) utilization in nontraumatic chest pain (CP) patients presenting to the emergency department (ED). Methods. Retrospective review of ED patients presenting with CP who had CXR performed during three nonconsecutive months was performed. The presence of 18 variables derived from history and exam was ascertained. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the original rule were calculated. Refinement using additional variables was performed. Results. 967 patient charts were reviewed. 89.9&#x25; of CXR were normal, 5.2&#x25; had insignificant findings, and 5.1&#x25; had significant findings. Application of the criteria had a sensitivity/specificity of 74&#x25;/59&#x25; and a PPV/ NPV of 9&#x25;/98&#x25;. Rule modification to obtain CXR for age &#x2265; 65 years, history of congestive heart failure and alcohol abuse, and exam findings of decreased breath sounds, fever, and tachypnea maintained sensitivity while improving specificity to 69&#x25;. Conclusions. Most CP patients have normal CXRs. Narrowing a decision rule to obtain CXR in patients with age &#x2265; 65 years, history of congestive heart failure and alcohol abuse, and exam findings of decreased breath sounds, fever, and tachypnea maintain sensitivity while improving specificity and NPV.

Case Newsom

Rebecca Jeanmonod

Karl Weller

Nabil Boutros

Mark Reiter

Donald Jeanmonod

Validation of a Decision Rule and Derivation of a Modified Rule to Obtain Chest Radiograph in Patients with Nontraumatic Chest Pain in the Emergency Department

Objective. To determine the common presenting problems for young people attending the emergency department. Design. A retrospective review of electronic patient records of all young people between the ages of 13 and 17 who attended a UK University Hospital ED between 07/02/2007 and 06/02/2008 (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.1560001pt" id="M1" height="8.41101pt" version="1.1" viewBox="0 -8.25501 52.9555 8.41101" width="52.9555pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g50-111" d="M504 89L488 119C453 85 428 69 416 69C408 69 405 75 412 102L462 304C492 438 460 451 436 451S388 441 356 423C311 397 229 336 170 256H168L189 340C208 418 200 451 177 451C144 451 82 413 24 352L40 322C65 345 98 369 108 369C114 369 119 363 112 335L28 -3L36 -12C54 -3 83 4 112 10C125 73 138 122 153 174C205 258 328 382 376 382C395 382 399 369 384 305L330 93C312 25 323 -12 351 -12C378 -12 439 21 504 89Z"/></g><g transform="matrix(.013,0,0,-0.013,10.332,0)"><path id="g54-34" d="M556 331V384H55V331H556ZM556 140V193H55V140H556Z"/></g><g transform="matrix(.013,0,0,-0.013,21.95,0)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g><g transform="matrix(.013,0,0,-0.013,28.281,0)"><path id="g50-49" d="M245 635C92 635 37 457 37 312C37 149 91 -12 244 -12C395 -12 449 166 449 312C449 469 395 635 245 635ZM243 598C332 598 358 454 358 312C358 173 334 26 245 26C158 26 128 174 128 313S152 598 243 598Z"/></g><g transform="matrix(.013,0,0,-0.013,34.612,0)"><path id="g50-53" d="M462 177V227H365V632H320C217 496 116 350 21 208V177H284V109C284 43 280 38 190 31V0H451V31C369 38 365 43 365 108V177H462ZM284 227H88C155 336 218 430 282 519H284V227Z"/></g><g transform="matrix(.013,0,0,-0.013,40.943,0)"><path id="g50-54" d="M158 548H390L417 615L410 623H122L83 318C105 326 143 337 185 337C296 337 350 275 350 188C350 116 308 42 225 42C164 42 122 74 100 93C90 101 82 99 72 92C60 82 51 68 50 59C48 46 52 38 66 24C82 9 125 -12 172 -12C225 -11 292 15 346 59C408 108 437 166 437 226C437 309 371 397 242 397C214 397 170 382 133 369L158 548Z"/></g><g transform="matrix(.013,0,0,-0.013,47.274,0)"><use xlink:href="#g50-54"/></g></svg>). Results. All emergency department attendances for young people over a one-year period were studied in order to determine the common presenting problems. There were a total of 10455 attendances by 8303 young people. The presenting problem in 7505 (71.8&#x25;) was classified as injury. Of the remainder the commonest presenting problems reported for young people were abdominal pain (480, 16.3&#x25;), self-harm (314, 10.6&#x25;), fits, faints and funny turns (308, 10.4&#x25;), breathing difficulty (213, 7.2&#x25;), and intoxication (178, 6.0&#x25;). Ten presenting problems accounted for 72&#x25; of noninjury related attendances. Conclusions. Clinical guidelines and pathways developed for young people attending the emergency department should target the commonest presenting problems. In our cohort ten presenting problems account for almost three-quarters of all noninjury attendances for young people. The presenting problems are different to those described in younger children in previous studies. These results will inform the development of clinical pathways in order to improve emergency care.

Dhurgshaarna Shanmugavadivel

Rebecca Sands

Damian Wood

Common Presenting Problems for Young People Attending the Emergency Department

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Advances in Emergency Medicine