Skip to main content
SpringerLink
Log in

Emergency Department of the New Era

  • Chapter
The Modern Hospital

  • 961 Accesses

Abstract

The past 10 years have demonstrated a dramatic evolution in how patients are cared for overall. The emergency department (ED) is where technologic solution has the potential to be most helpful because of the unpredictable, time-sensitive nature of patient logistics. In this chapter we review the evolution of these approaches as they relate to the problems they address.

The availability of patient data may be the single greatest challenge and opportunity in the ED setting. The transition to electronic medical records and then electronic health records and the promise of networked health information exchanges are reviewed.

Patient flow is a problem that vexes nearly every ED. How to pair the right resources and the right patient in a prompt, cost-effective manner is a challenge which in the modern ED can be assuaged by a variety of approaches. The most common include the application of queuing theory, and lean methodology, in addition to simpler approaches such as adjustments to the triage liaison provider and separation of low-acuity patients.

Clinical documentation is a problem in nearly every healthcare setting, but the ED highlights this workflow bottleneck. The use of medical scribes, speech recognition software, and wearable computing devices has all shown promise, but each comes with their distinct advantages and disadvantages.

Finally, clinical decision support, crowd-sourced open-access medical information, the ED application of telemedicine, prehospital testing, and point-of-care testing are discussed. This chapter provides an overview of how the challenges of a modern ED are met with modern solutions and provides the evidence supporting these changes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

APP:

Advanced practice provider

BPA:

Best practice alert

CDS:

Clinical decision support

CPOE:

Computerized physician order entry

ECG:

Electrocardiogram

ED:

Emergency department

EHR:

Electronic health record

EMR:

Electronic medical record

EMS:

Emergency medical services

FOAM:

Free open-access medical education

HIE:

Health information exchange

MI:

Myocardial infarction

POC:

Point of care

QT:

Queuing theory

STEMI:

ST-segment elevation myocardial infarction

TLP:

Triage liaison provider

t-PA:

Tissue plasminogen activator

US:

Ultrasound

WCD:

Wearable computing device

References

  1. Rothenhaus T, et al. Information systems for emergency care: American College of Emergency Physicians; 2009.

    Google Scholar 

  2. Kerr K, Norris T. Improving health care data quality: a practitioner’s perspective. Int J Inf Qual. 2008;2(1):39–59.

    Google Scholar 

  3. Hsiao C, et al. Electronic medical record/electronic health record systems of office-based physicians: 2009 and preliminary 2010 state estimates. National Center for Health Statistics, November 2011.

    Google Scholar 

  4. Ben-Assuli O. Electronic health records, adoption, quality of care, legal and privacy issues and their implementation in emergency departments. Health Policy. 2015;119(3):287–97.

    PubMed  Google Scholar 

  5. Miranda ML, Ferranti J, Strauss B. Geographic health information systems: a platform to support the ‘triple aim’. Health Aff. 2013;32(9):1608–15.

    Google Scholar 

  6. Stiell A, et al. Prevalence of information gaps in the Emergency Department and the effect on patient outcomes. CMAJ. 2003;169(10):1023–8.

    PubMed  PubMed Central  Google Scholar 

  7. Remen VM, Grimsmo A. Closing information gaps with shared electronic patient summaries: how much will it matter? Int J Med Inform. 2011;80(11):775–81.

    PubMed  Google Scholar 

  8. Jensen SA, et al. Erroneous drug charts: a health hazard? Tidsskr Nor Laegeforen. 2003;123:3598–9.

    PubMed  Google Scholar 

  9. Evans RS. Electronic health records: then, now, and in the future. Yearb Med Inform. 2016;Suppl 1:S48–61.

    CAS  PubMed  Google Scholar 

  10. Vest JR, et al. Factors motivating and affecting health information exchange usage. J Am Med Inform Assoc. 2011;18(2):143–9.

    PubMed  PubMed Central  Google Scholar 

  11. Bahous MC, Shadmi E. Health information exchange and information gaps in referrals to a pediatric emergency department. Int J Med Inform. 2016;87:68–74.

    PubMed  Google Scholar 

  12. Vest JR, Kaushal R, Silver MD. Health information exchange and the frequency of repeat medical imaging. Am J Manag Care. 2014;20(11):eSP16–24.

    PubMed  Google Scholar 

  13. Vest JR, et al. Association between use of a health information exchange system and hospital admissions. Appl Clin Inform. 2014;5(1):219–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Wilcox AB, Shen S, Dorr DA. Improving access to longitudinal patient health information within an emergency department. Appl Clin Inform. 2012;3(3):290–300.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Ben-Assuli O, Shabtai I, Leshno M. Using electronic health record systems to optimize admission decisions: the Creatinine case study. Health Informatics J. 2015;21(1):73–88.

    PubMed  Google Scholar 

  16. Flaks-Manov N, et al. Health information exchange systems and length of stay in readmissions to a different hospital. J Hosp Med. 2016;11(6):401–6.

    PubMed  Google Scholar 

  17. Vest JR, Kern LM, Silver MD. The potential for community-based health information exchange systems to reduce hospital readmissions. J Am Med Inform Assoc. 2015;22(2):435–42.

    PubMed  Google Scholar 

  18. Carr CM, et al. Observational study and estimate of cost savings from use of a health information exchange in an academic emergency department. J Emerg Med. 2014;46(2):250–6.

    PubMed  Google Scholar 

  19. Saef SH, Melvin CL, Carr CM. Impact of a health information exchange on resource use and Medicare-allowable reimbursements at 11 emergency departments in a midsized city. West J Emerg Med. 2014;15(7):777–85.

    PubMed  PubMed Central  Google Scholar 

  20. Neri PM, Redden L, Poole S. Emergency medicine resident physicians’ perceptions of electronic documentation and workflow: a mixed methods study. Appl Clin Inform. 2015;6(1):27–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Dexheimer JW, Borycki EM. Use of mobile devices in the emergency department: a scoping review. Health Informatics J. 2015;21(4):306–15.

    PubMed  Google Scholar 

  22. Schooley B, et al. Impacts of mobile tablet computing on provider productivity, communications, and the process of care. Int J Med Inform. 2016;88:62–70.

    PubMed  Google Scholar 

  23. Fleischmann R, Duhm J, Hupperts H, Brandt SA. Tablet computers with mobile electronic medical records enhance clinical routine and promote bedside time: a controlled prospective crossover study. J Neurol. 2015;262(3):532–40.

    PubMed  Google Scholar 

  24. Prgomet M, Georgiou A, Westbrook JI. The impact of mobile handheld technology on hospital physicians’ work practices and patient care: a systematic review. J Am Med Inform Assoc. 2009;16(6):792–801.

    PubMed  PubMed Central  Google Scholar 

  25. Horng S, et al. Prospective pilot study of a tablet computer in an Emergency Department. Int J Med Inform. 2012;81(5):314–9.

    PubMed  PubMed Central  Google Scholar 

  26. Strayer SM, et al. Patient attitudes toward physician use of tablet computers in the exam room. Fam Med. 2010;42(9):643–7.

    PubMed  Google Scholar 

  27. Duhm J, Fleischmann R, Schmidt S, et al. Mobile electronic medical records promote workflow: physicians’ perspective from a survey. JMIR Mhealth Uhealth. 2016;4(2):e70.

    PubMed  PubMed Central  Google Scholar 

  28. O’Connell TW, Patlas MN. Mobile devices and their prospective future role in emergency radiology. Br J Radiol. 2016;89(1061):20150820.

    PubMed  PubMed Central  Google Scholar 

  29. Singh N, et al. Tablet-based patient-centered decision support for minor head injury in the emergency department: pilot study. JMIR Mhealth Uhealth. 2017;5(9):e144.

    PubMed  PubMed Central  Google Scholar 

  30. Finn NB. Collaboration, communication and connection: fostering patient engagement in health care. J Participat Med. 2012;4:e20.

    Google Scholar 

  31. Purcell K. Half of adult cell phone owners have apps on their phones. [Online] Pew Internet Research, 2011. http://pewinternet.org/Reports/2011/Apps-update.aspx.

  32. Radhakrishna K, et al. Electronic health records and information portability: a pilot study in a rural primary healthcare center in India. Perspect Health Inf Manag. 2014;11:1b.

    PubMed  PubMed Central  Google Scholar 

  33. Huang LC, Chu HC, Lien CY, et al. Privacy preservation and information security protection for patients’ portable electronic health records. Comput Biol Med. 2009;39(9):743–50.

    PubMed  Google Scholar 

  34. Coats B, Acharya S. Leveraging the cloud for electronic health record access. Perspect Health Inf Manag. 2014;11:1g.

    PubMed  PubMed Central  Google Scholar 

  35. Institute of Medicine. Hospital-based emergency care: at the breaking point. Washington DC: National Academies Press; 2006.

    Google Scholar 

  36. Wilper AP, Woolhandler S, Lasser KE. Waits to see an emergency department physician: U.S. trends and predictors, 1997-2004. Health Aff. 2008;27:w84–95.

    Google Scholar 

  37. Horwitz LI, Bradley EH. Percentage of US emergency department patients seen within the recommended triage time: 1997 to 2006. Arch Intern Med. 2009;169:1857–65.

    PubMed  PubMed Central  Google Scholar 

  38. McCarthy ML, Zeger SL, Ding R. Crowding delays treatment and lengthens emergency department length of stay, even among high acuity patients. Ann Emerg Med. 2009;54:492–503.

    PubMed  Google Scholar 

  39. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med. 2008;15:825–31.

    PubMed  Google Scholar 

  40. Pines JM, Pollack CV Jr, Diercks DB, et al. The association between emergency department crowding and adverse cardiovascular outcomes in patients with chest pain. Acad Emerg Med. 2009;16:617–25.

    PubMed  Google Scholar 

  41. Chalfin DB, Trzeciak S, Likourezos A, et al. Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit. Crit Care Med. 2007;35:1477–83.

    PubMed  Google Scholar 

  42. Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med. 2008;52:126–36.

    PubMed  Google Scholar 

  43. Rui P, Kang K. National Hospital Ambulatory Medical Care Survey: 2014 Emergency Department Summary Tables. Center for Disease Control. [Online] [Cited: February 19, 2018.] https://www.cdc.gov/nchs/data/nhamcs/web_tables/2014_ed_web_tables.pdf.

  44. Peters ML. The older adult in the emergency department: aging and atypical illness presentation. J Emerg Nurs. 2010;36:29–34.

    PubMed  Google Scholar 

  45. Pines JM. Trends in the rates of radiography use and important diagnoses in emergency department patients with abdominal pain. Med Care. 2009;47:782–6.

    PubMed  Google Scholar 

  46. Hsia RY, Kellermann AL, Shen YC. Factors associated with closures of emergency departments in the United States. JAMA. 2011;305:1978–85.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Bullard MJ, Villa-Roel C, Bond K. Tracking emergency department overcrowding in a tertiary care academic institution. Healthc Q. 2009;12:99–106.

    PubMed  Google Scholar 

  48. Pines JM, Batt RJ, Hilton JA, Terwiesch C. The financial consequences of lost demand and reducing boarding in hospital emergency departments. Ann Emerg Med. 2011;58:331–40.

    PubMed  Google Scholar 

  49. Gupta, D. Queueing models for healthcare operations. [book auth.] BT Denton. Handbook of healthcare operations management: methods and applications. New York : Springer, 2013.

    Google Scholar 

  50. Cochran JK, Roche KT. A multi-class queueing network analysis methodology for improving hospital emergency department performance. Comput Oper Res. 2009;36:1497–512.

    Google Scholar 

  51. Lakshmi C, Sivakumar AI. Application of queueing theory in health care: a literature review. Operations Research for Health Care. 2013;2:25–39.

    Google Scholar 

  52. McCarthy ML, et al. The challenge of predicting demand for emergency department services. Acad Emerg Med. 2008;15:337–46.

    PubMed  Google Scholar 

  53. Gupta D, Denton BT. Appointment scheduling in health care: challenges and opportunities. IIE Trans. 2008;40(9):800–19.

    Google Scholar 

  54. Moll HA. Challenges in the validation of triage systems at emergency departments. J Clin Epidemiol. 2010;63:384–8.

    PubMed  Google Scholar 

  55. Konrad R, et al. Modeling the impact of changing patient flow processes in an emergency department: insights from a computer simulation study. Operations Research for Health Care. 2013;2:66–74.

    Google Scholar 

  56. Green LV, Kolesar PJ, Whitt W. Coping with time-varying demand when setting staffing requirements for a service system. Prod Oper Manag. 2007;16:13–39.

    Google Scholar 

  57. Green LV, et al. Using queueing theory to increase the effectiveness of emergency department provider staffing. Acad Emerg Med. 2006;13(1):61–8.

    PubMed  Google Scholar 

  58. Alavi-Moghaddam M, Forouzanfar R, Alamdari S, et al. Application of queuing analytic theory to decrease waiting times in emergency department: does it make sense? Arch Trauma Res. 2012;1(3):101–7.

    PubMed  PubMed Central  Google Scholar 

  59. Fitzgerald K, Pelletier L, Reznek MA. A queue-based Monte Carlo analysis to support decision making for implementation of an emergency department fast track. J Health Eng. 2017;4:1–8.

    Google Scholar 

  60. Laker LF, et al. The flex track: flexible partitioning between low- and high-acuity areas of an emergency department. Ann Emerg Med. 2014;64(6):591–603.

    PubMed  PubMed Central  Google Scholar 

  61. Fujimoto T. The evolution of a manufacturing system at Toyota. New York: Oxford University Press; 1999.

    Google Scholar 

  62. Andersen H, Rovik KA, Ingbrigsten T. Lean thinking in hospitals: is there a cure for the absence of evidence? A systematic review of reviews. BMJ Open. 2014;4:e003873.

    PubMed  PubMed Central  Google Scholar 

  63. De Koning H, et al. Lean six sigma in healthcare. J Healthc Qual. 2006;28:4–11.

    PubMed  Google Scholar 

  64. Brandao De Souza L. Trends and approaches in lean healthcare. Leadersh Health Serv. 2009;22:121–39.

    Google Scholar 

  65. Villeneuve C. Fujitsu’s Lean Solutions Group - Lean Healthcare in Canada. Fujitsu Sci Tech J. 2011;47:41–8.

    Google Scholar 

  66. Migita R, et al. Emergency department overcrowding: developing emergency department capacity through process improvement. Clin Pediatr Emerg Med. 2011;12:141–50.

    Google Scholar 

  67. Bucci S, de Belvis AG, Marventano S. Emergency Department crowding and hospital bed shortage: is Lean a smart answer? A systematic review. Eur Rev Med Pharmacol Sci. 2016;20:4209–19.

    CAS  PubMed  Google Scholar 

  68. Young G, Wagner M, Kellermann A, Bouley E. Ambulatory visits to hospital emergency departments. Patterns and reasons for use. 24 Hours in the ED Study Group. JAMA. 1996;276(6):460–5.

    CAS  PubMed  Google Scholar 

  69. Durand A, Gentile S, Devictor B, et al. ED patients: how nonurgent are they? Systematic review of the emergency medicine literature. Am J Emerg Med. 2010;29(3):333–45.

    PubMed  Google Scholar 

  70. Northington W, Brice J, Zou B. Use of an emergency department by nonurgent patients. Am J Emerg Med. 2005;23:131–7.

    PubMed  Google Scholar 

  71. Carret M, Fassa A, Kawachi I. Demand for emergency health service: factors associated with inappropriate use. BMC Health Serv Res. 2007;7:131.

    PubMed  PubMed Central  Google Scholar 

  72. Phelps K, Taylor C, Kimmel S, Nagel R, Klein W, Puczynski S. Factors associated with emergency department utilization for nonurgent pediatric problems. Arch Fam Med. 2000;9:1086–92.

    CAS  PubMed  Google Scholar 

  73. Redstone P, Vancura J, Barry D, Kutner J. Nonurgent use of the emergency department. J Ambulatory Care Manage. 2008;31(4):370–6.

    PubMed  Google Scholar 

  74. Eastwood K, Morgans A, Smith K, et al. Appropriateness of cases presenting in the emergency department following ambulance service secondary telephone triage: a retrospective cohort study. BMJ Open. 2017;7(10):e016845.

    PubMed  PubMed Central  Google Scholar 

  75. Takakuwa KM, Shofer FS, Abbuhl SB. Strategies for dealing with emergency department overcrowding: a one-year study on how bedside registration affects patient throughput times. J Emerg Med. 2007;32(4):337–42.

    PubMed  Google Scholar 

  76. Roberts L, Dykes L. Emergencies by appointment: would patients with minor injuries prefer a booked appointment at their local emergency department to the current walk-in service provision. Emerg Med J. 2014;31(9):786.

    Google Scholar 

  77. Yu KT, Green RA. Critical aspects of emergency department documentation and communication. Emerg Med Clin North Am. 2009;27(4):641–54.

    CAS  PubMed  Google Scholar 

  78. Velo GP, Minuz P. Medication errors: prescribing faults and prescription errors. Br J Clin Pharmacol. 2009;67(6):624–8.

    PubMed  PubMed Central  Google Scholar 

  79. Awan S, Abid S, Tariq M. Use of medical abbreviations and acronyms: knowledge among medical students and postgraduates. Postgrad Med J. 2016;92:721–5.

    PubMed  Google Scholar 

  80. Yu FB, Menachemi N, Berner ES. Full implementation of computerized physician order entry and medication-related quality outcomes: a study of 3364 hospitals. Am J Med Qual. 2009;24(4):278–86.

    PubMed  PubMed Central  Google Scholar 

  81. Howard J, Clark EC, Friedman A. Electronic health record impact on work burden in small, unaffiliated, community-based primary care practices. J Gen Intern Med. 2013;28(1):107–13.

    PubMed  Google Scholar 

  82. Payne TH, Corley S, Cullen TA. Report of the AMIA EHR-2020 Task Force on the status and future direction of EHRs. J Am Med Inform Assoc. 2015;22(5):1102–10.

    PubMed  PubMed Central  Google Scholar 

  83. Basanti A, Walch R, Todd B. Computerized prescriber order entry decreases patient satisfaction and emergency center physician productivity. Ann Emerg Med. 2010;56(3):s83–4.

    Google Scholar 

  84. Farber NJ, Liu L, Chen Y. EHR use and patient satisfaction: what we learned. J Fam Pract. 2015;64(11):687–96.

    PubMed  Google Scholar 

  85. Shultz CG, Holmstrom HL. The use of medical scribes in health care settings: a systematic review and future directions. J Am Board Fam Med. 2015;28(3):371–81.

    PubMed  Google Scholar 

  86. Heaton HA, Nestler DM, Lohse CM. Impact of scribes on emergency department patient throughput one year after implementation. Am J Emerg Med. 2017;34(10).

    Google Scholar 

  87. Shuaib W, Hilmi J, Caballero J, Rashid I, Stanazai H, Tawfeek K, Amari A, Ajanovic A, Moshtaghi A, Khurana A, Hasabo H, Baqais A, Szczerba AJ, Gaeta TJ. Impact of a scribe program on patient throughput, physician productivity, and patient satisfaction in a community-based emergency department. Health Informatics J. 2017;35(2):311–4.

    Google Scholar 

  88. Bastani A, Shagiri B, Palomba K, Bananno D, Anderson W. An ED scribe program is able to improve throughput time and patient satisfaction. Am J Emerg Med. 2014;32(5):399–402.

    PubMed  Google Scholar 

  89. Hess JJ, Wallenstein J, Ackerman JD, Akhter M, Ander D, Keadey MT, Capes JP. Scribe impacts on provider experience, operations, and teaching in an academic emergency medicine practice. West J Emerg Med. 2015;16(5):602–10.

    PubMed  PubMed Central  Google Scholar 

  90. Heaton HA, Nestler DM, Jones DD, Varghese RS, Lohse CM, Williamson ES, Sadosty AT. Impact of scribes on billed relative value units in an academic emergency department. J Emerg Med. 2017;52(3):370–6.

    PubMed  Google Scholar 

  91. Johnson M, Lapkin S, Long V, et al. A systematic review of speech recognition technology in health care. BMC Med Inform Decis Mak. 2014;14(1):94.

    PubMed  PubMed Central  Google Scholar 

  92. Bliss MF. Speech recognition for the health professions: (using Dragon naturally speaking). Upper Saddler River, NJ: Prentice Hall; 2005.

    Google Scholar 

  93. Paulett JM, Langlotz CP. Improving language models for radiology speech recognition. J Biomed Inform. 2009;42(1):53–8.

    PubMed  Google Scholar 

  94. Gales M, Young S. The application of hidden Markov models in speech recognition. Found Trends Signal Process. 2008;1(3):197–203.

    Google Scholar 

  95. Eddy SR. What is a hidden Markov model? Nat Biotechnol. 2004;22(10):1315–6.

    CAS  PubMed  Google Scholar 

  96. Zick RG, Olsen J. Voice recognition software versus a traditional transcription service for physician charting in the ED. Am J Emerg Med. 2001;19(4):295–8.

    CAS  PubMed  Google Scholar 

  97. Vogel M, Kaisers W, Wassmuth R, Mayatepek E. Analysis of documentation speed using web-based medical speech recognition technology: randomized controlled trial. J Med Internet Res. 2015;17(11):e247.

    PubMed  PubMed Central  Google Scholar 

  98. Dela, JE, Shabosky, JC, Albrecht, M, Clark, M, Milbrandt, JC, Kegg, JA. Typed Versus Voice Recognition for Data Entry in Electronic Health Records: Emergency Physician Time Use and Interruptions. West J Emerg Med. 2014;15(4):541–74.

    Google Scholar 

  99. Hodgson T, Magrabi F, Coiera E. Efficiency and safety of speech recognition for documentation in the electronic health record. J Am Med Inform Assoc. 2017;24(6):1127–33.

    Google Scholar 

  100. Hodgson T, Coiera E. Risks and benefits of speech recognition for clinical documentation: a systematic review. J Am Med Inform Assoc. 2016;23(e1):e169–79.

    PubMed  Google Scholar 

  101. Goss FR, Zhou L, Weiner SG. Incidence of speech recognition errors in the emergency department. Int J Med Inform. 2016;93:70–3.

    PubMed  Google Scholar 

  102. Landman A, et al. A mobile app for securely capturing and transferring clinical images to the electronic health record: description and preliminary usability study. JMIR Mhealth Uhealth. 2015;3(1):e1.

    PubMed  PubMed Central  Google Scholar 

  103. Pecina JL, Wyatt KD, Comfere NI, Bernard ME, North F. Uses of mobile device digital photography of dermatologic conditions in primary care. JMIR Mhealth Uhealth. 2017;5(11):e165.

    PubMed  PubMed Central  Google Scholar 

  104. Hartman DJ, Parwani AV, Cable B, Cucoranu IC, McHugh JS, Kolowitz BJ, Yousem SA, Palat V, Reden AV, Sloka S, Lauro GR, Ahmed I, Pantanowitz L. Pocket pathologist: a mobile application for rapid diagnostic surgical pathology consultation. J Pathol Inform. 2014;5(1):10.

    PubMed  PubMed Central  Google Scholar 

  105. Kassutto SM, Kayser JB, Kerlin MP, Upton M, Lipschik G, Epstein AJ, Dine CJ, Schweickert W. Google glass video capture of cardiopulmonary resuscitation events: a pilot simulation study. J Grad Med Educ. 2017;9(6):748–54.

    PubMed  PubMed Central  Google Scholar 

  106. Swensen SJ, et al. Cottage industry to postindustrial care — the revolution in health care delivery. N Engl J Med. 2010;362:e12.

    PubMed  Google Scholar 

  107. Osheroff J, Teich J, Levick D, et al. Improving outcomes with clinical decision support: an implementer’s guide. 2nd ed. Chicago: HIMSS; 2012.

    Google Scholar 

  108. Damiani G, Pinnarelli L, Colosimo SC, et al. The effectiveness of computerized clinical guidelines in the process of care: a systematic review. BMC Health Serv Res. 2010;10:2.

    PubMed  PubMed Central  Google Scholar 

  109. Bright TJ, Wong A, Dhurjati R, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29–43.

    PubMed  Google Scholar 

  110. Hurley SF, Dziukas LJ, McNeil JJ. A randomized controlled clinical trial of pharmacokinetic theophylline dosing. AJRCCM. 1986;134(6):1219–24.

    Google Scholar 

  111. Evans RS, Pestotnik SL, Classen DC, et al. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med. 1998;338:232–8.

    CAS  PubMed  Google Scholar 

  112. Burton ME, Ash CL, Hill DP. A controlled trial of the cost benefit of computerized bayesian aminoglycoside administration. Clin Pharmacol Ther. 1991;49:685–94.

    CAS  PubMed  Google Scholar 

  113. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:742–52.

    PubMed  Google Scholar 

  114. Gupta A, Ip IK, Raja AS, et al. Effect of clinical decision support on documented guideline adherence for head CT in emergency department patients with mild traumatic brain injury. J Am Med Inform Assoc. 2014;21:e347–51.

    PubMed  PubMed Central  Google Scholar 

  115. Britton DJ, et al. Impact of a computerized order set on adherence to Centers for Disease Control guidelines for the treatment of victims of sexual assault. J Emerg Med. 2013;44:528–35.

    PubMed  Google Scholar 

  116. Garg AX, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. JAMA. 2005;293(10):1223–38.

    CAS  PubMed  Google Scholar 

  117. Dean NC, et al. Impact of an electronic clinical decision support tool for emergency department patients with pneumonia. Ann Emerg Med. 2015;66(5):511–20.

    PubMed  Google Scholar 

  118. Curtis CE, Bahar FA, Marriot JF. The effectiveness of computerised decision support on antibiotic use in hospitals: a systematic review. PLoS One. 2017;12(8):e0183062.

    PubMed  PubMed Central  Google Scholar 

  119. Landman AB. The potential for clinical decision support to improve emergency care. Ann Emerg Med. 2015;66(5):521–2.

    PubMed  Google Scholar 

  120. Nickson CP, Cadogan MD. Free Open Access Medical education (FOAM) for the emergency physician. Emerg Med Aust. 2014;26(1):76–83.

    Google Scholar 

  121. Young PJ, Nickson CP, Gantner DC. Can social media bridge the gap between research and practice? Crit Care Resp. 2013;15:257–9.

    Google Scholar 

  122. Eysenbach G. Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. J Med Internet Res. 2011;13:e123.

    PubMed  PubMed Central  Google Scholar 

  123. Allen HG, et al. Social media release increases dissemination of original articles in the clinical pain sciences. PLoS One. 2013;8:e68914.

    CAS  PubMed  PubMed Central  Google Scholar 

  124. Reiter DA, Lakoff DJ, Trueger NS, et al. Individual interactive instruction: an innovative enhancement to resident education. Ann Emerg Med. 2013;61:110–3.

    PubMed  Google Scholar 

  125. Stuntz R, Clontz R. An evaluation of emergency medicine core content covered by Free Open Access Medical Education resources. Ann Emerg Med. 2016;67(5):649–653.e2.

    PubMed  Google Scholar 

  126. Grock A, Paolo W. Free open access medical education: a critical appraisal of techniques for quality assessment and content discovery. Clin Exp Emerg Med. 2016;3(3):183–5.

    PubMed  PubMed Central  Google Scholar 

  127. Physicians, American College of Emergency. Emergency medicine telemedicine. Ann Emerg Med. 2016;67(5):687–9

    Google Scholar 

  128. Zachrison KS, Hayden EM, Schwamm LH. Characterizing New England emergency departments by telemedicine use. West J Emerg Med. 2017;18(6):1055–60.

    PubMed  PubMed Central  Google Scholar 

  129. Mohr NM, Young T, Harland KK. Emergency department telemedicine shortens rural time-to-provider and emergency department transfer times. Telemed J E Health. 2018;24(8):582–93.

    PubMed  Google Scholar 

  130. du Toit, M, Malau-Aduli, B and Vangaveti, V. Use of telehealth in the management of non-critical emergencies in rural or remote emergency departments: a systematic review. J Telemed Telecare. 2017.

    Google Scholar 

  131. Wilson MH, et al. Pre-hospital emergency medicine. Lancet. 2016;387(10020):2526–34.

    Google Scholar 

  132. Chiara O, Scott JD, Cimbanassi S. Trauma deaths in an Italian urban area: an audit of pre-hospital and in-hospital trauma care. Injury. 2002;33:553–62.

    PubMed  Google Scholar 

  133. Kyriacou E, et al. Emergency health care information systems. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:2501–4.

    CAS  PubMed  Google Scholar 

  134. Antman EM, Anbe DT, Armstrong PW, et al. CC/AHA guidelines for the management of patients with ST-elevation myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2007;115(15):296–329.

    Google Scholar 

  135. Curtis JP, et al. The pre-hospital electrocardiogram and time to reperfusion in patients with acute myocardial infarction, 2000–2002: findings from the national registry of myocardial infarction-4. JACC. 2006;47(8):1544–52.

    PubMed  Google Scholar 

  136. Chen KC, et al. Effect of emergency department in-hospital tele-electrocardiographic triage and interventional cardiologist activation of the infarct team on door-to-balloon times in ST-segment-elevation acute myocardial infarction. Am J Cardiol. 2011;107(10):1430–5.

    PubMed  Google Scholar 

  137. Saver JL. Time is brain—quantified. Stroke. 2006;37(1):263–6.

    PubMed  Google Scholar 

  138. Group, The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study. Tissue plasminogen activator for acute ischemic stroke. N Engl J Med. 1995;333(24):1581–7.

    Google Scholar 

  139. Fonarow GC, Smith EE, Saver JL, et al. Timeliness of tissue-type plasminogen activator therapy in acute ischemic stroke: patient characteristics, hospital factors, and outcomes associated with door-to-needle times within 60 minutes. Circulation. 2011;123(7):750–8.

    CAS  PubMed  Google Scholar 

  140. Fassbender K, Balucani C, Walter S. Streamlining of prehospital stroke management: the golden hour. Lancet Neurol. 2013, 12(6):585–96.

    Google Scholar 

  141. Minnerup J, et al. Effects of emergency medical service transport on acute stroke care. Eur J Neurol. 2014;21(10):1344–7.

    CAS  PubMed  Google Scholar 

  142. Buck BH, et al. Dispatcher recognition of stroke using the National Academy Medical Priority Dispatch System. Stroke. 2009;40(6):2027–30.

    PubMed  PubMed Central  Google Scholar 

  143. Jones SP, et al. The identification of acute stroke: an analysis of emergency calls. Int J Stroke. 2013;8(6):408–12.

    PubMed  Google Scholar 

  144. Ramanujam P, Guluma KZ, Castillo EM. Accuracy of stroke recognition by emergency medical dispatchers and paramedics--San Diego experience. Prehosp Emerg Care. 2008;12(3):307–13.

    PubMed  Google Scholar 

  145. Mason J. Mobile stroke units for prehospital care of ischemic stroke. CADTH Issues in Emerging Health Technologies. 2017.

    Google Scholar 

  146. John S, et al. Brain imaging using mobile CT: current status and future prospects. J Neuro Img. 2015;26(1):5–15.

    Google Scholar 

  147. Spahn DR, Bouillon B, Cerny V, et al. Management of bleeding and coagulopathy following major trauma: an updated European guideline. Crit Care. 2013;17(2):R76.

    PubMed  PubMed Central  Google Scholar 

  148. Melniker LA, et al. Randomized controlled clinical trial of point-of-care, limited ultrasonography for trauma in the emergency department: the first sonography outcomes assessment program trial. Ann Emerg Med. 2006;48(3):227–35.

    PubMed  Google Scholar 

  149. Hasler RM, et al. Accuracy of prehospital diagnosis and triage of a Swiss helicopter emergency medical service. J Trauma Acute Care Surg. 2012;73(3):709–15.

    PubMed  Google Scholar 

  150. Walcher F, et al. Prehospital ultrasound imaging improves management of abdominal trauma. Br J Surg. 2006;93(2):238–42.

    CAS  PubMed  Google Scholar 

  151. Mazur SM, et al. Use of point-of-care ultrasound by a critical care retrieval team. Emerg Med Australas. 2007;19(6):547–52.

    PubMed  Google Scholar 

  152. Fernandes CM, Tanabe P, Gilboy N, et al. Five-level triage: a report from the ACEP/ENA Five-level Triage Task Force. J Emerg Nurs. 2005;31:39–50.

    PubMed  Google Scholar 

  153. Oredsson S, Jonsson H, Rognes J, et al. A systematic review of triage-related interventions to improve patient flow in emergency departments. Scand J Trauma Resusc Emerg Med. 2011;19:43.

    PubMed  PubMed Central  Google Scholar 

  154. Holroyd BR, et al. Impact of a triage liaison physician on emergency department overcrowding and throughput: a randomized controlled trial. Acad Emerg Med. 2007;14:702.

    PubMed  Google Scholar 

  155. Rogg JG, et al. A long-term analysis of physician triage screening in the emergency department. Acad Emerg Med. 2013;20(4):374–80.

    PubMed  Google Scholar 

  156. Abdulwahid MA, et al. The impact of senior doctor assessment at triage on emergency department performance measures: systematic review and meta-analysis of comparative studies. Emerg Med J. 2016;33(7):504–13.

    PubMed  Google Scholar 

  157. Weston V, Jain S, Gottlieb M, et al. Effectiveness of resident physicians as triage liaison providers in an academic emergency department. West J Emerg Med. 2017;18(4):577–84.

    PubMed  PubMed Central  Google Scholar 

  158. Nestler DM, Fratzke AR, Church CJ, et al. Effect of a physician assistant as triage liaison provider on patient throughput in an academic emergency department. Acad Emerg Med. 2012;19(11):1235–41.

    PubMed  PubMed Central  Google Scholar 

  159. Wuerz R, Milne LW, Eitel DR, Travers D, Gilboy N. Reliability and validity of a new five-level triage instrument. Acad Emerg Med. 2000;7(3):236–42.

    CAS  PubMed  Google Scholar 

  160. Wuerz R. Emergency Severity Index triage category is associated with six-month survival. ESI triage study group. Acad Emerg Med. 2001;8(1):61–4.

    CAS  PubMed  Google Scholar 

  161. Green NA, Durani Y, Brecher D, DePiero A, Loiselle J, Attia M. Emergency Severity Index version 4: a valid and reliable tool in pediatric emergency department triage. Pediatr Emerg Care. 2012;28(8):753–7.

    PubMed  Google Scholar 

  162. Rooney KD, Schilling UM. Point-of-care testing in the overcrowded emergency department: can it make a difference? Crit Care. 2014;18:692.

    PubMed  PubMed Central  Google Scholar 

  163. Graff L, Palmer AC, Lamonica P, et al. Triage of patients for a rapid (5-minute) electrocardiogram: a rule based on presenting chief complaints. Ann Emerg Med. 2000;36(6):554–60.

    CAS  PubMed  Google Scholar 

  164. Lee-Lewandrowski E, Nichols J, Van Cott E, et al. Implementation of a rapid whole blood D-dimer test in the emergency department of an urban academic medical center: impact on ED length of stay and ancillary test utilization. Am J Clin Pathol. 2009;132(3):326–31.

    CAS  PubMed  Google Scholar 

  165. Koehler J, Flarity K, Hertner G, et al. Effect of troponin I Point-of-Care testing on emergency department throughput measures and staff satisfaction. Adv Emerg Nurs J. 2013;35(3):270–7.

    PubMed  Google Scholar 

  166. Cooper JJ, Datner EM, Pines JM. Effect of an automated chest radiograph at triage protocol on time to antibiotics in patients admitted with pneumonia. Am J Emerg Med. 2008;26(3):264–9.

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Acute Care Surgery, InterTrauma Medical, New York, NY, USA

    Alejandro Guerrero

  2. Department of Emergency Medicine, UC Davis Health, UC Davis Medical Center, UC Davis School of Medicine, Sacramento, CA, USA

    David K. Barnes

  3. Department of Emergency Medicine, UC Davis Medical Center, Sacramento, CA, USA

    Hunter M. Pattison

Authors
  1. Alejandro Guerrero
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David K. Barnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hunter M. Pattison
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alejandro Guerrero .

Editor information

Editors and Affiliations

  1. New York Medical College, School of Medicine, Department of Surgery and Westchester Medical Center, Valhalla, NY, USA

    Rifat Latifi

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Cite this chapter

Guerrero, A., Barnes, D.K., Pattison, H.M. (2019). Emergency Department of the New Era. In: Latifi, R. (eds) The Modern Hospital. Springer, Cham. https://doi.org/10.1007/978-3-030-01394-3_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-01394-3_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01393-6

  • Online ISBN: 978-3-030-01394-3

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation