Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32586
A Continuous Real-Time Analytic for Predicting Instability in Acute Care Rapid Response Team Activations

Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward


A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1352


[1] Kause J, Smith G, Prytherch D, Parr M, Flabouris A, Hillman K. A comparison of antecedents to cardiac arrests, deaths and emergency intensive care admissions in Australia and New Zealand, and the United Kingdom—the ACADEMIA study. Resuscitation. 2004;62(3):275–82.
[2] Johnston MJ, Arora S, King D, Bouras G, Almoudaris AM, Davis R, et al. A systematic review to identify the factors that affect failure to rescue and escalation of care in surgery. Surgery. 2015;157(4):752–63.
[3] Mitchell IA, McKay H, Van Leuvan C, Berry R, McCutcheon C, Avard B, et al. A prospective controlled trial of the effect of a multi-faceted intervention on early recognition and intervention in deteriorating hospital patients. Resuscitation. 2010;81(6):658–66.
[4] Silber JH, Williams SV, Krakauer H, Schwartz JS. Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care. 1992;615–29.
[5] Brennan TA, Localio AR, Leape LL, Laird NM, Peterson L, Hiatt HH, et al. Identification of adverse events occurring during hospitalization: a cross-sectional study of litigation, quality assurance, and medical records at two teaching hospitals. Ann Intern Med. 1990;112(3):221–6.
[6] Harvey EM, Echols SR, Clark R, Lee E. Comparison of two TeamSTEPPS® Training Methods on nurse failure-to-rescue performance. Clin Simul Nurs. 2014;10(2):e57–64.
[7] Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–92.
[8] Fagan K, Sabel A, Mehler PS, MacKenzie TD. Vital sign abnormalities, rapid response, and adverse outcomes in hospitalized patients. Am J Med Qual. 2012;27(6):480–6.
[9] Jones DA, DeVita MA, Bellomo R. Rapid-response teams. N Engl J Med. 2011;365(2):139–46.
[10] Smith GB, Prytherch DR, Schmidt P, Featherstone PI, Knight D, Clements G, et al. Hospital-wide physiological surveillance–a new approach to the early identification and management of the sick patient. Resuscitation. 2006;71(1):19–28.
[11] Chua WL, Mackey S, Ng EKC, Liaw SY. Front line nurses’ experiences with deteriorating ward patients: a qualitative study. Int Nurs Rev. 2013;60(4):501–9.
[12] Mok W, Wang W, Cooper S, Ang ENK, Liaw SY. Attitudes towards vital signs monitoring in the detection of clinical deterioration: scale development and survey of ward nurses. Int J Qual Health Care. 2015;27(3):207–13.
[13] Sankey CB, McAvay G, Siner JM, Barsky CL, Chaudhry SI. “Deterioration to Door Time”: An Exploratory Analysis of Delays in Escalation of Care for Hospitalized Patients. J Gen Intern Med. 2016;31(8):895–900.
[14] Bates DW, Zimlichman E. Finding patients before they crash: the next major opportunity to improve patient safety. BMJ Publishing Group Ltd; 2015.
[15] Spaulding A, Ohsfeldt R. Rapid response teams and team composition: a cost-effectiveness analysis. Nurs Econ. 2014;32(4):194–204.
[16] Chan PS, Jain R, Nallmothu BK, Berg RA, Sasson C. Rapid response teams: a systematic review and meta-analysis. Arch Intern Med. 2010;170(1):18–26.
[17] Sulistio M, Franco M, Vo A, Poon P, William L. Hospital rapid response team and patients with life-limiting illness: a multicentre retrospective cohort study. Palliat Med. 2015;29(4):302–9.
[18] Barwise A, Thongprayoon C, Gajic O, Jensen J, Herasevich V, Pickering BW. Delayed rapid response team activation is associated with increased hospital mortality, morbidity, and length of stay in a tertiary care institution. Crit Care Med. 2016;44(1):54–63.
[19] Considine J, Jones D, Pilcher D, Currey J. Physiological status during emergency department care: relationship with inhospital death after clinical deterioration. Crit Care Resusc. 2015;17(4):257–62.
[20] Fasolino T, Verdin T. Nursing surveillance and physiological signs of deterioration. MedSurg Nurs. 2015;24(6):397–403.
[21] Bingham G, Fossum M, Barratt M, Bucknall T. Clinical review criteria and medical emergency teams: evaluating a two-tier rapid response system. Crit Care Resusc. 2015;17(3):167.
[22] Asensio JA, McDuffie L, Petrone P, Roldán G, Forno W, Gambaro E, et al. Reliable variables in the exsanguinated patient which indicate damage control and predict outcome. Am J Surg. 2001;182(6):743–51.
[23] Shoemaker WC, Wo CC, Chan L, Ramicone E, Kamel ES, Velmahos GC, et al. Outcome prediction of emergency patients by noninvasive hemodynamic monitoring. Chest. 2001;120(2):528–37.
[24] McManus J, Yershov AL, Ludwig D, Holcomb JB, Salinas J, Dubick MA, et al. Radial pulse character relationships to systolic blood pressure andtrauma outcomes. Prehosp Emerg Care. 2005;9(4):423–8.
[25] Wo CC, Shoemaker WC, Appel PL, Bishop MH, Kram HB, Hardin E. Unreliability of blood pressure and heart rate to evaluate cardiac output in emergency resuscitation and critical illness. Crit Care Med. 1993;21(2):218–23.
[26] Edmonds ZV, Mower WR, Lovato LM, Lomeli R. The reliability of vital sign measurements. Ann Emerg Med. 2002;39(3):233–7.
[27] Grant S, Crimmons K. Limitations of track and trigger systems and the National Early Warning Score. Part 2: sensitivity versus specificity. Br J Nurs. 2018;27(12):705–10.
[28] Downey CL, Tahir W, Randell R, Brown JM, Jayne DG. Strengths and limitations of early warning scores: a systematic review and narrative synthesis. Int J Nurs Stud. 2017;76:106–19.
[29] Koch E, Lovett S, Nghiem T, Riggs RA, Rech MA. Shock index in the emergency department: utility and limitations. Open Access Emerg Med OAEM. 2019;11:179.
[30] Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, et al. Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016 Feb 23;315(8):762–74.
[31] Stein PK, Bosner MS, Kleiger RE, Conger BM. Heart rate variability: A measure of cardiac autonomic tone. Am Heart J. 1994 May 1;127(5):1376–81.
[32] Kleiger RE, Miller JP, Bigger Jr JT, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987;59(4):256–62.
[33] Sztajzel J. Heart rate variability: a noninvasive electrocardiographic method to measure the autonomic nervous system. Swiss Med Wkly. 2004;134(35–36):514–22.
[34] Chen I-C, Kor C-T, Lin C-H, Kuo J, Tsai J-Z, Ko W-J, et al. High-frequency power of heart rate variability can predict the outcome of thoracic surgical patients with acute respiratory distress syndrome on admission to the intensive care unit: a prospective, single-centric, case-controlled study. BMC Anesthesiol. 2018;18(1):34.
[35] Gañán-Calvo AM, Fajardo-López J. Universal structures of normal and pathological heart rate variability. Sci Rep. 2016;6:21749.
[36] Belle A, Ansari S, Spadafore M, Convertino VA, Ward KR, Derksen H, et al. A signal processing approach for detection of hemodynamic instability before decompensation. PloS One. 2016;11(2):e0148544.
[37] Rao MH, Marella P, Kath B. Assessment of severity and outcome of critical illness. Indian J Anaesth. 2008;52:652–62.
[38] Mukkamala R, Reisner AT, Hojman HM, Mark RG, Cohen RJ. Continuous cardiac output monitoring by peripheral blood pressure waveform analysis. IEEE Trans Biomed Eng. 2006;53(3):459–67.
[39] Moulton SL, Mulligan J, Santoro MA, Bui K, Grudic GZ, MacLeod D. Validation of a noninvasive monitor to continuously trend individual responses to hypovolemia. J Trauma Acute Care Surg. 2017;83(1):S104–11.
[40] Pirracchio R, Cohen MJ, Malenica I, Cohen J, Chambaz A, Cannesson M, et al. Big data and targeted machine learning in action to assist medical decision in the ICU. Anaesth Crit Care Pain Med. 2019;38(4):377–84.
[41] Huang C-T, Tsai Y-J, Lin J-W, Ruan S-Y, Wu H-D, Yu C-J. Application of heart-rate variability in patients undergoing weaning from mechanical ventilation. Crit Care. 2014;18(1):R21.