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Journal of Clinical Monitoring and Computing

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Open Access 11-02-2021 | Original Research

Adaptive threshold-based alarm strategies for continuous vital signs monitoring

Authors: Mathilde C. van Rossum, Lyan B. Vlaskamp, Linda M. Posthuma, Maarten J. Visscher, Martine J. M. Breteler, Hermie J. Hermens, Cor J. Kalkman, Benedikt Preckel

Published in: Journal of Clinical Monitoring and Computing | Issue 2/2022

Abstract

Continuous vital signs monitoring in post-surgical ward patients may support early detection of clinical deterioration, but novel alarm approaches are required to ensure timely notification of abnormalities and prevent alarm-fatigue. The current study explored the performance of classical and various adaptive threshold-based alarm strategies to warn for vital sign abnormalities observed during development of an adverse event. A classical threshold-based alarm strategy used for continuous vital signs monitoring in surgical ward patients was evaluated retrospectively. Next, (combinations of) six methods to adapt alarm thresholds to personal or situational factors were simulated in the same dataset. Alarm performance was assessed using the overall alarm rate and sensitivity to detect adverse events. Using a wireless patch-based monitoring system, 3999 h of vital signs data was obtained in 39 patients. The clinically used classical alarm system produced 0.49 alarms/patient/day, and alarms were generated for 11 out of 18 observed adverse events. Each of the tested adaptive strategies either increased sensitivity to detect adverse events or reduced overall alarm rate. Combining specific strategies improved overall performance most and resulted in earlier presentation of alarms in case of adverse events. Strategies that adapt vital sign alarm thresholds to personal or situational factors may improve early detection of adverse events or reduce alarm rates as compared to classical alarm strategies. Accordingly, further investigation of the potential of adaptive alarms for continuous vital signs monitoring in ward patients is warranted.

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Zegers M, de Bruijne MC, de Keizer B, Merten H, Groenewegen PP, van der Wal G, et al. The incidence, root-causes, and outcomes of adverse events in surgical units: implication for potential prevention strategies. Patient Saf Surg. 2011;5:13. https://doi.org/10.1186/1754-9493-5-13.CrossRefPubMedPubMedCentral

Anderson O, Davis R, Hanna GB, Vincent CA. Surgical adverse events: a systematic review. Am J Surg. 2013;206:253–62. https://doi.org/10.1016/j.amjsurg.2012.11.009.CrossRefPubMed

The International Surgical Outcomes Study group. Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle-and high-income countries. Br J Anaesth. 2016;117:601–9. https://doi.org/10.1093/bja/aew316.CrossRefPubMedCentral

DeVita MA, Smith GB, Adam SK, Adams-Pizarro I, Buist M, Bellomo R, et al. “Identifying the hospitalised patient in crisis”—A consensus conference on the afferent limb of Rapid Response Systems. Resuscitation. 2010;81:375–82. https://doi.org/10.1016/j.resuscitation.2009.12.008.CrossRefPubMed

Ludikhuize J, Smorenburg SM, de Rooij SE, de Jonge E. Identification of deteriorating patients on general wards; measurement of vital parameters and potential effectiveness of the Modified Early Warning Score. J Crit Care. 2012;27:424.e7-424.e13. https://doi.org/10.1016/j.jcrc.2012.01.003.CrossRef

Taenzer AH, Spence BC. The afferent limb of rapid response systems: continuous monitoring on general care units. Crit Care Clin. 2018;34:189–98. https://doi.org/10.1016/j.ccc.2017.12.001.CrossRefPubMed

Boer C, Touw HR, Loer SA. Postanesthesia care by remote monitoring of vital signs in surgical wards. Curr Opin Anesthesiol. 2018;31:716–22. https://doi.org/10.1097/ACO.0000000000000650.CrossRef

Breteler MJM, KleinJan E, Numan L, Ruurda JP, Van Hillegersberg R, Leenen LPH, et al. Are current wireless monitoring systems capable of detecting adverse events in high-risk surgical patients? A descriptive study. Injury. 2020;51:S97-105. https://doi.org/10.1016/j.injury.2019.11.018.CrossRefPubMed

Downey CL, Chapman S, Randell R, Brown JM, Jayne DG. The impact of continuous versus intermittent vital signs monitoring in hospitals: A systematic review and narrative synthesis. Int J Nurs Stud. 2018;84:19–27. https://doi.org/10.1016/j.ijnurstu.2018.04.013.CrossRefPubMed

10.

Khanna AK, Hoppe P, Saugel B. Automated continuous noninvasive ward monitoring: future directions and challenges. Crit Care. 2019;23:194. https://doi.org/10.1186/s13054-019-2485-7.CrossRefPubMedPubMedCentral

11.

Posthuma LM, Visscher MJ, Hollmann MW, Preckel B. Monitoring of high- and intermediate-risk surgical patients. Anesth Analg. 2019;129:1185–90. https://doi.org/10.1213/ane.0000000000004345.CrossRefPubMed

12.

Vincent J-L, Einav S, Pearse R, Jaber S, Kranke P, Overdyk FJ, et al. Improving detection of patient deterioration in the general hospital ward environment. Eur J Anaesthesiol. 2018;35:325–33. https://doi.org/10.1097/EJA.0000000000000798.CrossRefPubMedPubMedCentral

13.

Kellett J, Sebat F. Make vital signs great again – A call for action. Eur J Intern Med. 2017;45:13–9. https://doi.org/10.1016/j.ejim.2017.09.018.CrossRefPubMed

14.

Krauchi K, Wirz-Justice A. Circadian rhythm of heat production, heart rate, and skin and core temperature under unmasking conditions in men. Am J Physiol Integr Comp Physiol. 1994;267:R819-29. https://doi.org/10.1152/ajpregu.1994.267.3.R819.CrossRef

15.

Chester JG, Rudolph JL. Vital Signs in Older Patients: Age-Related Changes. J Am Med Dir Assoc. 2011;12:337–43. https://doi.org/10.1016/j.jamda.2010.04.009.CrossRefPubMed

16.

McGrath SP, Taenzer AH, Karon N, Blike G. Surveillance monitoring management for general care units: strategy, design, and implementation. Jt Comm J Qual Patient Saf. 2016;42:293–302. https://doi.org/10.1016/S1553-7250(16)42040-4.CrossRefPubMed

17.

Cvach M. Monitor alarm fatigue: an integrative review. Biomed Instrum Technol. 2012;46:268–77. https://doi.org/10.2345/0899-8205-46.4.268.CrossRefPubMed

18.

Hravnak M, Pellathy T, Chen L, Dubrawski A, Wertz A, Clermont G, et al. A call to alarms: current state and future directions in the battle against alarm fatigue. J Electrocardiol. 2018;51:S44-8. https://doi.org/10.1016/j.jelectrocard.2018.07.024.CrossRefPubMedPubMedCentral

19.

Petit C, Bezemer R, Atallah L. A review of recent advances in data analytics for post-operative patient deterioration detection. J Clin Monit Comput. 2018;32:391–402. https://doi.org/10.1007/s10877-017-0054-7.CrossRefPubMed

20.

Winters BD, Cvach MM, Bonafide CP, Hu X, Konkani A, O’Connor MF, et al. Technological distractions (part 2): a summary of approaches to manage clinical alarms with intent to reduce alarm fatigue. Crit Care Med. 2018;46:130–7. https://doi.org/10.1097/CCM.0000000000002803.CrossRefPubMed

21.

da Costa CA, Pasluosta CF, Eskofier B, da Silva DB, da Rosa Righi R. Internet of health things: toward intelligent vital signs monitoring in hospital wards. Artif Intell Med. 2018;89:61–9. https://doi.org/10.1016/j.artmed.2018.05.005.CrossRefPubMed

22.

Baig MM, GholamHosseini H, Moqeem AA, Mirza F, Lindén M. A systematic review of wearable patient monitoring systems – current challenges and opportunities for clinical adoption. J Med Syst. 2017;41:115. https://doi.org/10.1007/s10916-017-0760-1.CrossRefPubMed

23.

Neill DB. Using artificial intelligence to improve hospital inpatient care. IEEE Intell Syst. 2013;28:92–5. https://doi.org/10.1109/MIS.2013.51.CrossRef

24.

Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. QJM. 2001;94:521–6. https://doi.org/10.1093/qjmed/94.10.521.CrossRefPubMed

25.

Griffin FA, Resar RK. IHI global trigger tool for measuring adverse events (Second Edition). IHI Innov: Ser. white Pap; 2009.

26.

Poole S, Shah N. Addressing vital sign alarm fatigue using personalized alarm thresholds. Pacific Symp Biocomput. 2018. https://doi.org/10.1142/9789813235533_0043.CrossRef

27.

Hollis RH, Graham LA, Lazenby JP, Brown DM, Taylor BB, Heslin MJ, et al. A role for the early warning score in early identification of critical postoperative complications. Ann Surg. 2016;263:918–23. https://doi.org/10.1097/SLA.0000000000001514.CrossRefPubMed

28.

Finnerty CC, Mabvuure NT, Ali A, Kozar RA, Herndon DN. The surgically induced stress response. J Parenter Enter Nutr. 2013;37:21S-29S. https://doi.org/10.1177/0148607113496117.CrossRef

29.

Welch J, Kanter B, Skora B, McCombie S, Henry I, McCombie D, et al. Multi-parameter vital sign database to assist in alarm optimization for general care units. J Clin Monit Comput. 2016;30:895–900. https://doi.org/10.1007/s10877-015-9790-8.CrossRefPubMed

30.

Paine CW, Goel VV, Ely E, Stave CD, Stemler S, Zander M, et al. Systematic review of physiologic monitor alarm characteristics and pragmatic interventions to reduce alarm frequency. J Hosp Med. 2016;11:136–44. https://doi.org/10.1002/jhm.2520.CrossRefPubMed

31.

Posthuma LM, Visscher MJ, Lirk PB, van Dijkum EJMN, Hollmann MW, Preckel B. Insights into postoperative respiration by using continuous wireless monitoring of respiratory rate on the postoperative ward: a cohort study. J Clin Monit Comput. 2019. https://doi.org/10.1007/s10877-019-00419-4.CrossRefPubMedPubMedCentral

32.

Brekke IJ, Puntervoll LH, Pedersen PB, Kellett J, Brabrand M. The value of vital sign trends in predicting and monitoring clinical deterioration: a systematic review. PLoS One. 2019;14:e0210875. https://doi.org/10.1371/journal.pone.0210875.CrossRefPubMedPubMedCentral

33.

Chopra V, McMahon LF. Redesigning hospital alarms for patient safety: alarmed and potentially dangerous. Jama. 2014;311:1199–200. https://doi.org/10.1001/jama.2014.710.CrossRefPubMed

34.

Gao H, McDonnell A, Harrison DA, Moore T, Adam S, Daly K, et al. Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward. Intensive Care Med. 2007;33:667–79. https://doi.org/10.1007/s00134-007-0532-3.CrossRefPubMed

35.

Drews FA 2008. Patient monitors in critical care: Lessons for improvement. In: Henriksen K, Battles JB, Keyes MA, Grady ML, editors. Adv patient Saf new Dir Altern approaches (vol 3 Perform tools) Agency Healthc Res Qual (US), Rockville, Maryl.

36.

Imhoff M, Kuhls S. Alarm algorithms in critical care monitoring. Anesth Analg. 2006;102:1525–37. https://doi.org/10.1213/01.ane.0000204385.01983.61.CrossRefPubMed

37.

Gross B, Dahl D, Nielsen L. Physiologic monitoring alarm load on medical/surgical floors of a community hospital. Biomed Instrum Technol. 2011;45:29–36. https://doi.org/10.2345/0899-8205-45.s1.29.CrossRef

38.

Tarassenko L, Clifton DA, Pinsky MR, Hravnak MT, Woods JR, Watkinson PJ. Centile-based early warning scores derived from statistical distributions of vital signs. Resuscitation. 2011;82:1013–8. https://doi.org/10.1016/j.resuscitation.2011.03.006.CrossRefPubMed

39.

Churpek MM, Adhikari R, Edelson DP. The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016;102:1–5. https://doi.org/10.1016/j.resuscitation.2016.02.005.CrossRefPubMedPubMedCentral

40.

Bartkowiak B, Snyder AM, Benjamin A, Schneider A, Twu NM, Churpek MM, et al. Validating the electronic cardiac arrest risk triage (eCART) score for risk stratification of surgical inpatients in the postoperative setting: retrospective cohort study. Ann Surg. 2019;269:1059–63. https://doi.org/10.1097/SLA.0000000000002665.CrossRefPubMed

41.

Rothman MJ, Rothman SI, Beals J. Development and validation of a continuous measure of patient condition using the Electronic Medical Record. J Biomed Inform. 2013;46:837–48. https://doi.org/10.1016/j.jbi.2013.06.011.CrossRefPubMed

42.

Churpek MM, Edelson DP. Moving beyond single parameter early warning scores for rapid response system activation. Crit Care Med. 2016;44:2283–5. https://doi.org/10.1097/CCM.0000000000002105.CrossRefPubMedPubMedCentral

43.

Clifton L, Clifton DA, Pimentel MAF, Watkinson PJ, Tarassenko L. Predictive monitoring of mobile patients by combining clinical observations with data from wearable sensors. IEEE J Biomed Heal Informatics. 2014;18:722–30. https://doi.org/10.1109/JBHI.2013.2293059.CrossRef

44.

Churpek MM, Yuen TC, Winslow C, Meltzer DO, Kattan MW, Edelson DP. Multicenter comparison of machine learning methods and conventional regression for predicting clinical deterioration on the wards. Crit Care Med. 2016;44:368–74. https://doi.org/10.1097/CCM.0000000000001571.CrossRefPubMedPubMedCentral

45.

Breteler MJM, KleinJan EJ, Dohmen DAJ, Leenen LPH, van Hillegersberg R, Ruurda JP, et al. Vital signs monitoring with wearable sensors in high-risk surgical patients: a clinical validation study. Anesthesiology. 2020;132:424–39. https://doi.org/10.1097/ALN.0000000000003029.CrossRefPubMed

Title: Adaptive threshold-based alarm strategies for continuous vital signs monitoring
Authors: Mathilde C. van Rossum
Lyan B. Vlaskamp
Linda M. Posthuma
Maarten J. Visscher
Martine J. M. Breteler
Hermie J. Hermens
Cor J. Kalkman
Benedikt Preckel
Publication date: 11-02-2021
Publisher: Springer Netherlands
Published in: Journal of Clinical Monitoring and Computing / Issue 2/2022
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI: https://doi.org/10.1007/s10877-021-00666-4

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Adaptive threshold-based alarm strategies for continuous vital signs monitoring

Abstract

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