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Criterion validity and inter-rater reliability of a palliative care screening tool for patients admitted to an emergency department intensive care unit

Published online by Cambridge University Press:  26 December 2017

Sabrina Corrêa da Costa Ribeiro
Affiliation:
Emergency Department of Hospital das Clínicas of University of São Paulo Medical School, São Paulo, Brazil
Ricardo Tavares de Carvalho
Affiliation:
Palliative Care Service of Hospital das Clínicas of University of São Paulo Medical School, São Paulo, Brazil
Juraci Aparecida Rocha
Affiliation:
Palliative Care Service of Hospital das Clínicas of University of São Paulo Medical School, São Paulo, Brazil
Roger Daglius Dias*
Affiliation:
Emergency Department of Hospital das Clínicas of University of São Paulo Medical School, São Paulo, Brazil Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts (current affiliation)
*
Author for correspondence: Roger Daglius Dias, STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Harvard Medical School, 10 Vining Street, 02215, Boston, MA 02115. E-mail: [email protected]

Abstract

Objective

The use of palliative care (PC) screening criteria to trigger PC consultations may optimize the utilization of PC services, improve patient comfort, and reduce invasive and futile end-of-life care. The aim of the present study was to assess the criterion validity and inter-rater reliability of a PC screening tool for patients admitted to an emergency department intensive care unit (ED-ICU).

Method

Observational retrospective study evaluating PC screening criteria based on the presence of advanced diagnosis and the use of two “surprise questions” (traditional and modified). Patients were classified at ED-ICU admission in four categories according to the proposed algorithm.

Result

A total of 510 patients were included in the analysis. From these, 337 (66.1%) were category 1, 0 (0.0%) category 2, 63 (12.4%) category 3, and 110 (21.6%) category 4. Severity of illness (Simplified Acute Physiology Score III score and mechanical ventilation), mortality (ED-ICU and intrahospital), and PC-related measures (order for a PC consultation, time between admission and PC consultation, and transfer to a PC bed) were significantly different across groups, more evidently between categories 4 and 1. Category 3 patients presented similar outcomes to patients in category 1 for severity of illness and mortality. However, category 3 patients had a PC consultation ordered more frequently than did category 1 patients. The screening criteria were assessed by two independent raters (n = 100), and a substantial interrater reliability was found, with 80% of agreement and a kappa coefficient of 0.75 (95% confidence interval = 0.62, 0.88).

Significance of results

This study is the first step toward the implementation of a PC screening tool in the ED-ICU. The tool was able to discriminate three groups of patients within a spectrum of increasing severity of illness, risk of death, and PC needs, presenting substantial inter-rater reliability. Future research should investigate the implementation of these screening criteria into routine practice of an ED-ICU.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2017 

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References

American College of Emergency Physicians (ACEP) (2011) Boarding of admitted and intensive care patients in the emergency department. Policy statement. Annals of Emergency Medicine 58(1), 110.Google Scholar
Aslakson, R, Cheng, J, Vollenweider, D, et al. (2014) Evidence-based palliative care in the intensive care unit: A systematic review of interventions. Journal of Palliative Medicine 17(2), 219235.Google Scholar
Aslaner, MA, Akkaş, M, Eroğlu, S, et al. (2015). Admissions of critically ill patients to the ED intensive care unit. American Journal of Emergency Medicine 33(4), 501505.Google Scholar
Braus, N, Campbell, TC, Kwekkeboom, KL, et al. (2016) Prospective study of a proactive palliative care rounding intervention in a medical ICU. Intensive Care Medicine 42(1), 5462.Google Scholar
Byock, I (2006) Improving palliative care in intensive care units: Identifying strategies and interventions that work. Critical Care Medicine 34(11 Suppl), S302S305.Google Scholar
Campbell, ML and Guzman, JA (2003) Impact of a proactive approach to improve end-of-life care in a medical ICU. Chest 123(1), 266271.Google Scholar
Chalfin, DB, Trzeciak, S, Likourezos, A, et al. (2007) Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit. Critical Care Medicine 35(6), 14771483.Google Scholar
Downar, J, Goldman, R, Pinto, R, et al. (2017) The “surprise question” for predicting death in seriously ill patients: A systematic review and meta-analysis. CMAJ 189(13), E484E493.Google Scholar
George, N, Phillips, E, Zaurova, M, et al. (2016) Palliative care screening and assessment in the emergency department: A systematic review. Journal of Pain and Symptom Management 51(1), 108119.Google Scholar
Goldstein, RS (2005). Management of the critically ill patient in the emergency department: focus on safety issues. Critical Care Clinics 21(1), 8189, viii–ix.Google Scholar
Hamano, J, Morita, T, Inoue, S, et al. (2015) Surprise questions for survival prediction in patients with advanced cancer: A multicenter prospective cohort study. Oncologist 20(7), 839844.Google Scholar
Harris, PA, Taylor, R, Thielke, R, et al. (2009). Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 42(2), 377381.Google Scholar
Haydar, SA, Almeder, L, Michalakes, L, et al. (2017) Using the surprise question to identify those with unmet palliative care needs in emergency and inpatient settings: What do clinicians think? Journal of Palliative Medicine 20(7), 729735.Google Scholar
Katz, S, Ford, AB, Moskowitz, RW, et al. (1963) Studies of illness in the aged. The index of ADL: A standardized measure of biological and psychosocial function. JAMA 185, 914919.Google Scholar
Knaus, WA, Zimmerman, JE, Wagner, DP, et al. (1981) APACHE-acute physiology and chronic health evaluation: A physiologically based classification system. Critical Care Medicine 9(8), 591597.Google Scholar
Landis, JR and Koch, GG (1977) The measurement of observer agreement for categorical data. Biometrics 33(1), 159174.Google Scholar
Le Maguet, P, Roquilly, A, Lasocki, S, et al. (2014) Prevalence and impact of frailty on mortality in elderly ICU patients: A prospective, multicenter, observational study. Intensive Care Medicine 40(5), 674682.Google Scholar
Moreno, RP, Metnitz, PG, Almeida, E, et al. (2005) SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Medicine 31(10), 13451355.Google Scholar
Moroni, M, Zocchi, D, Bolognesi, D, et al. (2014) The ‘surprise’ question in advanced cancer patients: A prospective study among general practitioners. Palliative Medicine 28(7), 959964.Google Scholar
Mullins, PM, Goyal, M, and Pines, JM (2013) National growth in intensive care unit admissions from emergency departments in the United States from 2002 to 2009. Academic Emergency Medicine 20(5), 479486.Google Scholar
Nelson, JE, Bassett, R, Boss, RD, et al. (2010) Models for structuring a clinical initiative to enhance palliative care in the intensive care unit: A report from the IPAL-ICU Project (Improving Palliative Care in the ICU). Critical Care Medicine 38(9), 17651772.Google Scholar
Nelson, JE, Curtis, JR, Mulkerin, C, et al. (2013) Choosing and using screening criteria for palliative care consultation in the ICU: A report from the Improving Palliative Care in the ICU (IPAL-ICU) Advisory Board. Critical Care Medicine 41(10), 23182327.Google Scholar
Norton, SA, Hogan, LA, Holloway, RG, et al. (2007). Proactive palliative care in the medical intensive care unit: Effects on length of stay for selected high-risk patients. Critical Care Medicine 35(6), 15301535.Google Scholar
O'Callaghan, A, Laking, G, Frey, R, et al. (2014). Can we predict which hospitalised patients are in their last year of life? A prospective cross-sectional study of the Gold Standards Framework Prognostic Indicator Guidance as a screening tool in the acute hospital setting. Palliative Medicine 28(8), 10461052.Google Scholar
O'Mahony, S, McHenry, J, Blank, AE, et al. (2010) Preliminary report of the integration of a palliative care team into an intensive care unit. Palliative Medicine 24(2), 154165.Google Scholar
Ramos, JG, Perondi, B, Daglius Dias, R, et al. (2016) Development of an algorithm to aid triage decisions for intensive care unit admission: A clinical vignette and retrospective cohort study. Critical Care 20(1), 81.Google Scholar
Schneiderman, LJ, Gilmer, T, Teetzel, HD, et al. (2003) Effect of ethics consultations on nonbeneficial life-sustaining treatments in the intensive care setting: A randomized controlled trial. JAMA 290(9), 11661172.Google Scholar
Small, N, Gardiner, C, Barnes, S, et al. (2010) Using a prediction of death in the next 12 months as a prompt for referral to palliative care acts to the detriment of patients with heart failure and chronic obstructive pulmonary disease. Palliative Medicine 24(7), 740741.Google Scholar
Sprung, CL, Baras, M, Iapichino, G, et al. (2012) The Eldicus prospective, observational study of triage decision making in European intensive care units: Part I--European Intensive Care Admission Triage Scores. Critical Care Medicine 40(1), 125131.Google Scholar
Sullivan, KM (2006) SMR analysis. Available from http://web1.sph.emory.edu/cdckms/exact-midP-SMR.html.Google Scholar
Teno, JM, Gozalo, PL, Bynum, JP, et al. (2013) Change in end-of-life care for Medicare beneficiaries: Site of death, place of care, and health care transitions in 2000, 2005, and 2009. JAMA 309(5), 470477.Google Scholar
Truog, RD, Campbell, ML, Curtis, JR, et al. (2008) Recommendations for end-of-life care in the intensive care unit: A consensus statement by the American College [corrected] of Critical Care Medicine. Critical Care Medicine 36(3), 953963.Google Scholar
Tseng, JC, Li, CH, Chen, KF, et al. (2015) Outcomes of an emergency department intensive care unit in a tertiary medical center in Taiwan: An observational study. Journal of Critical Care 30(3), 444448.Google Scholar
Walter, SD, Eliasziw, M, and Donner, A (1998) Sample size and optimal designs for reliability studies. Statistics in Medicine 17(1), 101110.Google Scholar
Weingart, SD, Sherwin, RL, Emlet, LL, et al. (2013) ED intensivists and ED intensive care units. American Journal of Emergency Medicine 31(3), 617620.Google Scholar
Weissman, DE and Meier, DE (2011) Identifying patients in need of a palliative care assessment in the hospital setting: A consensus report from the Center to Advance Palliative Care. Journal of Palliative Medicine 14(1), 1723.Google Scholar
Zalenski, R, Courage, C, Edelen, A, et al. (2014) Evaluation of screening criteria for palliative care consultation in the MICU: A multihospital analysis. BMJ Supportive & Palliative Care 4(3), 254262.Google Scholar