Abstract
Managing respiratory distress during end-of-life (EOL) ventilator withdrawal poses significant challenges, particularly without structured algorithms or validated, reliable tools. This quality improvement (QI) project addressed these challenges by implementing Campbell’s ventilator withdrawal algorithm and the Respiratory Distress Observation Scale (RDOS), a validated, reliable tool for objective dyspnea assessment. This project sought to enhance care quality by evaluating process feasibility while addressing implementation barriers.
Dyspnea is a complex, subjective symptom frequently encountered during EOL ventilator withdrawal. Campbell’s algorithm provides a structured, individualized approach emphasizing prevention, early intervention, reassessment, and treatment while considering patient-specific factors such as illness severity and level of consciousness. Its algorithmic approach to medication titration, extubation planning, and survival discussions provides individualized care. The RDOS complements this by using objective dyspnea assessment in non-communicative patients.
Conducted over 5 months in an intensive care unit (ICU), this QI project involved a multidisciplinary team of nurses, respiratory therapists, physicians, and advanced practice providers. Participation was voluntary, with education provided via webinars requiring an 80% passing grade to ensure fidelity. The project had 3 phases: observing usual EOL care, conducting educational sessions, and implementing the algorithm and RDOS. Tools such as checklists supported adherence, with fidelity monitored throughout.
Barriers included time constraints, staff workload, knowledge gaps, skepticism regarding sedation adequacy, concerns about euthanasia, and resource limitations. Strategies to mitigate these included “just-in-time” training, computerized order sets, and targeted education addressing knowledge gaps. However, ethical apprehensions and reluctance to relinquish autonomy occurred among some staff.
The project underscores the potential of ventilator withdrawal algorithms in reducing dyspnea and improving the quality of EOL care. However, addressing educational, logistical, and ethical challenges remains crucial for successful implementation. Future efforts should focus on identifying and addressing the root causes of these barriers to improve feasibility and acceptance in clinical practice.
Notes
References:
1. Campbell M.L. (2016). Caring Practice: EBP for Terminal Ventilator Withdrawal.
https://www.aacn.org/education/webinar-series/wb0030/caring-practice-ebp-for-terminal-ventilator-withdrawal.
2. Campbell, M. L., Kero, K. K., & Templin, T. N. (2017). Mild, moderate, and severe intensity cut-points for the Respiratory Distress Observation Scale. Heart & lung : the journal of critical care, 46(1), 14–17. https://doi.org/10.1016/j.hrtlng.2016.06.008
3. Campbell, M. L., & Templin, T. N. (2015). Intensity cut-points for the Respiratory Distress Observation Scale. Palliative medicine, 29(5), 436–442. https://doi.org/10.1177/0269216314564238
4. Campbell, M. L., Yarandi, H. N., & Mendez, M. (2015). A Two-Group Trial of a Terminal Ventilator Withdrawal Algorithm: Pilot Testing. Journal of palliative medicine, 18(9), 781–785. https://doi.org/10.1089/jpm.2015.0111
5. Chan, Y. H., Wu, H. S., Yen, C. C., & Campbell, M. L. (2018). Psychometric Evaluation of the Chinese Respiratory Distress Observation Scale on Critically Ill Patients With Cardiopulmonary Diseases. The journal of nursing research : JNR, 26(5), 340–347. https://doi.org/10.1097/jnr.0000000000000250
6. Delaney, J. W., & Downar, J. (2016). How is life support withdrawn in intensive care units: A narrative review. Journal of critical care, 35, 12–18. https://doi.org/10.1016/j.jcrc.2016.04.006
7. Mularski, R. A., Campbell, M. L., Asch, S. M., Reeve, B. B., Basch, E., Maxwell, T. L., Hoverman, J. R., Cuny, J., Clauser, S. B., Snyder, C., Seow, H., Wu, A. W., & Dy, S. (2010). A review of quality of care evaluation for the palliation of dyspnea. American journal of respiratory and critical care medicine, 181(6), 534–538. https://doi.org/10.1164/rccm.200903-0462PP
8. Mularski, R. A., Reinke, L. F., Carrieri-Kohlman, V., Fischer, M. D., Campbell, M. L., Rocker, G., Schneidman, A., Jacobs, S. S., Arnold, R., Benditt, J. O., Booth, S., Byock, I., Chan, G. K., Curtis, J. R., Donesky, D., Hansen-Flaschen, J., Heffner, J., Klein, R., Limberg, T. M., Manning, H. L., … ATS Ad Hoc Committee on Palliative Management of Dyspnea Crisis (2013). An official American Thoracic Society workshop report: assessment and palliative management of dyspnea crisis. Annals of the American Thoracic Society, 10(5), S98–S106. https://doi.org/10.1513/AnnalsATS.201306-169ST
9. Paruk, F., Kissoon, N., Hartog, C. S., Feldman, C., Hodgson, E. R., Lipman, J., Guidet, B., Du, B., Argent, A., & Sprung, C. L. (2014). The Durban World Congress Ethics Round Table Conference Report: III. Withdrawing Mechanical ventilation--the approach should be individualized. Journal of critical care, 29(6), 902–907. https://doi.org/10.1016/j.jcrc.2014.05.022
10. Puntillo, K., Nelson, J. E., Weissman, D., Curtis, R., Weiss, S., Frontera, J., Gabriel, M., Hays, R.,Lustbader, D., Mosenthal, A., Mulkerin, C., Ray, D., Bassett, R., Boss, R., Brasel, K., & Campbell, M. (2014). Palliative care in the ICU: relief of pain, dyspnea, and thirst—a report from the IPAL-ICU Advisory Board. Intensive care medicine, 40(2), 235–248. https://doi.org/10.1007/s00134-013-3153-z
11. Zhuang, Q., Yang, G. M., Neo, S. H., & Cheung, Y. B. (2019). Validity, Reliability, and Diagnostic Accuracy of the Respiratory Distress Observation Scale for Assessment of Dyspnea in Adult Palliative Care Patients. Journal of pain and symptom management, 57(2), 304–310. https://doi.org/10.1016/j.jpainsymman.2018.10.506
Sigma Membership
Alpha Tau
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Quality Improvement
Research Approach
Translational Research/Evidence-based Practice
Keywords:
Hospice, Palliative, End-of-Life, Interprofessional, Interdisciplinary, Interprofessional Initiatives, Interprofessional Evidence-Based Solutions, Ventilator Withdrawal
Recommended Citation
Aguilar, Al-Zada and Nicastro, Olivia, "Palliative Ventilator Withdrawal Algorithm: A Feasibility Quality Improvement (QI) Project" (2025). Biennial Convention (CONV). 129.
https://www.sigmarepository.org/convention/2025/presentations_2025/129
Conference Name
48th Biennial Convention
Conference Host
Sigma Theta Tau International
Conference Location
Indianapolis, Indiana, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2025-12-01
Palliative Ventilator Withdrawal Algorithm: A Feasibility Quality Improvement (QI) Project
Indianapolis, Indiana, USA
Managing respiratory distress during end-of-life (EOL) ventilator withdrawal poses significant challenges, particularly without structured algorithms or validated, reliable tools. This quality improvement (QI) project addressed these challenges by implementing Campbell’s ventilator withdrawal algorithm and the Respiratory Distress Observation Scale (RDOS), a validated, reliable tool for objective dyspnea assessment. This project sought to enhance care quality by evaluating process feasibility while addressing implementation barriers.
Dyspnea is a complex, subjective symptom frequently encountered during EOL ventilator withdrawal. Campbell’s algorithm provides a structured, individualized approach emphasizing prevention, early intervention, reassessment, and treatment while considering patient-specific factors such as illness severity and level of consciousness. Its algorithmic approach to medication titration, extubation planning, and survival discussions provides individualized care. The RDOS complements this by using objective dyspnea assessment in non-communicative patients.
Conducted over 5 months in an intensive care unit (ICU), this QI project involved a multidisciplinary team of nurses, respiratory therapists, physicians, and advanced practice providers. Participation was voluntary, with education provided via webinars requiring an 80% passing grade to ensure fidelity. The project had 3 phases: observing usual EOL care, conducting educational sessions, and implementing the algorithm and RDOS. Tools such as checklists supported adherence, with fidelity monitored throughout.
Barriers included time constraints, staff workload, knowledge gaps, skepticism regarding sedation adequacy, concerns about euthanasia, and resource limitations. Strategies to mitigate these included “just-in-time” training, computerized order sets, and targeted education addressing knowledge gaps. However, ethical apprehensions and reluctance to relinquish autonomy occurred among some staff.
The project underscores the potential of ventilator withdrawal algorithms in reducing dyspnea and improving the quality of EOL care. However, addressing educational, logistical, and ethical challenges remains crucial for successful implementation. Future efforts should focus on identifying and addressing the root causes of these barriers to improve feasibility and acceptance in clinical practice.
Description
Managing respiratory distress during end-of-life (EOL) ventilator withdrawal can be challenging. This 5-month QI project implemented Campbell’s ventilator withdrawal algorithm and the Respiratory Distress Observation Scale (RDOS) to reduce dyspnea and improve EOL care. It evaluated feasibility, identified barriers, and introduced strategies to support implementation. It demonstrated the potential for improved EOL care with these tools while highlighting challenges to successful implementation.