Patient, Practice, and Organizational Factors Associated With Early Mobility Performance in Critically Ill Adults

Author:

Krupp Anna E.1,Tan Alai2,Vasilevskis Eduard E.3,Mion Lorraine C.4,Pun Brenda T.5,Brockman Audrey6,Hetland Breanna7,Ely E. Wesley8,Balas Michele C.9

Affiliation:

1. Anna E. Krupp is an assistant professor, College of Nursing, University of Iowa, Iowa City.

2. Alai Tan is a research professor, Center for Research and Health Analytics, The Ohio State University College of Nursing, Columbus.

3. Eduard E. Vasilevskis is a professor and chief of the Division of Hospital Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.

4. Lorraine C. Mion is a research professor, Center for Healthy Aging, Self-Management and Complex Care, The Ohio State University College of Nursing.

5. Brenda T. Pun is director of data quality, Critical Illness, Brain Dysfunction, and Survivorship Center, Vanderbilt University Medical Center, Nashville, Tennessee.

6. Audrey Brockman is a graduate research assistant, The Ohio State University College of Nursing.

7. Breanna Hetland is an assistant professor, College of Nursing, University of Nebraska Medical Center, Omaha, and a critical care nurse scientist, Nebraska Medicine, Omaha.

8. E. Wesley Ely is a professor, Department of Medicine and the Critical Illness, Brain Dysfunction, and Survivorship Center, Vanderbilt University Medical Center, and associate director of medicine and research, Geriatric Research Education and Clinical Center, Veterans Affairs Tennessee Valley Healthcare System, Nashville, Tennessee.

9. Michele C. Balas is professor and associate dean of research, College of Nursing, University of Nebraska Medical Center.

Abstract

Background Adoption of early mobility interventions into intensive care unit (ICU) practice has been slow and varied. Objectives To examine factors associated with early mobility performance in critically ill adults and evaluate factors’ effects on predicting next-day early mobility performance. Methods A secondary analysis of 66 ICUs’ data from patients admitted for at least 24 hours. Mixed-effects logistic regression modeling was done, with area under the receiver operating characteristic curve (AUC) calculated. Results In 12 489 patients, factors independently associated with higher odds of next-day mobility included significant pain (adjusted odds ratio [AOR], 1.16; 95% CI, 1.09–1.23), documented sedation target (AOR, 1.09; 95% CI, 1.01–1.18), performance of spontaneous awakening trials (AOR, 1.77; 95% CI, 1.59–1.96), spontaneous breathing trials (AOR, 2.35; 95% CI, 2.14–2.58), mobility safety screening (AOR, 2.26; 95% CI, 2.04–2.49), and prior-day physical/occupational therapy (AOR, 1.44; 95% CI, 1.30–1.59). Factors independently associated with lower odds of next-day mobility included deep sedation (AOR, 0.44; 95% CI, 0.39–0.49), delirium (AOR, 0.63; 95% CI, 0.59–0.69), benzodiazepine administration (AOR, 0.85; 95% CI, 0.79–0.92), physical restraints (AOR, 0.74; 95% CI, 0.68–0.80), and mechanical ventilation (AOR, 0.73; 95% CI, 0.68–0.78). Black and Hispanic patients had lower odds of next-day mobility than other patients. Models incorporating patient, practice, and between-unit variations displayed high discriminant accuracy (AUC, 0.853) in predicting next-day early mobility performance. Conclusions Collectively, several modifiable and nonmodifiable factors provide excellent prediction of next-day early mobility performance.

Publisher

AACN Publishing

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