Can a Patient's In-Hospital Length of Stay and Mortality Be Explained by Early-Risk Assessments?

• Published in: PloS one Vol. 11; no. 9; p. e0162976
• Main Authors: Azadeh-Fard, Nasibeh, Ghaffarzadegan, Navid, Camelio, Jaime A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 15.09.2016; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Blood pressure; Data processing; Demographics; Demography; Emergency communications systems; Emergency medical care; Female; Health care; Health care industry; Health care policy; Health risk assessment; Hospital Mortality; Hospital patients; Hospitals; Humans; Intensive care; Length of Stay; Male; Medical personnel; Medical research; Medicine and Health Sciences; Mortality; Patient outcomes; Patients; People and Places; Physical Sciences; Physicians; Pneumonia; Regression analysis; Regression models; Research and Analysis Methods; Risk Assessment; Studies; United States; Variables; Vital signs; United States > US; Virginia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0162976

To assess whether a patient's in-hospital length of stay (LOS) and mortality can be explained by early objective and/or physicians' subjective-risk assessments. Analysis of a detailed dataset of 1,021 patients admitted to a large U.S. hospital between January and September 2014. We empirically test the explanatory power of objective and subjective early-risk assessments using various linear and logistic regression models. The objective measures of early warning can only weakly explain LOS and mortality. When controlled for various vital signs and demographics, objective signs lose their explanatory power. LOS and death are more associated with physicians' early subjective risk assessments than the objective measures. Explaining LOS and mortality require variables beyond patients' initial medical risk measures. LOS and in-hospital mortality are more associated with the way in which the human element of healthcare service (e.g., physicians) perceives and reacts to the risks.