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

PLoS One. 2016 Sep 15;11(9):e0162976. doi: 10.1371/journal.pone.0162976. eCollection 2016.

Abstract

Objective: 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.

Data sources/study setting: Analysis of a detailed dataset of 1,021 patients admitted to a large U.S. hospital between January and September 2014.

Study design: We empirically test the explanatory power of objective and subjective early-risk assessments using various linear and logistic regression models.

Principal findings: 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.

Conclusions: 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.

MeSH terms

  • Female
  • Hospital Mortality*
  • Humans
  • Length of Stay*
  • Male
  • Risk Assessment
  • United States

Grants and funding

The authors received no specific funding for conducting this study.