Predictors of Change in Code Status from Time of Admission to Death in Critically Ill Surgical Patients

Am Surg. 2020 Mar 1;86(3):237-244.

Abstract

Racial and gender disparities in end-of-life decision-making practices have not been well described in surgical patients. We performed an eight-year retrospective analysis of surgical patients within the Cerner Acute Physiology and Chronic Health Evaluation Outcomes database. ICU patients with documented admission code status, and death or ICU discharge code status, respectively, were included. Logistic regression analysis was performed to assess change in code status. Of 468,000 ICU patients, 97,968 (20.9%) were surgical, 63,567 (95%) survived, and 3,343 (5%) died during their hospitalization. Of those, 50,915 (80.1%) and 2,625 (78.5%) had complete code status data on admission and discharge or death, respectively. Women were less likely than men to remain full code at ICU discharge and death (n = 20,940, 95.6% and n = 141, 11.9% vs n = 29,320, 97.4% and n = 233, 16.3%, P < 0.001). Compared with whites, blacks and other minorities had a 0.46 odds (95% confidence interval [CI]: 0.33-0.64, P < 0.001) and 0.54 odds (95% CI: 0.34-0.85, P = 0.01) of changing from full code status before death, respectively. Before ICU discharge, blacks and other minorities had a 0.56 odds of changing from full code status when compared with whites (95% CI: 0.40-0.79, P < 0.001 vs 95% CI: 0.36-0.87, P = 0.01, respectively). Women were more likely to be discharged or die after a change in code status from full code (odds ratio 1.27, 95% CI: 1.06-1.07, P < 0.001; odds ratio 1.39, 95% CI: 1.09-1.79, P = 0.009). Men and minorities are more likely to be discharged from the ICU or die with a full code status designation.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Black or African American / statistics & numerical data
  • Cardiopulmonary Resuscitation / mortality*
  • Cause of Death
  • Clinical Decision-Making
  • Confidence Intervals
  • Critical Illness / mortality
  • Critical Illness / therapy
  • Databases, Factual
  • Female
  • Health Care Surveys
  • Hospital Mortality / trends*
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Logistic Models
  • Male
  • Middle Aged
  • Minority Groups*
  • Outcome Assessment, Health Care*
  • Patient Admission
  • Predictive Value of Tests
  • Retrospective Studies
  • Risk Assessment
  • Sex Factors
  • Surgical Procedures, Operative