Do patient safety indicators explain increased weekend mortality?

J Surg Res. 2016 Jan;200(1):164-70. doi: 10.1016/j.jss.2015.07.030. Epub 2015 Jul 22.

Abstract

Background: We sought to determine the differential role of patient safety indicator (PSI) events on mortality after weekend as compared with weekday admission.

Materials and methods: We evaluated Agency for Healthcare Research and Quality PSI events within a cohort of patients with nonelective admissions. First, we identified all patients with a PSI based on day of admission (weekend versus weekday). Then, we evaluated the outcome of mortality after each PSI event. Finally, we entered age, sex, race, median household income, payer information, and Charlson comorbidity scores in regression models to develop risk ratios of weekend to weekday PSI events and mortality.

Results: There were 28,236,749 patients evaluated with 428,685 (1.5%) experiencing one or more PSI events. The rate of PSI was the same for patients admitted on weekends as compared to weekdays (1.5%). However, the risk of mortality was 7% higher if a PSI event occurred to a patient admitted on a weekend as compared with a weekday. In addition, compared to patients admitted on weekdays, patients admitted on weekends had a 36% higher risk of postoperative wound dehiscence, 19% greater risk of death in a low-mortality diagnostic-related group, 19% increased risk of postoperative hip fracture, and 8% elevated risk of surgical inpatient death.

Conclusions: Risk adjusted data reveal that PSI events are substantially higher among patients admitted on weekends. The considerable differences in death after PSI events in patients admitted on weekends as compared with weekdays indicate that responses to adverse events may be less effective on weekends.

Keywords: Mortality; Non-elective; Patient safety indicator; Weekend.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • After-Hours Care / standards*
  • After-Hours Care / statistics & numerical data
  • Aged
  • Aged, 80 and over
  • Databases, Factual
  • Female
  • Hospital Mortality*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Patient Safety / statistics & numerical data*
  • Quality Indicators, Health Care / statistics & numerical data*
  • Risk Adjustment
  • Time Factors
  • United States