Predictors of return visits to the emergency department among different age groups of older adults

Am J Emerg Med. 2021 Aug:46:241-246. doi: 10.1016/j.ajem.2020.07.042. Epub 2020 Jul 22.

Abstract

Objective: To identify predictors of 30-day emergency department (ED) return visits in patients age 65-79 years and age ≥ 80 years.

Methods: This was a cohort study of older adults who presented to the ED over a 1-year period. A mixed-effects logistic regression model was used to identify predictors for returning to the ED within 30 days. We stratified the cohort into those aged 65-79 years and aged ≥80 years. Adjusted odds ratios (aORs) with 95% confidence intervals (CI) were reported. This study adhered to the STROBE reporting guidelines.

Results: A total of 21,460 ED visits representing 14,528 unique patients were included. The overall return rate was 15% (1998/13,300 visits) for age 65-79 years, and 16% (1306/8160 visits) for age ≥ 80 years. A history of congestive heart failure (CHF), dementia, or prior hospitalization within 2 years were associated with increased odds of returning in both age groups (for age 65-79: CHF aOR 1.36 [CI 1.16-1.59], dementia aOR 1.27 [CI 1.07-1.49], prior hospitalization aOR 1.36 [CI 1.19-1.56]; for age ≥ 80: CHF aOR 1.32 [CI 1.13-1.55], dementia aOR 1.22 [CI 1.04-1.42], and prior hospitalization aOR 1.27 [CI 1.09-1.47]). Being admitted from the ED was associated with decreased odds of returning to the ED within 30 days (aOR 0.72 [CI 0.64-0.80] for age 65-79 years and 0.72 [CI 0.63-0.82] for age ≥ 80).

Conclusion: Age alone was not an independent predictor of return visits. Prior hospitalization, dementia and CHF were predictors of 30-day ED return. The identification of predictors of return visits may help to optimize care transition in the ED.

Keywords: Aged; Aged 80 and over; Emergency service; Patient readmission; Risk factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Risk Factors
  • Utilization Review*