Fifteen-year outcomes of an acute medical admission unit

Ir J Med Sci. 2018 Nov;187(4):1097-1105. doi: 10.1007/s11845-018-1789-y. Epub 2018 Mar 17.

Abstract

Background: The Acute Medical Admission Unit (AMAU) model of care has been associated with improved short- and medium-term outcomes; whether these improvements are sustained remains unclear. We report on the 15-year outcomes of an AMAU in our institution.

Methods: All emergency medical admissions between 2002 and 2016 were examined and 30-day in-hospital mortality, admission rates, readmission rates and length of stay (LOS) assessed. We used logistic and Poisson regression and margin statistics to evaluate outcomes.

Results: There were 96,305 admissions in 50,612 patients. By admission, the 30-day in-hospital mortality averaged 5.6% (95% CI 5.4 to 5.7%); there was a relative risk reduction (RRR) of 33.9% between 2002 and 2016, from 7.0 to 4.6% (p = 0.001), number need to treat (NNT) 41.9. By unique patient the 30-day in-hospital mortality averaged 10.5% (95% CI 10.3 to10.8%); there was a RRR of 61.7% between 2002 and 2016, from 15.1 to 5.8% (p = 0.001), NNT 10.7. The median LOS was 5.0 days (IQR 2.1, 9.8) and was unaltered over time. Deprivation status strongly influenced the admission rate/1000 population increasing from Q1 7.7 (95% CI 7.6 to 7.8) to Q5 37.8 (95% CI 37.6 to 38.0); this showed a slight trend to increase over time. Total readmissions increased as a function of time; early readmissions (< 4 weeks) remained constant 10.5% (95% CI 9.6 to 11.3).

Conclusion: The 30-day in-hospital mortality showed a linear trend to reduce over the 15 years following the institution of an AMAU; other key parameters were unaltered.

Keywords: Acute medical admissions unit; Admission rate; Emergency medical admissions; Mortality; Readmissions.

MeSH terms

  • Adult
  • Aged
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Follow-Up Studies
  • Hospital Mortality
  • Hospitalization / statistics & numerical data*
  • Humans
  • Ireland / epidemiology
  • Length of Stay / statistics & numerical data*
  • Male
  • Middle Aged
  • Patient Admission / statistics & numerical data*
  • Time Factors