A hospitalist-run short-stay unit: features that predict length-of-stay and eventual admission to traditional inpatient services

J Hosp Med. 2009 May;4(5):276-84. doi: 10.1002/jhm.386.


Background: Short-stay units (SSUs) provide an alternative to traditional inpatient services for patients with short anticipated hospital stays. Yet little is known about which patient types predict SSU success.

Objective: To describe patients admitted to our hospitalist-run SSU and explore predictors of length-of-stay (LOS) and eventual admission to traditional inpatient services.

Design: Prospective observational cohort study.

Setting: Large public teaching hospital.

Patients: Consecutive admissions (n = 755) to the SSU over 4 months.

Intervention: Hospitalist attending physicians prospectively collected data from patients' histories, physical exams, and medical records upon admission and discharge.

Measurements: Risk assessments were made for patients with our most common provisional diagnoses: possible acute coronary syndrome (ACS) and heart failure. Patient stays were considered successful when LOS was less than 72 hours and eventual admission to traditional inpatient services was not required.

Results: Of 738 eligible patients, 79% (n = 582) had successful SSU stays. In a multivariable model, the provisional diagnosis of heart failure predicted stays longer than 72 hours (P = 0.007) but risk assessments were unimportant. Patients who received specialty consultations were most likely to need eventual admission (odds ratio [OR], 13.1; 95% confidence interval [CI], 6.9-24.9), and the likelihood of long stays was inversely proportional to the accessibility of diagnostic tests.

Conclusions: In our hospitalist-run SSU, the inaccessibility of diagnostic tests and the need for specialty consultations were the most important predictors of unsuccessful stays. Designs for other SSUs that care for mostly low-risk patients should focus on matching patients' diagnostic and consultative needs with readily accessible services.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Coronary Syndrome
  • Aged
  • Chicago
  • Efficiency, Organizational*
  • Female
  • Heart Failure
  • Hospitalists*
  • Hospitals, Teaching / organization & administration*
  • Humans
  • Length of Stay* / statistics & numerical data
  • Male
  • Middle Aged
  • Observation
  • Odds Ratio
  • Patient Admission*
  • Program Evaluation
  • Prospective Studies
  • Referral and Consultation
  • Risk Assessment