Impact of localizing general medical teams to a single nursing unit

J Hosp Med. 2012 Sep;7(7):551-6. doi: 10.1002/jhm.1948. Epub 2012 Jul 12.


Background: Localization of general medical inpatient teams is an attractive way to improve inpatient care but has not been adequately studied.

Objective: To evaluate the impact of localizing general medical teams to a single nursing unit.

Design: Quasi-experimental study using historical and concurrent controls.

Setting: A 490-bed academic medical center in the midwestern United States.

Patients: Adult, general medical patients, other than those with sickle cell disease, admitted to medical teams staffed by a hospitalist and a physician assistant (PA).

Intervention: Localization of patients assigned to 2 teams to a single nursing unit.

Measurements: Length of stay (LOS), 30-day risk of readmission, charges, pages to teams, encounters, relative value units (RVUs), and steps walked by PAs.

Results: Localized teams had 0.89 (95% confidence interval [CI], 0.37-1.41) more patient encounters and generated 2.20 more RVUs per day (CI, 1.10-3.29) compared to historical controls; and 1.02 (CI, 0.46-1.58) more patient encounters and generated 1.36 more RVUs per day (CI, 0.17-2.55) compared to concurrent controls. Localized teams received 51% (CI, 48-54) fewer pages during the workday. LOS may have been approximately 10% higher for localized teams. Risk of readmission within 30 days and charges incurred were no different. PAs possibly walked fewer steps while localized.

Conclusion: Localization of medical teams led to higher productivity and better workflow, but did not significantly impact readmissions or charges. It may have had an unintended negative impact on hospital efficiency; this finding deserves further study.

MeSH terms

  • Academic Medical Centers / organization & administration*
  • Adult
  • Aged
  • Aged, 80 and over
  • Confidence Intervals
  • Efficiency, Organizational
  • Female
  • Geography
  • Humans
  • Inpatients*
  • Intensive Care Units
  • Length of Stay
  • Male
  • Medical Staff, Hospital / organization & administration*
  • Middle Aged
  • Models, Organizational*
  • Nursing Service, Hospital / organization & administration*
  • Odds Ratio
  • Patient Care
  • Statistics, Nonparametric
  • Wisconsin
  • Workflow