The performance of intensive care units: does good management make a difference?
A significant portion of health care resources are spent in intensive care units with, historically, up to two-fold variation in risk-adjusted mortality. Technological, demographic, and social forces are likely to lead to an increased volume of intensive care in the future. Thus, it is important to identify ways of more efficiently managing intensive care units and reducing the variation in patient outcomes. Based on data collected from 17,440 patients across 42 ICUs, the present study examines the factors associated with risk-adjusted mortality, risk-adjusted average length of stay, nurse turnover, evaluated technical quality of care, and evaluated ability to meet family member needs. Using the Apache III methodology for risk-adjustment, findings reveal that: 1) technological availability is significantly associated with lower risk-adjusted mortality (beta = -.42); 2) diagnostic diversity is significantly associated with greater risk-adjusted mortality (beta = .46); and 3) caregiver interaction comprising the culture, leadership, coordination, communication, and conflict management abilities of the unit is significantly associated with lower risk-adjusted length of stay (beta = .34), lower nurse turnover (beta = -.36), higher evaluated technical quality of care (beta = .81), and greater evaluated ability to meet family member needs (beta = .74). Furthermore, units with greater technological availability are significantly more likely to be associated with hospitals that are more profitable, involved in teaching activities, and have unit leaders actively participating in hospital-wide quality improvement activities. The findings hold a number of important managerial and policy implications regarding technological adoption, specialization, and the quality of interaction among ICU team members. They suggest intervention "leverage points" for care givers, managers, and external policy makers in efforts to continuously improve the outcomes of intensive care.
Shortell
S M
SM
Center for Health Services and Policy Research, Northwestern University, Evanston, IL 60208-2007.
Zimmerman
J E
JE
Rousseau
D M
DM
Gillies
R R
RR
Wagner
D P
DP
Draper
E A
EA
Knaus
W A
WA
Duffy
J
J
D017028:Caregivers / Q000706:statistics & numerical data; D017598:Efficiency, Organizational / Q000592:standards*; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration* / Q000706:statistics & numerical data; D007400:Interprofessional Relations; D007902:Length of Stay / Q000706:statistics & numerical data; D009741:Nursing Staff, Hospital / Q000458:organization & administration / Q000706:statistics & numerical data; D010563:Personnel Turnover / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000706:statistics & numerical data; D012307:Risk Factors; D012720:Severity of Illness Index; D014481:United States / Q000453:epidemiology; D000078329:Workforce