RATIONALE: Moving patients from low-performing hospitals to high-performing hospitals may improve patient outcomes. These transfers may be particularly important in critical care, where small relative improvements can yield substantial absolute changes in survival. OBJECTIVE: To characterize the existing critical care network in terms of the pattern of transfers. METHODS: In a retrospective cohort study, the nationwide 2005 Medicare fee-for-service claims were used to identify the interhospital transfer of critically ill patients, defined as instances where patients used critical care services in 2 temporally adjacent hospitalizations. MEASUREMENTS: We measured the characteristics of the interhospital transfer network and the extent to which intensive care unit patients are referred to each hospital in that network--a continuous quantitative measure at the hospital-level known as centrality. We evaluated associations between hospital centrality and organizational, medical, surgical, and radiologic capabilities. RESULTS: There were 47,820 transfers of critically ill patients among 3308 hospitals. 4.5% of all critical care stays of any length involved an interhospital critical care transfer. Hospitals transferred out to a mean of 4.4 other hospitals. More central hospital positions were associated with multiple indicators of increased capability. Hospital characteristics explained 40.7% of the variance in hospitals' centrality. CONCLUSIONS: Critical care transfers are common, and traverse an informal but structured network. The centrality of a hospital is associated with increased capability in delivery of services, suggesting that existing transfers generally direct patients toward better resourced hospitals. Studies of this network promise further improvements in patient outcomes and efficiency of care.
RATIONALE: Moving patients from low-performing hospitals to high-performing hospitals may improve patient outcomes. These transfers may be particularly important in critical care, where small relative improvements can yield substantial absolute changes in survival. OBJECTIVE: To characterize the existing critical care network in terms of the pattern of transfers. METHODS: In a retrospective cohort study, the nationwide 2005 Medicare fee-for-service claims were used to identify the interhospital transfer of critically illpatients, defined as instances where patients used critical care services in 2 temporally adjacent hospitalizations. MEASUREMENTS: We measured the characteristics of the interhospital transfer network and the extent to which intensive care unit patients are referred to each hospital in that network--a continuous quantitative measure at the hospital-level known as centrality. We evaluated associations between hospital centrality and organizational, medical, surgical, and radiologic capabilities. RESULTS: There were 47,820 transfers of critically illpatients among 3308 hospitals. 4.5% of all critical care stays of any length involved an interhospital critical care transfer. Hospitals transferred out to a mean of 4.4 other hospitals. More central hospital positions were associated with multiple indicators of increased capability. Hospital characteristics explained 40.7% of the variance in hospitals' centrality. CONCLUSIONS: Critical care transfers are common, and traverse an informal but structured network. The centrality of a hospital is associated with increased capability in delivery of services, suggesting that existing transfers generally direct patients toward better resourced hospitals. Studies of this network promise further improvements in patient outcomes and efficiency of care.
Authors: J G Canto; N R Every; D J Magid; W J Rogers; J A Malmgren; P D Frederick; W J French; A J Tiefenbrunn; V K Misra; C I Kiefe; H V Barron Journal: N Engl J Med Date: 2000-05-25 Impact factor: 91.245
Authors: P D McGrath; D E Wennberg; J D Dickens; A E Siewers; F L Lucas; D J Malenka; M A Kellett; T J Ryan Journal: JAMA Date: 2000-12-27 Impact factor: 56.272
Authors: Edmond W Chen; John G Canto; Lori S Parsons; Eric D Peterson; Katherine A Littrell; Nathan R Every; C Michael Gibson; Judith S Hochman; E Magnus Ohman; Morris Cheeks; Hal V Barron Journal: Circulation Date: 2003-08-11 Impact factor: 29.690
Authors: Jeremy M Kahn; Walter T Linde-Zwirble; Hannah Wunsch; Amber E Barnato; Theodore J Iwashyna; Mark S Roberts; Judith R Lave; Derek C Angus Journal: Am J Respir Crit Care Med Date: 2007-11-15 Impact factor: 21.405
Authors: Derek C Angus; Amber E Barnato; Walter T Linde-Zwirble; Lisa A Weissfeld; R Scott Watson; Tim Rickert; Gordon D Rubenfeld Journal: Crit Care Med Date: 2004-03 Impact factor: 7.598
Authors: Anil N Makam; Oanh Kieu Nguyen; Lei Xuan; Michael E Miller; James S Goodwin; Ethan A Halm Journal: JAMA Intern Med Date: 2018-03-01 Impact factor: 21.873
Authors: Jeremy M Kahn; Rachel M Werner; Guy David; Thomas R Ten Have; Nicole M Benson; David A Asch Journal: Med Care Date: 2013-01 Impact factor: 2.983
Authors: David J Wallace; Derek C Angus; Christopher W Seymour; Amber E Barnato; Jeremy M Kahn Journal: Am J Respir Crit Care Med Date: 2015-02-15 Impact factor: 21.405
Authors: Martin S Zand; Melissa Trayhan; Samir A Farooq; Christopher Fucile; Gourab Ghoshal; Robert J White; Caroline M Quill; Alexander Rosenberg; Hugo Serrano Barbosa; Kristen Bush; Hassan Chafi; Timothy Boudreau Journal: PLoS One Date: 2017-04-20 Impact factor: 3.240