Literature DB >> 17925432

Intensive care services in the Veterans Health Administration.

Peter Almenoff1, Anne Sales, Sharon Rounds, Michael Miller, Kelly Schroeder, Karen Lentz, Jonathan Perlin.   

Abstract

OBJECTIVE: We describe the national organization and distribution of intensive care services within the Veterans Health Administration (VHA), the largest single integrated health-care system in the United States. DATA SOURCES: Data come primarily from the 2004 Survey of Intensive Care Units in VHA, an electronically distributed survey of all ICUs in the VHA. Medical directors and nurse managers from all 213 ICUs in the VHA responded to the survey. In addition, we extracted data on the number of ICU admissions and unique veterans served from national VHA databases.
RESULTS: The VHA has a geographically dispersed, multilevel system of care with variation in geographic access for eligible veterans (varying from 3.1 to 3.5 ICU beds per 1,000 patient discharges) and variation in service provision (from 10 to 19 level 1 ICUs across four regions). Level 1 ICUs are the highest tertiary-level ICUs, with the full range of subspecialty care. The proportion of beds associated with VHA-developed ICU levels of care ranges from 55% level 1 beds in the Northeast to 73% in the South, while level 4 beds represent 4% of all ICU beds in the South and 10% in the Midwest.
CONCLUSIONS: Overall, the VHA system has a fair amount of regional variation, but level 1 ICUs are available in all geographic regions, and there are regional clusters of all levels. Adopting a four-level system for rating ICUs may assist in monitoring and assessing the quality of care provided in the smallest, most rural facilities.

Entities:  

Mesh:

Year:  2007        PMID: 17925432     DOI: 10.1378/chest.06-3083

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  4 in total

1.  The benefits of designing a stratification system for New York City pediatric intensive care units for use in regional surge capacity planning and management.

Authors:  Christiana Campbell
Journal:  J Community Health       Date:  2010-08

2.  Using electronic medical record notes to measure ICU telemedicine utilization.

Authors:  Amy M J O'Shea; Mary Vaughan Sarrazin; Boulos Nassar; Peter Cram; Lynelle Johnson; Robert Bonello; Ralph J Panos; Heather S Reisinger
Journal:  J Am Med Inform Assoc       Date:  2017-09-01       Impact factor: 4.497

3.  The STS case study: an analysis method for longitudinal qualitative research for implementation science.

Authors:  Jennifer M Van Tiem; Heather Schacht Reisinger; Julia E Friberg; Jaime R Wilson; Lynn Fitzwater; Ralph J Panos; Jane Moeckli
Journal:  BMC Med Res Methodol       Date:  2021-02-05       Impact factor: 4.615

4.  Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system.

Authors:  Daniel Molling; Brenda M Vincent; Wyndy L Wiitala; Gabriel J Escobar; Timothy P Hofer; Vincent X Liu; Amy K Rosen; Andrew M Ryan; Sarah Seelye; Hallie C Prescott
Journal:  Medicine (Baltimore)       Date:  2020-06-12       Impact factor: 1.817

  4 in total

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