Computerized Decision Support System Improves Fluid Resuscitation Outcomes Following Severe Burns: An Original Study

Abstract

Objective: Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was to analyze the efficacy of a computerized open-loop decision support system for burn resuscitation compared to historical controls. Design: Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group. Setting: Burn intensive care unit of a metropolitan Level 1 Trauma center. Patients: Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn. Measurements and Main Results: We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2011
Accession Number
ADA619106

Entities

People

  • Charles E Wade
  • Elizabeth A. Mann
  • Evan M. Renz
  • George C. Kramer
  • Josè Salinas
  • Kevin K Chung
  • Leopoldo C. Cancio
  • Maria L. Serio-melvin
  • Steven Wolf

Organizations

  • United States Army Institute of Surgical Research

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Burns
  • Combat Casualty Care
  • Computers
  • Decision Support Systems
  • Fluid Dynamics
  • Health Services
  • Information Systems
  • Intensive Care Units
  • Medical Personnel
  • Patient Care
  • Resuscitation
  • Standards
  • Therapy

Readers

  • Computer Science.
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Trauma Surgery or Emergency Medicine.