Computerized decision support system improves fluid resuscitation following severe burns

An original study

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

Research output: Contribution to journalArticle

72 Citations (Scopus)

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. Conclusions: Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care.

Original languageEnglish (US)
Pages (from-to)2031-2038
Number of pages8
JournalCritical Care Medicine
Volume39
Issue number9
DOIs
StatePublished - Sep 2011

Fingerprint

Burns
Resuscitation
Body Surface Area
Intensive Care Units
Decision Support Techniques
Trauma Centers
Wounds and Injuries
Patient Care
Age Groups
Body Weight
Technology
crystalloid solutions

Keywords

  • automated systems
  • burn care
  • burn resuscitation
  • computer decision support
  • crystalloid infusion
  • information technology

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

Cite this

Computerized decision support system improves fluid resuscitation following severe burns : An original study. / Salinas, José; Chung, Kevin K.; Mann, Elizabeth A.; Cancio, Leopoldo C.; Kramer, George; Serio-Melvin, Maria L.; Renz, Evan M.; Wade, Charles E.; Wolf, Steven.

In: Critical Care Medicine, Vol. 39, No. 9, 09.2011, p. 2031-2038.

Research output: Contribution to journalArticle

Salinas, José ; Chung, Kevin K. ; Mann, Elizabeth A. ; Cancio, Leopoldo C. ; Kramer, George ; Serio-Melvin, Maria L. ; Renz, Evan M. ; Wade, Charles E. ; Wolf, Steven. / Computerized decision support system improves fluid resuscitation following severe burns : An original study. In: Critical Care Medicine. 2011 ; Vol. 39, No. 9. pp. 2031-2038.
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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. Conclusions: Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care.",
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