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Credit: CDC
An early warning and response system can predict a patient’s likelihood of developing sepsis, according to research published in the Journal of Hospital Medicine.
The system uses lab and vital-sign data in the electronic health record of hospital inpatients to identify those at risk for sepsis.
In a multi-hospital study, the system allowed for a marked increase in sepsis identification and care, transfer to the intensive care unit (ICU), and an indication of fewer deaths due to sepsis.
Craig A. Umscheid, MD, of Penn Medicine in Philadelphia, and his colleagues developed the system using 4575 patients admitted to the University of Pennsylvania Health System in October 2011.
The system monitored lab values and vital signs in real time. If a patient had 4 or more predefined abnormalities at any single time, an electronic communication was sent to the provider, nurse, and rapid response coordinator, who performed an immediate bedside patient evaluation.
The researchers validated the effectiveness of the system during a pre-implementation period from June to September 2012, when data on admitted patients was evaluated and alerts triggered in a database, but no notifications were sent to providers on the ground.
Outcomes in that control period were then compared to a post-implementation period from June to September 2013. The total number of patients included in both periods was 31,093.
In the pre- and post-implementation periods, 4% of patient visits triggered the alert. Analysis revealed that 90% of those patients received bedside evaluations by the care team within 30 minutes of the alert being issued.
The system resulted in a 2- to 3-fold increase in orders for tests that could help identify the presence of sepsis and a 1.5- to 2-fold increase in the administration of antibiotics and intravenous fluids.
The system prompted an increase of more than 50% in the proportion of patients quickly transferred to the ICU and a 50% increase in documentation of sepsis in the patients’ electronic health record.
There was a lower death rate from sepsis and an increase in the number of patients successfully discharged home in the post-implementation period. But these rates were not significantly different from those in the pre-implementation period.
“Our study is the first we’re aware of that was implemented throughout a multihospital health system,” Dr Umscheid said.
“Previous studies that have examined the impact of sepsis prediction tools at other institutions have only taken place on a limited number of inpatient wards. The varied patient populations, clinical staffing, practice models, and practice cultures across our health system increases the generalizability of our findings to other healthcare settings.”
Dr Umscheid also noted that the system could help triage patients for suitability of ICU transfer.
“By better identifying those with sepsis requiring advanced care,” he said, “the tool can help screen out patients not needing the inevitably limited number of ICU beds.” 
Credit: CDC
An early warning and response system can predict a patient’s likelihood of developing sepsis, according to research published in the Journal of Hospital Medicine.
The system uses lab and vital-sign data in the electronic health record of hospital inpatients to identify those at risk for sepsis.
In a multi-hospital study, the system allowed for a marked increase in sepsis identification and care, transfer to the intensive care unit (ICU), and an indication of fewer deaths due to sepsis.
Craig A. Umscheid, MD, of Penn Medicine in Philadelphia, and his colleagues developed the system using 4575 patients admitted to the University of Pennsylvania Health System in October 2011.
The system monitored lab values and vital signs in real time. If a patient had 4 or more predefined abnormalities at any single time, an electronic communication was sent to the provider, nurse, and rapid response coordinator, who performed an immediate bedside patient evaluation.
The researchers validated the effectiveness of the system during a pre-implementation period from June to September 2012, when data on admitted patients was evaluated and alerts triggered in a database, but no notifications were sent to providers on the ground.
Outcomes in that control period were then compared to a post-implementation period from June to September 2013. The total number of patients included in both periods was 31,093.
In the pre- and post-implementation periods, 4% of patient visits triggered the alert. Analysis revealed that 90% of those patients received bedside evaluations by the care team within 30 minutes of the alert being issued.
The system resulted in a 2- to 3-fold increase in orders for tests that could help identify the presence of sepsis and a 1.5- to 2-fold increase in the administration of antibiotics and intravenous fluids.
The system prompted an increase of more than 50% in the proportion of patients quickly transferred to the ICU and a 50% increase in documentation of sepsis in the patients’ electronic health record.
There was a lower death rate from sepsis and an increase in the number of patients successfully discharged home in the post-implementation period. But these rates were not significantly different from those in the pre-implementation period.
“Our study is the first we’re aware of that was implemented throughout a multihospital health system,” Dr Umscheid said.
“Previous studies that have examined the impact of sepsis prediction tools at other institutions have only taken place on a limited number of inpatient wards. The varied patient populations, clinical staffing, practice models, and practice cultures across our health system increases the generalizability of our findings to other healthcare settings.”
Dr Umscheid also noted that the system could help triage patients for suitability of ICU transfer.
“By better identifying those with sepsis requiring advanced care,” he said, “the tool can help screen out patients not needing the inevitably limited number of ICU beds.”
Credit: CDC
An early warning and response system can predict a patient’s likelihood of developing sepsis, according to research published in the Journal of Hospital Medicine.
The system uses lab and vital-sign data in the electronic health record of hospital inpatients to identify those at risk for sepsis.
In a multi-hospital study, the system allowed for a marked increase in sepsis identification and care, transfer to the intensive care unit (ICU), and an indication of fewer deaths due to sepsis.
Craig A. Umscheid, MD, of Penn Medicine in Philadelphia, and his colleagues developed the system using 4575 patients admitted to the University of Pennsylvania Health System in October 2011.
The system monitored lab values and vital signs in real time. If a patient had 4 or more predefined abnormalities at any single time, an electronic communication was sent to the provider, nurse, and rapid response coordinator, who performed an immediate bedside patient evaluation.
The researchers validated the effectiveness of the system during a pre-implementation period from June to September 2012, when data on admitted patients was evaluated and alerts triggered in a database, but no notifications were sent to providers on the ground.
Outcomes in that control period were then compared to a post-implementation period from June to September 2013. The total number of patients included in both periods was 31,093.
In the pre- and post-implementation periods, 4% of patient visits triggered the alert. Analysis revealed that 90% of those patients received bedside evaluations by the care team within 30 minutes of the alert being issued.
The system resulted in a 2- to 3-fold increase in orders for tests that could help identify the presence of sepsis and a 1.5- to 2-fold increase in the administration of antibiotics and intravenous fluids.
The system prompted an increase of more than 50% in the proportion of patients quickly transferred to the ICU and a 50% increase in documentation of sepsis in the patients’ electronic health record.
There was a lower death rate from sepsis and an increase in the number of patients successfully discharged home in the post-implementation period. But these rates were not significantly different from those in the pre-implementation period.
“Our study is the first we’re aware of that was implemented throughout a multihospital health system,” Dr Umscheid said.
“Previous studies that have examined the impact of sepsis prediction tools at other institutions have only taken place on a limited number of inpatient wards. The varied patient populations, clinical staffing, practice models, and practice cultures across our health system increases the generalizability of our findings to other healthcare settings.”
Dr Umscheid also noted that the system could help triage patients for suitability of ICU transfer.
“By better identifying those with sepsis requiring advanced care,” he said, “the tool can help screen out patients not needing the inevitably limited number of ICU beds.”