CHOP uses EHR data to identify cancer patients for malnutrition
Children’s Hospital of Philadelphia has developed what it says is the first automated pediatric malnutrition screening tool using electronic health record data.
Children’s Hospital of Philadelphia has developed what it says is the first automated pediatric malnutrition screening tool using electronic health record data.
In a study, published in the Journal of Nutrition and Dietetics, the tool analyzed anthropometric measurements in the hospital’s Epic EHR—including body mass index, height, length and weight—for inpatients in the pediatric oncology unit at CHOP for a little more than a year, representing about 2,100 hospitalizations.
Researchers used software to take note of changes in the anthropometric measurements to assess each hospitalized patient’s risk of malnutrition. For those pediatric cancer patients determined to be at risk, the automated program categorized their risk as either mild, moderate or severe.
In the study, 47 percent were classified as at mild risk, 24 percent as moderate risk and 29 percent as severe—consistent with clinical experience and other research. In addition, the overall prevalence of malnutrition was determined to be 42 percent for the study period, which was also consistent with previous studies.
“This test study demonstrates the feasibility of using EHR data to create an automated screening tool for malnutrition in pediatric inpatients,” says Charles Phillips, MD, the study’s leader and a pediatric oncologist at CHOP. “Further research is needed to formally assess this screening tool, but it has the potential to identify at-risk patients in the early stages of malnutrition, so we can intervene quickly. In addition, this tool could be implemented to screen all pediatric patients for malnutrition, because it uses data common to all electronic medical records.”
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Phillips notes that estimates vary—depending on the type of pediatric cancer—but as many as 60 percent of patients will have some form of malnutrition during therapy. He also points out that there is currently no universal standardized approach to screen children in hospitals.
“Electronic health record data is incredibly important,” concludes Phillips, who adds that the automated tool provides alerts to hospital clinicians so they can quickly conduct medical interventions if deemed necessary. An email to providers lists the patient’s name, medical record number, unit, as well as malnutrition severity level.
Ultimately, Phillips would like to “fully internalize” the tool into CHOP’s Epic EHR. “We also tried to keep the code relatively simple so that it theoretically could be compatible with any number of electronic health record vendors,” he says. “We’re thinking very carefully about how to best integrate this into sustainable clinical decision support.”
In a study, published in the Journal of Nutrition and Dietetics, the tool analyzed anthropometric measurements in the hospital’s Epic EHR—including body mass index, height, length and weight—for inpatients in the pediatric oncology unit at CHOP for a little more than a year, representing about 2,100 hospitalizations.
Researchers used software to take note of changes in the anthropometric measurements to assess each hospitalized patient’s risk of malnutrition. For those pediatric cancer patients determined to be at risk, the automated program categorized their risk as either mild, moderate or severe.
In the study, 47 percent were classified as at mild risk, 24 percent as moderate risk and 29 percent as severe—consistent with clinical experience and other research. In addition, the overall prevalence of malnutrition was determined to be 42 percent for the study period, which was also consistent with previous studies.
“This test study demonstrates the feasibility of using EHR data to create an automated screening tool for malnutrition in pediatric inpatients,” says Charles Phillips, MD, the study’s leader and a pediatric oncologist at CHOP. “Further research is needed to formally assess this screening tool, but it has the potential to identify at-risk patients in the early stages of malnutrition, so we can intervene quickly. In addition, this tool could be implemented to screen all pediatric patients for malnutrition, because it uses data common to all electronic medical records.”
Also See: Electronic alerts, new protocols help speed sepsis treatmentPhillips notes that estimates vary—depending on the type of pediatric cancer—but as many as 60 percent of patients will have some form of malnutrition during therapy. He also points out that there is currently no universal standardized approach to screen children in hospitals.
“Electronic health record data is incredibly important,” concludes Phillips, who adds that the automated tool provides alerts to hospital clinicians so they can quickly conduct medical interventions if deemed necessary. An email to providers lists the patient’s name, medical record number, unit, as well as malnutrition severity level.
Ultimately, Phillips would like to “fully internalize” the tool into CHOP’s Epic EHR. “We also tried to keep the code relatively simple so that it theoretically could be compatible with any number of electronic health record vendors,” he says. “We’re thinking very carefully about how to best integrate this into sustainable clinical decision support.”
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