Paediatric malnutrion: EHRs offer automated warnings

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  • Published: Oct 15, 2018
  • Author: David Bradley
  • Channels: Chemometrics & Informatics
thumbnail image: Paediatric malnutrion: EHRs offer automated warnings

Automated screening

Data from electronic health records (EHR) can be used to create an automated screening tool for malnutrition in paediatric hospital inpatients, according to work by a US team of clinicians, dietitians, and researchers.

Data from electronic health records (EHR) can be used to create an automated screening tool for malnutrition in paediatric hospital inpatients, according to work by a US team of clinicians, dietitians, and researchers. The system developed by Charles Phillips of the Children's Hospital of Philadelphia and colleagues provides daily alerts to healthcare providers so they can quickly intervene with appropriate treatment.

"Undernutrition is extremely common in children with cancer - the population we studied in this project," explains Phillips, who is a paediatric oncologist at the hospital. "There is currently no universal, standardized approach to nutrition screening for children in hospitals, and our project is the first fully automated pediatric malnutrition screen using EHR data." The multidisciplinary team published details of their approach in the Journal of Nutrition and Dietetics.

Improving health outcomes

Health outcomes for seriously ill children in hospital can often depend on nutrition evaluation and intervention. Not only is nutrition while the child is in inpatient important because of the disease for which they are being treated but if it is long-term treatment physical and cognitive development have to be considered too, wound healing following surgery, immune function to preclude infections, and at an even more fundamental level the child's quality of life and the risk of mortality. Phillips adds that although the current study used oncology patients as a test case, the same automated screening could easily be used in other paediatric wards and for patients where a high prevalence of malnutrition is commonplace.

The team analysed EHR data from inpatients at the hospital's 54-bed paediatric oncology unit for late 2016 to early 2018, which covered around 2100 hospital admissions. The anthropometric measurements in the EHR included height, length, weight and body mass index. The researchers used software to take note of changes in those measurements, and used criteria issued by the Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition, to evaluate each patient's risk of malnutrition based on the ongoing measurements and the EHR data.

For each child that the screening program determined to be at risk of under-nutrution, the software would apply a flag of mild, moderate, or severe, and then automatically send an email to the clinicians on the ward giving them each patient's name, medical record number, unit, and malnutrition severity level, as well as other data.

Inpatients

In the patient cohort, the researchers' automated screen calculated the overall prevalence of malnutrition at 42 percent for the entire period of study. This was consistent with the range expected from previous studies where up to about 65 percent for inpatient paediatric oncology patients is observed). Overall severity levels for malnutrition were 47 percent in the mild category, 24 percent moderate and 29 percent severe; again, consistent with other research and clinical experience.

"This test study demonstrates the feasibility of using EHR data to create an automated screening tool for malnutrition in pediatric inpatients," explains Phillips. "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."

Related Links

J Nutr Dietet 2018, online: "Implementation of an automated pediatric malnutrition screen using anthropometric measurements in the electronic health record"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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