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Updated: Jun 18, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Body weight and height data in electronic medical records of children
Ning Smith1, Karen J Coleman, Jean M Lawrence
1Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA.
Insights
Data entry errors in children's body weight and height measurements are infrequent. Improving data quality through simple methods can prevent misclassification of obesity and enhance population health management.
Area of Science:
- Pediatric Health
- Biostatistics
- Health Informatics
Background:
- Electronic health records (EHRs) are crucial for pediatric care.
- Data quality issues, such as errors in body weight and height measurements, can arise during routine medical encounters.
- These inaccuracies can lead to biologically implausible values, impacting data integrity.
Purpose of the Study:
- To evaluate the quality of body weight and height data for children aged 0-18 years.
- To assess the impact of data entry errors on pediatric health metrics.
- To determine the effectiveness of excluding implausible values in improving data accuracy.
Main Methods:
- Analysis of weight and height data from children (0-18 years) at Kaiser Permanente Southern California.
- Calculation of error rates before and after data cleaning.
- Exclusion of biologically implausible height and weight values from electronic medical record reviews.
Main Results:
- Initial error rates for weight and height varied by age group, ranging from 0.4% to 1.0%.
- Common errors included implausibly low heights and high weights.
- After excluding implausible values, error rates decreased significantly across all age groups, with the greatest reduction observed in older children.
Conclusions:
- Routine electronic medical record data for pediatric weight and height exhibit low error rates.
- Implementing simple data cleaning methods can further reduce errors, preventing misclassification of pediatric obesity.
- Accurate anthropometric data is valuable for population health management.
Objective:
Data entry errors may occur in body weights and heights assessed during routine medical care. These errors may affect data quality markedly and create a large number of biologically implausible values. To address this issue, we evaluated the quality of body weight and height measures for children based on sequential health care encounters.
Methods:
We evaluated the weight and height data of children aged 0-18 years receiving care at Kaiser Permanente Southern California medical centers. Error rates were calculated before and after excluding implausible values for height and weight as recorded in the electronic medical chart reviews.
Results:
The error rates in weight and height data of children aged <2, 2-5, 6-9, 10-13, 14-18 years were 0.4%, 0.7%, 1.0%, 1.0% and 0.7%, respectively. The most frequently identified errors were implausibly low values for height and implausibly high values for weight. After excluding implausible values, the error rates were 0.4%, 0.4%, 0.6%, 0.4% and 0.1%, respectively. The sensitivity of our approach to detect errors was 10.9%, 36.6%, 32.9%, 59.2%, and 82.5%, respectively.
Conclusions:
Error rates in weight and height recorded in the electronic medical record during routine medical care are low, raising the potential for this information to be used for population care management. With little effort and with the recording of this information at each encounter, error rates can be further lowered to avoid misclassification of children as obese.
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