| Autor: |
Pi-I D Lin, Sheryl L Rifas-Shiman, Izzuddin M Aris, Matthew F Daley, David M Janicke, William J Heerman, Daniel L Chudnov, David S Freedman, Jason P Block |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
JAMIA Open. 5 |
| ISSN: |
2574-2531 |
| DOI: |
10.1093/jamiaopen/ooac089 |
| Popis: |
Objective To demonstrate the utility of growthcleanr, an anthropometric data cleaning method designed for electronic health records (EHR). Materials and Methods We used all available pediatric and adult height and weight data from an ongoing observational study that includes EHR data from 15 healthcare systems and applied growthcleanr to identify outliers and errors and compared its performance in pediatric data with 2 other pediatric data cleaning methods: (1) conditional percentile (cp) and (2) PaEdiatric ANthropometric measurement Outlier Flagging pipeline (peanof). Results 687 226 children ( Conclusion growthcleanr is useful for cleaning pediatric and adult height and weight data. It is the only method with the ability to clean adult data and identify carried-forward and duplicates, which are prevalent in EHR. Findings of this study can be used to improve the growthcleanr algorithm. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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