CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i
Leveraging Automated Approaches to Categorize Birth Defects from Abstracted Birth Hospitalization Data
-
1 2024
-
-
Source: Birth Defects Res. 116(1):e2267
Details:
-
Alternative Title:Birth Defects Res
-
Personal Author:
-
Description:Background:
The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) collects data abstracted from medical records and birth defects registries on pregnant people and their infants to understand outcomes associated with prenatal exposures. We developed an automated process to categorize possible birth defects for prenatal COVID-19, hepatitis C, and syphilis surveillance. By employing keyword searches, fuzzy matching, natural language processing (NLP), and machine learning (ML), we aimed to decrease the number of cases needing manual clinician review.
Methods:
SET-NET captures International Classification of Diseases, 10thRevision, Clinical Modification (ICD-10-CM) codes and free text describing birth defects. For unstructured data, we used keyword searches, then conducted fuzzy matching with a cut-off match score of ≥90%. Finally, we employed NLP and ML by testing three predictive models to categorize birth defect data.
Results:
As of June 2023, 8,326 observations containing data on possible birth defects were submitted to SET-NET. The majority (n=6,758 [81%]) were matched to an ICD-10-CM code and 1,568 (19%) were unable to be matched. Through keyword searches and fuzzy matching, we categorized 1,387/1,568 possible birth defects. Of the remaining 181 unmatched observations, we correctly categorized 144 (80%) using a predictive model.
Conclusions:
Using automated approaches allowed for categorization of 99.6% of reported possible birth defects, which helps detect possible patterns requiring further investigation. Without employing these analytic approaches, manual review would have been needed for 1,568 observations. These methods can be employed to quickly and accurately sift through data to inform public health responses.
-
Subjects:
-
Keywords:
-
Source:
-
Pubmed ID:37932954
-
Pubmed Central ID:PMC10872559
-
Document Type:
-
Funding:
-
Volume:116
-
Issue:1
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type: