Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data

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, 10th Revision, Clinical Modification (ICD-10-CM) codes and free text describing birth defects. For unstructured data, we used keyword searches, and 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, 8326 observations containing data on possible birth defects were submitted to SET-NET. The majority (n = 6758 [81%]) were matched to an ICD-10-CM code and 1568 (19%) were unable to be matched. Through keyword searches and fuzzy matching, we categorized 1387/1568 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 1568 observations. These methods can be employed to quickly and accurately sift through data to inform public health responses.

Urban and Rural Mpox Incidence Among Persons Aged 15-64 Years - United States, May 10-December 31, 2022

During May 10-December 31, 2022, a total of 29,980 confirmed and probable^† U.S. monkeypox (mpox) cases were reported to CDC, predominantly in cisgender adult men reporting recent same-gender sexual partners (1). Urban-rural differences in health (2) and diagnosis of HIV (3,4) and other sexually transmitted infections (5) are well documented nationally. This report describes urban-rural differences in mpox incidence (cases per 100,000 population) among persons aged 15-64 years, by gender and race and ethnicity. Urbanicity was assessed using the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme for Counties (2). Substantial differences in incidence by urbanicity, gender, and race and ethnicity were observed; most (71.0%) cases occurred in persons residing in large central urban areas. Among the cases in large central urban areas, most (95.7%) were in cisgender men. The overall incidence of mpox in the United States was 13.5 per 100,000 persons aged 15-64 years and peaked in August in both urban and rural areas. Among cisgender men, incidence in rural areas was approximately 4% that in large central urban areas (risk ratio [RR] = 0.04). Among cisgender women, incidence in rural areas was approximately 11% that in large central urban areas (RR = 0.11). In both urban and rural areas, incidence among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) persons was consistently higher than that among non-Hispanic White (White) persons; RRs between Black and White persons were highest in rural areas. Support and maintenance of mpox surveillance and prevention efforts including vaccinations should focus on urban areas with the highest incidence of mpox during the 2022 outbreak; however, surveillance and prevention efforts should include all genders, persons of color, and persons residing in both urban and rural areas who are at increased risk for mpox.

Atlanta Residents' Knowledge Regarding Heavy Metal Exposures and Remediation in Urban Agriculture

Urban agriculture and gardening provide many health benefits, but the soil is sometimes at risk of heavy metal and metalloid (HMM) contamination. HMM, such as lead and arsenic, can result in adverse health effects for humans. Gardeners may face exposure to these contaminants because of their regular contact with soil and consumption of produce grown in urban areas. However, there is a lack of research regarding whether differential exposure to HMM may be attributed to differential knowledge of exposure sources. In 2018, industrial slag and hazardous levels of soil contamination were detected in West Atlanta. We conducted community-engaged research through surveys and follow-up interviews to understand awareness of slag, HMM in soil, and potential remediation options. Home gardeners were more likely to recognize HMM health effects and to cite health as a significant benefit of gardening than community gardeners. In terms of knowledge, participants were concerned about the potential health effects of contaminants in soil yet unconcerned with produce in their gardens. Gardeners’ knowledge on sources of HMM exposure and methods for remediation were low and varied based on racial group.