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Global birth defects app: An innovative tool for describing and coding congenital anomalies at birth in low resource
Helen Dolk1, Aminkeng Zawuo Leke1, Phil Whitfield2
1Centre for Maternal, Fetal and Infant Research, Institute for Nursing and Health Research, Ulster University, Newtownabbey, United Kingdom.
Insights
A new mobile health app aids in identifying and coding congenital anomalies in low-resource settings. This tool supports global birth defect surveillance, improving prevention and care for affected newborns.
Area of Science:
- Public Health
- Medical Informatics
- Global Health
Background:
- Congenital anomaly surveillance in low- and middle-income countries (LMICs) faces challenges in data accuracy.
- Limited resources hinder effective data collection and analysis for birth defects.
Purpose of the Study:
- To develop a mobile health (mHealth) tool for describing and coding externally visible congenital anomalies.
- To overcome language and terminology barriers in low-resource settings for birth defect identification.
Main Methods:
- An app was developed with "basic" and "surveillance" versions, featuring images, definitions, and ICD-10 codes for 98 anomalies and 12 syndromes.
- The "basic" version provides visual aids and guidance for anomaly identification.
- The "surveillance" version allows for pseudonymized data collection and secure uploading for analysis.
Main Results:
- The app includes detailed descriptions, images, and coding for numerous congenital anomalies and syndromes, including congenital Zika syndrome.
- The "basic" app version is available on major app stores and has been downloaded in 39 countries since its launch.
- The "surveillance" version is currently undergoing field testing.
Conclusions:
- The developed mHealth tool can significantly enhance congenital anomaly surveillance in resource-limited settings.
- This app supports improved prevention strategies and clinical care for newborns with birth defects globally.
Background:
Surveillance programs in low- and middle-income countries (LMICs) have difficulty in obtaining accurate information about congenital anomalies.
Methods:
As part of the ZikaPLAN project, an International Committee developed an app for the description and coding of congenital anomalies that are externally visible at birth, for use in low resource settings. The "basic" version of the app was designed for a basic clinical setting and to overcome language and terminology barriers by providing diagrams and photos, sourced mainly from international Birth Defects Atlases. The "surveillance" version additionally allows recording of limited pseudonymized data relevant to diagnosis, which can be uploaded to a secure server, and downloaded by the surveillance program data center.
Results:
The app contains 98 (88 major and 10 minor) externally visible anomalies and 12 syndromes (including congenital Zika syndrome), with definitions and International Classification of Disease v10 -based code. It also contains newborn examination videos and links to further resources. The user taps a region of the body, then selects among a range of images to choose the congenital anomaly that best resembles what they observe, with guidance regarding similar congenital anomalies. The "basic" version of the app has been reviewed by experts and made available on the Apple and Google Play stores. Since its launch in November 2019, it has been downloaded in 39 countries. The "surveillance" version is currently being field-tested.
Conclusion:
The global birth defects app is a mHealth tool that can help in developing congenital anomaly surveillance in low resource settings to support prevention and care.
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