Abstract

Abortion is a common occurrence during pregnancy. Intelligent technologies can be developed to assist in predicting abortions. This study aims to identify the essential data elements necessary for creating an intelligent system to predict abortion in pregnant women, which represents the first step in the creating of such systems. This descriptive research was conducted in the years 2022-2023. In this study, to access the essential data elements, accredited printed and electronic scientific sources, as well as paper and electronic hospital records, were reviewed. Then, a questionnaire was developed that confirmed its validity by experts, and its reliability was calculated with Cronbach’s alpha coefficient, which was 0.83. Then, the questionnaire was distributed among faculty members holding specialty and subspecialty degrees in obstetrics and gynecology, as well as Ph.D.s in health information management and medical informatics. The collected data were analyzed. A total of 19 managerial data elements and 126 clinical data elements were identified across 9 subclasses. Precautionary and preventive measures for pregnant mothers at risk can be provided with the aid of intelligent systems to predict abortion that to develop these systems, the presence of valid and important data elements is required.