Demographic and Clinical Profiles of Patients with Endometriosis

Judith W. Dexheimer, Parand Shams, Emily G. Hurley, Katie E. Smith, Sczcesniak Rhonda, Albert Hsu
2025 · doi:10.5281/zenodo.19473032 · W7151950745
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Researchers analyzed electronic health record data to identify demographic and clinical features most predictive of endometriosis, aiming to reduce diagnostic delays by distinguishing patients with the condition from those without.

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This study utilized electronic health record data to evaluate demographic and clinical differences between patients diagnosed with endometriosis and those without, aiming to identify the most predictive features for diagnosis. The research addressed the significant diagnostic delay often associated with the condition by applying feature selection techniques to determine key indicators within the patient population. By analyzing these variables, the authors sought to improve early detection strategies based on existing clinical records. This paper is centrally about endometriosis, focusing specifically on identifying predictive demographic and clinical profiles using EHR data to address diagnostic delays.

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Abstract

Background: Endometriosis affects 176 million women, with an average diagnostic delay of up to twelve years. We sought to evaluate differences between patients diagnosed with and without endometriosis, using electronic health record (EHR) data. Our goal was to use feature selection to determine the elements most predictive of endometriosis. Presented at: 16th World Congress on EndometriosisLocation: Sydney, AustriliaDates: May 21 to 24, 2025 Authors: Judith W. Dexheimer, PhD; Parand Shams, MS; Emily G. Hurley, MD; Katie Smith, WHNP; Rhonda Sczcesniak, PhD; Albert L. Hsu, MD Affiliations: Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical CenterDepartment of Pediatrics, College of Medicine, University of CincinnatiDepartment of Biostatistics, Health Informatics and Data Science, University of CincinnatiDivision of Reproductive Endocrinology and Infertility (REI), Department of Obstetrics and Gynecology, University of Cincinnati College of MedicineDivision of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical CenterDivision of Pulmonary Medicine, Cincinnati Children’s Hospital Medical Center
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Demographic and Clinical Profiles of Patients with Endometriosis Authors/Creators Description Background: Endometriosis affects 176 million women, with an average diagnostic delay of up to twelve years. We sought to evaluate differences between patients diagnosed with and without endometriosis, using electronic health record (EHR) data. Our goal was to use feature selection to determine the elements most predictive of endometriosis. Presented at: 16th World Congress on Endometriosis Location: Sydney, Austrilia Dates: May 21 to 24, 2025 Authors: Judith W. Dexheimer, PhD; Parand Shams, MS; Emily G. Hurley, MD; Katie Smith, WHNP; Rhonda Sczcesniak, PhD; Albert L. Hsu, MD Affiliations: Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center Department of Pediatrics, College of Medicine, University of Cincinnati Department of Biostatistics, Health Informatics and Data Science, University of Cincinnati Division of Reproductive Endocrinology and Infertility (REI), Department of Obstetrics and Gynecology, University of Cincinnati College of Medicine Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center Division of Pulmonary Medicine, Cincinnati Children’s Hospital Medical Center Files Abstract_WECAus.pdf Files (697.3 kB) | Name | Size | Download all | |---|---|---| | md5:4ba15ae918c3857013f167ed4d03398b | 697.3 kB | Preview Download |

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