Background: Since long-term outcome data for individuals with differences of sex development (DSD) remain limited, current consensus statements emphasize the need for standardized, longitudinal, multidisciplinary care, and systematic outcome evaluation to improve healthcare delivery and research for this heterogeneous and rare group of conditions.
Aim: To describe the design and implementation of a structured, multidisciplinary follow-up program for children and adolescents with DSD in a tertiary care setting, integrating a health intelligence approach to facilitate data-driven care and research.
Methods: The program was developed at Amsterdam UMC, Emma Children's Hospital, as part of the so-called Follow Me initiative. Patients were identified using International Classification of Diseases Tenth Revision codes and categorized into 3 diagnostic groups: XX and XY DSD, Turner syndrome, and sex chromosome trisomies including Klinefelter syndrome (SCT). Standardized care pathways were developed in collaboration with the multidisciplinary DSD team (MDT), based on existing literature. An automated data pipeline was built to securely transfer clinical data to a hospital-wide data warehouse.
Outcomes: A reproducible framework for cohort identification, care pathways for structured, multidisciplinary care, and an automated data-infrastructure for clinical outcome collection and monitoring.
Results: In January 2024, 620 patients under the age of 18 were identified as eligible for inclusion in the program: 466 in the XX and XY DSD group, 72 with Turner syndrome, and 82 in the SCT group. Standardized follow-up pathways were implemented for each group. Interactive dashboards were developed to visualize real-time clinical outcomes, which are used during MDT meetings and annual care evaluations to monitor quality and effectiveness of care.
Clinical implications: This study demonstrates how integrating multidisciplinary care with a health intelligence program enables data-driven medicine to promote consistent, high-quality care for individuals with DSD and generate valuable data for clinical evaluation and innovation, and research purposes.
Strengths and limitations: This is the first reported initiative translating existing recommendations into a practical framework that supports structured, multidisciplinary care across all diagnostic groups and facilitates systematic automated data collection. Nevertheless, the current implementation is limited to pediatric care within a single center, though expansion is feasible.
Conclusion: This study presents a framework for standardized, long-term care for children and adolescents with DSD, supported by health intelligence, that meets the need for longitudinal outcome data, enhances care quality, and drives innovation.
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