Rare disease monitoring plans: a case study within a clinical decision support system

Introduction Clinical decision support systems (CDSS) have emerged as valuable tools for enhancing healthcare for rare diseases. Nonetheless, most tools focus on diagnosis, while few support patient monitoring. We aim to report the methods to develop an evidence-based CDSS for monitoring rare diseases, using Bardet-Biedl Syndrome (BBS) as a case study. Methods We assembled a multidisciplinary team of over 40 healthcare providers from 11 specialities to develop rare disease monitoring plans. We conducted a scoping review to map the existing literature on BBS monitoring, followed by the systematic development of a plan framework with four sections: a tailored medical record with clinical manifestations, a multidisciplinary appointment schedule, a questionnaire tracker, and a complementary exam tracker. We extracted data from articles, books, guidelines, and point-of-care resources. Results We included 128 references in the analysis. Common study designs included case reports (37.5%), case series (19.5%), and cohort studies (16.4%). We documented 108 clinical manifestations of BBS across ten body systems. The multidisciplinary appointment schedule identified 24 healthcare professionals essential for BBS follow-up, and primary consultations were recommended with 13 specialities. We identified 28 scales and questionnaires, 8 sets of laboratory analyses, 7 electrophysiological studies, and 6 imaging studies for patient follow-up. Conclusion Our CDSS provides a structured, evidence-based approach to monitoring BBS and improving patient outcomes. This model can be adapted for other rare diseases, promoting comprehensive and multidisciplinary patient care.

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Journal
Computers in Biology and Medicine
Published
2026-06-18
DOI
https://doi.org/10.1016/j.compbiomed.2026.111814
Primary Topic
Genetic and Kidney Cyst Diseases
Type
article
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article

Rare disease monitoring plans: a case study within a clinical decision support system

Carina F. Argüelles, Ayla Gerk, Jorgelina Stegmann, Letícia Nunes Campos et al.
Computers in Biology and Medicine
Genetic and Kidney Cyst Diseases
article

Rare disease monitoring plans: a case study within a clinical decision support system

Carina F. Argüelles, Ayla Gerk, Jorgelina Stegmann, Letícia Nunes Campos, Federico Fernandez Zelcer, Israel Dávila Rivera, Carlos Stegmann, Ivo Valentin Rudzinski, Gabriela Oriana Pintos, Santino Curto, Santiago Miguel Maximowicz, Rashid Benítez Yazbek
article en

Abstract

Introduction Clinical decision support systems (CDSS) have emerged as valuable tools for enhancing healthcare for rare diseases. Nonetheless, most tools focus on diagnosis, while few support patient monitoring. We aim to report the methods to develop an evidence-based CDSS for monitoring rare diseases, using Bardet-Biedl Syndrome (BBS) as a case study. Methods We assembled a multidisciplinary team of over 40 healthcare providers from 11 specialities to develop rare disease monitoring plans. We conducted a scoping review to map the existing literature on BBS monitoring, followed by the systematic development of a plan framework with four sections: a tailored medical record with clinical manifestations, a multidisciplinary appointment schedule, a questionnaire tracker, and a complementary exam tracker. We extracted data from articles, books, guidelines, and point-of-care resources. Results We included 128 references in the analysis. Common study designs included case reports (37.5%), case series (19.5%), and cohort studies (16.4%). We documented 108 clinical manifestations of BBS across ten body systems. The multidisciplinary appointment schedule identified 24 healthcare professionals essential for BBS follow-up, and primary consultations were recommended with 13 specialities. We identified 28 scales and questionnaires, 8 sets of laboratory analyses, 7 electrophysiological studies, and 6 imaging studies for patient follow-up. Conclusion Our CDSS provides a structured, evidence-based approach to monitoring BBS and improving patient outcomes. This model can be adapted for other rare diseases, promoting comprehensive and multidisciplinary patient care.

Computers in Biology and MedicineVol. 213
National University of Misiones (AR), Universidad de Buenos Aires (AR), McGill University Health Centre (CA), Recombinant Antibody Technology (United Kingdom) (GB), Fundación Huésped (AR), Fundación para la Investigación, Docencia y Prevención del Cáncer (AR), Instituto de Biología Subtropical (AR), Universidade de Pernambuco (BR)
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Genetic and Kidney Cyst Diseases
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