Hospital Carlos Van Buren
Valparaíso, Valparaiso, 2341131, Chile
Location status: Recruiting
NCT Number: NCT06725901
This study evaluates a diagnostic support platform, DIAGEN-IA, designed to identify pediatric neurological diseases with a genetic basis. Conducted at Carlos Van Buren Hospital in Chile, it aims to determine if the platform reduces inappropriate referrals to clinical geneticists, improves diagnostic evaluations, enhances referral quality, and increases user satisfaction. A prospective before-and-after design will compare outcomes across two phases: baseline data collection and an intervention phase using DIAGEN-IA. Healthcare professionals will use the platform to guide referrals and diagnostic studies. Outcomes include referral appropriateness, completeness of evaluations, quality of referrals, and user satisfaction.
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Interventional
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Valparaíso, Valparaiso, 2341131, Chile
Location status: Recruiting
This study aims to evaluate the DIAGEN-IA diagnostic support platform, developed to assist in the identification of pediatric neurological diseases with a genetic basis. The primary objective is to assess whether the platform reduces the proportion of inappropriate referrals to clinical geneticists. Secondary objectives include improving the completeness of initial diagnostic evaluations, enhancing the quality of referral requests, and evaluating user satisfaction with the platform.
The study will be conducted at Carlos Van Buren Hospital in Valparaíso, a high-complexity hospital serving over 486,000 individuals. Using a prospective before-and-after design, the study is divided into two phases. The initial 6-month phase will collect baseline data on referrals, their appropriateness, and the completeness of initial diagnostic evaluations. Interobserver variability among geneticists will also be analyzed. In the 6-month intervention phase, healthcare professionals will use DIAGEN-IA during consultations, and the same outcomes will be reassessed.
Participants include healthcare providers from primary and secondary care centers who manage pediatric patients and are responsible for referring cases to clinical geneticists. Eligible participants must be Spanish-speaking professionals with advanced proficiency, working with children under 18 years old, and involved in diagnosing rare diseases. Data will be anonymized, and demographic information such as age, gender, specialty, years of practice, and specific training in genetics or metabolic disorders will be collected.
DIAGEN-IA is a platform co-designed with input from neuropediatricians and geneticists, integrating the Orphanet ontologies (ORDO, HPO, and HOOM) to ensure comprehensive diagnostic support. The application employs a Bayesian network model to recommend differential diagnoses and appropriate tests based on phenotypic characteristics. This AI-driven approach enables interpretable decision-making and models uncertainty inherent in rare disease diagnosis. The platform operates on a client-server architecture and supports seamless integration into clinical workflows.
Primary outcomes include the proportion of referrals deemed inappropriate, assessed using a 5-point Likert scale by clinical geneticists. Secondary outcomes focus on referral quality, evaluated against standardized criteria, and user satisfaction, measured with the validated CSQ-8 questionnaire. User satisfaction will be assessed at one and six months during the intervention phase. Results will inform strategies to optimize referral processes and diagnostic accuracy in pediatric care.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
The intervention involves the DIAGEN-IA platform, a diagnostic support tool designed to identify pediatric neurological diseases with a genetic basis. Using a Bayesian network model and integrating ontologies such as ORDO, HPO, and HOOM, DIAGEN-IA links phenotypic data entered by physicians to suggested diagnoses and tests. Pediatric neurologists will be trained to use the platform during a 12-month intervention. DIAGEN-IA allows clinicians to input clinical and diagnostic data, generating differential diagnoses and recommended tests, with results exportable in PDF for integration into medical records. Platform usage will be tracked, including login frequency, time spent, and evaluations performed.
Time frame: 6 months
The primary outcome of this study is the proportion of referrals deemed inappropriate by clinical geneticists. Appropriateness is assessed using a 5-point Likert scale, where referrals scoring 1 or 2 are classified as inappropriate. This evaluation considers all referral requests received during the study period, regardless of whether an in-person evaluation occurred.
Time frame: 6 months
The completeness of evaluations in this study is assessed using Morera's scale, adapted for the study's objectives. This scale evaluates whether essential components such as clinical history, findings from physical examinations, relevant diagnostic tests, and a clear presumptive or differential diagnosis are sufficiently detailed to justify the referral. Referrals are categorized into four levels: Very Poor (minimal or no relevant data), Poor (some clinical or test data but insufficient for a justified referral), Normal (adequate data with a basic diagnostic judgment), and Very Good (comprehensive history, examination, and tests with a clear diagnostic justification).
Time frame: 1 and 6 months
User satisfaction will be evaluated using the Client Satisfaction Questionnaire (CSQ-8), a validated tool widely used in healthcare settings. The CSQ-8 consists of eight questions, each scored on a 4-point Likert scale, assessing users' perceptions of the utility, quality, and impact of the service provided. Scores range from 8 to 32, with higher scores indicating greater satisfaction. The questionnaire is designed to be self-administered and has undergone extensive linguistic validation, including in Spanish.
Contact information is provided by the study sponsor or research team.
Universidad Nacional Andres Bello
Other
Diagnostic Support Platform for the Identification of Pediatric Genetic Neurological Diseases Through a Machine Learning-Based Recommendation System
Acronym: DIAGEN-IA
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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