Standardized clinical data capture to describe cerebral palsy

Area of Science:

• Neurology
• Pediatrics
• Clinical Informatics

Background:

• Cerebral palsy (CP) characterization is often limited by traditional data collection methods like registries and chart reviews.
• Existing methods may not capture comprehensive data on functional classification systems crucial for CP management.
• There is a need for standardized methodologies to gather detailed clinical information in routine care settings.

Purpose of the Study:

• To establish a standardized methodology for collecting clinically relevant information on young individuals with CP.
• To integrate caregiver and clinician-entered data into routine clinical practice at a specialized CP center.
• To describe the manifestation of CP and identify predictors of functional outcomes in this population.

Main Methods:

• Development and implementation of a caregiver-facing intake form and a clinician-facing standardized note template.
• Integration of these tools into the workflow of a tertiary care CP center.
• Extraction and analysis of data from individuals diagnosed with CP between March 2023 and December 2023.

Main Results:

• High data capture rate (97%) from both caregivers and clinicians.
• Prevalence of quadriplegia (47.0%), spasticity with dystonia (40.7%), independent walking (58.1%), safe oral feeding (55.9%), and understandable speech (42.6%) noted.
• Cortical grey matter injury and initial intensive care unit stay duration significantly impacted the odds of walking, oral feeding, and speech (p<0.001).

Conclusions:

• A standardized methodology effectively captured comprehensive data on individuals with CP in a tertiary care setting.
• The collected data enabled the identification of medical features influencing key functional outcomes.
• Sharing this methodology aims to promote replication and enhance understanding of CP manifestations across different sites.