Abstract Details

Title Application of a Clinical Algorithm on Real-World Electronic Medical Record Data to Assist With Earlier Detection of Amyotrophic Lateral Sclerosis

Topic General Neurology

Presentation(s) P8 - Poster Session 8 (8:00 AM-9:00 AM)

Poster/Presentation
Number 2-010

Objective To integrate a clinical algorithm applied to neurologists’ electronic medical record (EMR) data to reduce the delay in time to diagnosis and treatment for patients with amyotrophic lateral sclerosis (ALS).

Background ALS is a rare and progressive neurodegenerative disease that is difficult to diagnose. An estimated 3000 Canadians are living with ALS and approximately 1000 are diagnosed annually. Delayed ALS diagnosis, reported to range from 9.1 to 27 months, can lead to mismanagement and deterioration of patient outcomes. To date, no single test definitively confirms ALS. Algorithm-based tools may be used to help physicians improve the timeliness and accuracy of ALS diagnosis.

Design/Methods A clinical algorithm applied to neurologists’ EMR data categorizes patients into risk groupings based on evidence of upper and lower motor neuron abnormalities and spinal region involvement. EMR records of participating clinics are scanned and the likelihood of ALS is estimated for patients whose records include a recent electromyography test. A report is sent to the clinic for each patient flagged for follow up. In an initial study, the algorithm demonstrated improved sensitivity and specificity of 93.9% and 98.0%, respectively, when compared to an original proof-of-concept study. This software has been registered as a class 1 medical device (Health Canada). An ongoing, 12-month pilot study aims to deploy this algorithm within 20 community clinics.

Results Results to be presented.

Conclusions Clinical algorithms may aid in the diagnosis of ALS when applied to real-world EMR data in neurological community practice. The algorithm in this study has been proven to identify patients with an elevated risk of ALS to support expedited follow up, diagnosis, and treatment. This study is ongoing, and additional details aimed to improve the results of earlier algorithm testing and increase exposure to the clinical community are currently being investigated.

Authors/Disclosures
Amanda E. Fiander, MD (Maritime Neurology) PRESENTER	Dr. Fiander has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Mitsubishi Tanabe Pharmaceuticals. Dr. Fiander has received research support from Mitsubishi Tanabe Pharmaceuticals.
Amer A. Ghavanini, MD	Dr. Ghavanini has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Mitisubishi Tanabe Pharm.
Dung Pham, PhD	Mr. Pham has received personal compensation for serving as an employee of Mitsubishi Tanabe Pharma Canada.
Pinay Kainth	Pinay Kainth has received personal compensation for serving as an employee of Mitsubishi Tanabe Pharma Canada. Pinay Kainth has received personal compensation for serving as an employee of Ultragenyx Canada.
Angela L. Genge, MD (Mcgill University)	Dr. Genge has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for AL-S Pharma. Dr. Genge has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Amylyx. Dr. Genge has received personal compensation in the range of $100,000-$499,999 for serving as a Consultant for Quralis. Dr. Genge has received personal compensation in the range of $500-$4,999 for serving as a Consultant for MTPA. Dr. Genge has received personal compensation in the range of $0-$499 for serving as a Consultant for WAVE. Dr. Genge has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for eikonizo. Dr. Genge has received personal compensation in the range of $0-$499 for serving on a Scientific Advisory or Data Safety Monitoring board for rapa.

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