The use of MNd-5 algorithm screens electronic medical records has bee shown to be capable of assisting physicians in identifying individuals for which follow-up investigations for ALS may be appropriate.
This is a programme designed to analyse de-identified electronic medical records (EMRs) and identify individuals for which follow-up investigations for Amyotrophic Lateral Sclerosis (ALS), or referral to a specialty centre may be clinically appropriate.
Termed ‘Process for Progress in ALS: An EMR-based practice enhancement initiative’, the tool utilises a clinical algorithm, MNd-5, and is intended to support healthcare professionals (HCPs) in making timely decisions regarding follow-up testing or referral to a specialist.
Detecting in time is important, since early diagnosis and treatment of ALS can improve outcomes, but the disease can be difficult to diagnose in its early stages. The more time that passes before diagnosis, the less opportunities exist for disease-management for someone living with ALS.
Dr. Angela Genge, Executive Director, ALS Centre of Excellence at The Neuro in Montreal, states: “Process for Progress in ALS is a unique advancement in AI medical technology which can help healthcare professionals identify patients who present multiple warning signs for ALS so that they can receive expedited follow-ups, diagnoses, and treatment if needed.”
ALS is a neurodegenerative disease that currently has no cure and can progress rapidly. The disease is challenging to diagnose because symptoms of the condition can be subtle at first and no test can provide a definitive diagnosis. In Canada, it takes an average of 21 months to receive a diagnosis of ALS.2,3 The majority of people with ALS die within three years from symptom onset.
It is hoped, based on the research, that intervening in patients’ journeys earlier in the course of their disease can provide access to multidisciplinary care, approved therapies or clinical trials that can slow the progression of the disease and enhance the quality of their lives.
The MNd-5 algorithm acts as a clinical decision support tool to aid community neurologists in identifying individuals in which follow-up investigations for ALS. The technological approach prioritizes patients for clinical review by comparing their presenting characteristics and EMG findings to a reference population of patients diagnosed with ALS.
The algorithm can be applied to electronic health records at the Toronto Data Lab of Ensho Health as a service. The service is available to approximately 80 percent of community neurologists through integrations with the Epic, Cerner, Accuro, OscarPro, Indivicare, Mediquest and other electronic medical record systems.
