Predicting Glycogen Storage Diseases (Pompe Disease) And Decision Support

A computerized method of initiating an electronic health record (EHR) intervention action for glycogen storage disease, the method comprising:

• determining a multi-variable biomarker based on a set of physiological variables associated with an individual that is received as input data;
• utilizing a trained multi-variable logistic regression statistical model, determining a probability of a clinically significant glycogen storage disease for the individual based on the multi-variable biomarker;
• and
• based on the probability of the clinically significant glycogen storage disease for the individual, automatically modifying treatment of the patient, ordering additional diagnostics for the patient, scheduling treatment or diagnostics for the patient, and issuing a notification to a caregiver associated with the patient.