Precision clinical decision support with data driven approach on multiple medical knowledge modules

A non-transitory storage medium storing:

• a database storing clinical decision rules, each clinical decision rule comprising a set of preconditions and being executable to generate a predicted value of a clinical conclusion that is dependent on values of the set of preconditions of the clinical decision rule;
• and
• instructions readable and executable by a computer to perform an electronic clinical decision support (CDS) method including:
• obtaining values of the preconditions of the clinical decision rules for a current patient;
• executing the clinical decision rules to generate predicted values of clinical conclusions for the current patient based on the obtained values for the current patient of preconditions of the clinical decision rules;
• retrieving, from an Electronic Medical Record (EMR), values of the preconditions of the clinical decision rules for past patients and values of the clinical conclusions of the clinical decision rules for the past patients;
• for each past patient, executing the clinical decision rules using the values of the preconditions retrieved from the EMIR for the past patient to generate predicted values of the clinical conclusions for the past patients;
• and
• generating rule summary scores for the clinical decision rules based on comparisons of the retrieved values of the clinical conclusions for the past patients with the predicted values of the clinical conclusions for the past patients to prioritize the clinical decision rules or the predicted values generated by the clinical conclusion for the current patient.

An electronic clinical decision support (CDS) method comprising:

• obtaining values of the preconditions of the clinical decision rules for a current patient, each clinical decision rule comprising a set of preconditions and being executable to generate a predicted value of a clinical conclusion that is dependent on values of the set of preconditions of the clinical decision rule;
• executing clinical decision rules using a computer to generate predicted values of clinical conclusions for the current patient based on the obtained values for the current patient of preconditions of the clinical decision rules;
• executing the clinical decision rules using the computer to generate predicted values of the clinical conclusions for past patients based on values for the past patients of the preconditions of the clinical decision rules retrieved from an Electronic Medical Record (EMR) hosted by or connected with the computer and;
• generating rule summary scores for the clinical decision rules using the computer based on comparisons of values of the clinical conclusions for the past patients retrieved from the EMR with the predicted values of the clinical conclusions for the past patients to prioritize the clinical decision rules or the predicted values generated by the clinical conclusion for the current patient.