1. A computer implemented method for automatically generating a medical decision for a patient having an associated electronic medical record, the method comprising: retrieving, with at least one computer processor, an electronic medical record data structure defining a patient condition, the patient condition associated with a context; retrieving, with the at least one computer processor, a voice input associated with the patient condition and a time stamp; generating, with the at least one computer processor executing a speech-to-text process, a text input data structure based on the voice input; tokenizing, with the at least one computer processor executing a natural language processing process, the text input to obtain a plurality of tokens including a first token and a second token; querying, with the at least one computer processor, a concept database for a first concept associated with the first token; querying, with the at least one computer processor, the concept database for a second concept associated with the second token; determining, with the at least one computer processor, that the first concept is associated with a time-based trigger based on the time stamp and the context; generating, with the at least one computer processor, a sequence comprising the first concept and the second concept; querying, with the at least one computer processor, a guideline database to obtain a guideline associated with the time-based trigger; generating, with the at least one computer processor, a determination that the sequence does not comply with the guideline; generating, with the at least one computer processor, a prompt describing a course of action for treating the patient based on the determination; and wherein the patient is treated according to the course of action.
1. A computer implemented method for automatically generating a medical decision for a patient having an associated electronic medical record, the method comprising: retrieving, with at least one computer processor, an electronic medical record data structure defining a patient condition, the patient condition associated with a context; retrieving, with the at least one computer processor, a voice input associated with the patient condition and a time stamp; generating, with the at least one computer processor executing a speech-to-text process, a text input data structure based on the voice input; tokenizing, with the at least one computer processor executing a natural language processing process, the text input to obtain a plurality of tokens including a first token and a second token; querying, with the at least one computer processor, a concept database for a first concept associated with the first token; querying, with the at least one computer processor, the concept database for a second concept associated with the second token; determining, with the at least one computer processor, that the first concept is associated with a time-based trigger based on the time stamp and the context; generating, with the at least one computer processor, a sequence comprising the first concept and the second concept; querying, with the at least one computer processor, a guideline database to obtain a guideline associated with the time-based trigger; generating, with the at least one computer processor, a determination that the sequence does not comply with the guideline; generating, with the at least one computer processor, a prompt describing a course of action for treating the patient based on the determination; and wherein the patient is treated according to the course of action. 2. The method according to claim 1 , further comprising receiving, with the at least one computer processor, a second voice input associated with a result of treating the patient according to the course of action; and generating, with the at least one computer processor, an update data element based on the second voice input; and updating, with the at least one computer processor, the electronic medical record with the update data element.