3. The system according to claim 1 the NLP engine tags each phrase with a primary tag based on a subject matter of the phrase.
1. A system for processing and actionizing patient experience data, the system comprising: a server comprising a natural language processing (NLP) engine; and a relational database; wherein a plurality of communications is received at the server, each of the plurality of communications comprises comment data collected from publicly available data of an Internet web site or from one or more surveys, wherein the comment data comprises structured or unstructured patient experience data; wherein the comment data from each of the plurality of communications is transformed to structured patient experience data and stored at the relational database in a response table that includes one or more records, wherein each record corresponds to the comment data from a communication, and wherein each record comprises the corresponding comment data and a timestamp; wherein the comment data from each of the plurality of communications is parsed for individual phrases to generate a plurality of phrases; wherein one or more phrases are selected from the plurality of phrases based on a predetermined parameter; wherein the NLP engine is to predict one or more annotations for the one or more phrases based upon a score, wherein to predict the one or more annotations for the one or more phrases based upon the score comprises to (i) predict one or more annotations for the one or more phrases based upon a machine learning score, wherein the one or more annotations comprise a sentiment, a theme, or any named entity of the one or more phrases, (ii) determine whether the machine learning score is less than a predetermined threshold score, and (iii) predict the one or more annotations for the one or more phrases based upon a reference score in response to a determination that the machine learning score is less than the predetermined threshold score; wherein the one or more annotations are stored at the relational database in an annotation table that includes one or more records in response to prediction of the one or more annotations, wherein each record corresponds to an annotation, and wherein each record includes the sentiment, the named entity, a primary tag indicative of a subject matter, or a secondary tag indicative of the theme; and wherein the server is to generate a dashboard web page for a user that includes the one or more annotations in response to prediction of the one or more annotations.