4 Keys to Health Content Analytics
By Marc Edwards, B.Sc. , PMP, Content Analyticss, bpms, MBA
The four key steps in the health content analytics process.
When dealing with novel and/or difficult concepts, I find that it’s always easier to understand them when they are broken down into simpler methods or steps. Therefore, when describing health content analytics to the neophyte, which you yourself may be, I thought it best to break that concept down into the following four steps:
Identify key sources of information required to produce the required analytic results. The ability to simply connect to most sources and types of unstructured content will simplify the process and enable a focus on the analysis of the information.
Documents are processed using text analytics and natural language processing capabilities, which provides a basic understanding of the meaning and context in the document. Clusters of information are identified to further enhance the understanding of key concepts.
Information is explored to begin to reveal key insights in the unstructured information. Statistical correlation and temporal relationships are revealed through a mining environment that enables analysts to navigate around the information by facets and concepts.
Extend the natural language processing model to create a deeper analysis of the information. A modelling environment is used to create rules for deeper analysis of the correlation using the collection of documents itself.
Following these four basic steps should help you establish your process for health content analytics. So what do you think? Do you find this information helpful?