Traditionally, binary data will be stored in RDBMS as BLOB. Using a hybrid approach of traditional RDBMS and “document-oriented” databases seems to be a good choice. The other alternative is something like DB2 purexml.
The final answer may be “it depends”, but I really just want to get some general feedback/ideas.
Does anyone use the NoSql method for medical records?
**Clarification of the question**
To clarify: Someone uses nosql database in a production environment, such as: mongoDB, Cassandra, CouchDB medical records?
I know that some MUMPS implementations (I am considering Intersystems Caché) allow you to query the database using SQL, but this requires some in-depth technical knowledge to map non-relational data models to relational tables.
I work for a large EMR supplier that uses MUMPS, and I can tell you this is not an “interesting” experience. So I mean there is no good tool that allows me to whip up awesome features in a few lines of code (no LINQ-To-M in .NET). But I realize that I pay the price to write more code to query the data is worth market analysis.
If you are developing an EMR business and designing your architecture, you need to consider your ultimate goal. If you want to create a complete EMR that spans multiple fields and specializations, you will need a lot of features, while focusing on performance, reliability, and scalability. You also need thousands of developers to get your product to market as quickly as possible, because hospitals are now buying through new healthcare stimulus measures.
If you are considering a special application, your user community will be miniaturized and focused. You can choose any database technology, learn more about tools and develop quickly.
Electronic medical records are composed of different types of data. The access information (date/location/insurance information) seems to be applicable to the RDMS. Other types of medical information, such as laboratory reports, X-ray photographs, photographs, and electronic signatures, are all document-based and seem to be good candidates for “document-oriented” databases such as MongoDB.
Traditionally, binary data will be stored in RDBMS as BLOB. Using a hybrid approach of traditional RDBMS and “document-oriented” databases seems to be a good choice. The other alternative is something like DB2 purexml.
The final answer may be “it depends”, but I really just want to get some general feedback/ideas.
Does anyone use the NoSql method for medical records?
**Clarification of the question**
To clarify: Someone uses nosql database in a production environment, such as: mongoDB, Cassandra, CouchDB medical records?
Some large healthcare software vendors use some versions of MUMPS, which is definitely a non-SQL database. Epic, Meditech, GE and VA’s VistA all use some implementations of MUMPS. MUMPS is suitable for healthcare solutions, partly because of its performance and scalability.
I know that some MUMPS implementations (I am considering Intersystems Caché) allow you to query the database using SQL, but this requires some in-depth technical knowledge to map non-relational data models to relational tables.
I work for a large EMR supplier that uses MUMPS, and I can tell you this is not an “interesting” experience. So I mean there is no good tool that allows me to whip up awesome features in a few lines of code (no LINQ-To-M in .NET). But I realize that I pay the price to write more code to query the data is worth market analysis.
If you are developing an EMR business and designing your architecture, you need to consider your ultimate goal. If you want to create a complete EMR that spans multiple fields and specializations, you will need a lot of features, while focusing on performance, reliability, and scalability. You also need thousands of developers to get your product to market as quickly as possible, because hospitals are now buying through new healthcare stimulus measures.
If you are considering a special application, your user community will be miniaturized and focused. You can choose any database technology, learn more about tools and develop quickly.