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Comparing the Performance of NoSQL Approaches for Managing Archetype-Based Electronic Health Record Data.

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Summary
This summary is machine-generated.

Couchbase offers better performance for population-based queries on Electronic Health Record (EHR) data compared to XML and relational databases. While XML databases were slower and used more space, Couchbase demonstrated faster response times, especially for large datasets.

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Area of Science:

  • Health Informatics
  • Database Systems
  • Health Data Management

Background:

  • Limited research exists on the performance of persistence mechanisms for multilevel modeling in Electronic Health Record (EHR) systems, particularly for population-based queries.
  • Archetype-based data modeling is increasingly used in EHR systems, necessitating efficient data storage and retrieval strategies.

Purpose of the Study:

  • To experimentally evaluate the performance of NoSQL databases for population-based queries on archetype-based EHR data.
  • To compare the performance of Couchbase (a NoSQL system) against traditional relational databases (MySQL) and XML databases (BaseX, eXistdb, Berkeley DB XML).

Main Methods:

  • Generated XML and JSON documents from a 4.2 million record healthcare dataset using the openEHR reference model.
  • Imported data into three single-machine XML databases and a distributed Couchbase cluster (1-12 nodes).
  • Submitted population-based queries to all tested databases and measured response times and storage space.

Main Results:

  • Couchbase significantly outperformed XML databases in both query response time and storage space efficiency.
  • Couchbase generally offered better response times than MySQL for larger datasets, though it required more disk space and had longer indexing times.
  • Distributed Couchbase clusters (2-12 nodes) did not improve query response times over single-node clusters but reduced indexing time proportionally.

Conclusions:

  • Couchbase presents a promising research direction for scalable storage and querying of archetype-based EHR data, especially for population-based use cases.
  • XML databases may be suitable for smaller datasets or specific querying scenarios but are generally less performant than Couchbase.
  • While Couchbase excels in query speed, its indexing requirements and disk space usage need consideration for practical EHR implementations.