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Enabling flexible integration of healthcare information using the entity-attribute-value storage model.

Löper D, Klettke M, Bruder I, Heuer A - Health Inf Sci Syst (2013)

Bottom Line: Therefore, a digital patient care record is introduced to establish the foundation for integrating healthcare-related information.The time for traversing the results strongly depends on the number of documents.The underlying database structure is presented, the import process for extracting incoming reports is described and the export process for generating new outgoing standardized reports is briefly illustrated.

View Article: PubMed Central - PubMed

Affiliation: Database Research Group, University of Rostock, 18051 Rostock, Germany.

ABSTRACT

Background: For an optimal care of patients in home healthcare, it is essential to exchange healthcare-related information with other stakeholders. Unfortunately, paper-based documentation procedures as well as the heterogeneity between information systems inhibit a well-regulated communication. Therefore, a digital patient care record is introduced to establish the foundation for integrating healthcare-related information.

Methods: For the digital patient care record, suitable integration techniques are required that store data in a compact way and offer flexibility as well as robustness. For this purpose, a generic storage structure based on the entity-attribute-value (EAV) model is introduced. This storage structure fulfills the stated requirements and incoming information can be stored directly without any loss of data.

Evaluation results and discussions: First performance tests regarding the query response time are given in this paper. The tests measured the connection time, the query execution time, and the time for traversing the result set. The time for executing the query is lowest. The time for traversing the results strongly depends on the number of documents. A concept comparison to other integration techniques is also presented.

Conclusions: This approach offers flexibility concerning different standard types and the evolution in healthcare knowledge and processes. It also allows for highly sparse data to be stored in a compact way. The underlying database structure is presented, the import process for extracting incoming reports is described and the export process for generating new outgoing standardized reports is briefly illustrated.

No MeSH data available.


Basic Class Model of the EAV Storage Structure. The basic class model of the EAV storage structure extends the main EAV model by introducing separate value relations for each data type. As most of the documents to be included are XML-based, an entity’s parent and the position among its siblings are stored in the entity relation as well. The database also stores some general information about each document, e.g. information about the author.
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Fig3: Basic Class Model of the EAV Storage Structure. The basic class model of the EAV storage structure extends the main EAV model by introducing separate value relations for each data type. As most of the documents to be included are XML-based, an entity’s parent and the position among its siblings are stored in the entity relation as well. The database also stores some general information about each document, e.g. information about the author.

Mentions: We developed a storage structure based on the extended EAV model. Figure 3 represents the basic schema of our database storage structure. All data types that are enumerated in the ISO standard 21090 [18] can be stored in the model. For reflecting hierarchical structures (e.g. derived from XML documents), an attribute Parent was added in the entity relation. Moreover, an attribute Sibling_Pos refers to the position of an entity among its siblings.Figure 3


Enabling flexible integration of healthcare information using the entity-attribute-value storage model.

Löper D, Klettke M, Bruder I, Heuer A - Health Inf Sci Syst (2013)

Basic Class Model of the EAV Storage Structure. The basic class model of the EAV storage structure extends the main EAV model by introducing separate value relations for each data type. As most of the documents to be included are XML-based, an entity’s parent and the position among its siblings are stored in the entity relation as well. The database also stores some general information about each document, e.g. information about the author.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4340778&req=5

Fig3: Basic Class Model of the EAV Storage Structure. The basic class model of the EAV storage structure extends the main EAV model by introducing separate value relations for each data type. As most of the documents to be included are XML-based, an entity’s parent and the position among its siblings are stored in the entity relation as well. The database also stores some general information about each document, e.g. information about the author.
Mentions: We developed a storage structure based on the extended EAV model. Figure 3 represents the basic schema of our database storage structure. All data types that are enumerated in the ISO standard 21090 [18] can be stored in the model. For reflecting hierarchical structures (e.g. derived from XML documents), an attribute Parent was added in the entity relation. Moreover, an attribute Sibling_Pos refers to the position of an entity among its siblings.Figure 3

Bottom Line: Therefore, a digital patient care record is introduced to establish the foundation for integrating healthcare-related information.The time for traversing the results strongly depends on the number of documents.The underlying database structure is presented, the import process for extracting incoming reports is described and the export process for generating new outgoing standardized reports is briefly illustrated.

View Article: PubMed Central - PubMed

Affiliation: Database Research Group, University of Rostock, 18051 Rostock, Germany.

ABSTRACT

Background: For an optimal care of patients in home healthcare, it is essential to exchange healthcare-related information with other stakeholders. Unfortunately, paper-based documentation procedures as well as the heterogeneity between information systems inhibit a well-regulated communication. Therefore, a digital patient care record is introduced to establish the foundation for integrating healthcare-related information.

Methods: For the digital patient care record, suitable integration techniques are required that store data in a compact way and offer flexibility as well as robustness. For this purpose, a generic storage structure based on the entity-attribute-value (EAV) model is introduced. This storage structure fulfills the stated requirements and incoming information can be stored directly without any loss of data.

Evaluation results and discussions: First performance tests regarding the query response time are given in this paper. The tests measured the connection time, the query execution time, and the time for traversing the result set. The time for executing the query is lowest. The time for traversing the results strongly depends on the number of documents. A concept comparison to other integration techniques is also presented.

Conclusions: This approach offers flexibility concerning different standard types and the evolution in healthcare knowledge and processes. It also allows for highly sparse data to be stored in a compact way. The underlying database structure is presented, the import process for extracting incoming reports is described and the export process for generating new outgoing standardized reports is briefly illustrated.

No MeSH data available.