Evaluation of software maintainability with openEHR – a comparison of architectures

Atalag, Koray; Yang, Hong Yul; Tempero, Ewan; Warren, James R.

doi:10.1016/j.ijmedinf.2014.07.006

Cited by 22 publications

(10 citation statements)

References 11 publications

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“…The openEHR specifications aim at accommodating new requirements primarily at the AM (archetype and template) level without the need to change the RM and its associated storage mechanism, thus requiring fewer changes in the application code and persistence mechanism [ 9 ]. This approach also promotes semantic interoperability between systems based on the shared RM, configured using (partly) shared archetypes and templates, but the interoperability aspect is not the focus of this paper.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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This study provides an experimental performance evaluation on population-based queries of NoSQL databases storing archetype-based Electronic Health Record (EHR) data. There are few published studies regarding the performance of persistence mechanisms for systems that use multilevel modelling approaches, especially when the focus is on population-based queries. A healthcare dataset with 4.2 million records stored in a relational database (MySQL) was used to generate XML and JSON documents based on the openEHR reference model. Six datasets with different sizes were created from these documents and imported into three single machine XML databases (BaseX, eXistdb and Berkeley DB XML) and into a distributed NoSQL database system based on the MapReduce approach, Couchbase, deployed in different cluster configurations of 1, 2, 4, 8 and 12 machines. Population-based queries were submitted to those databases and to the original relational database. Database size and query response times are presented. The XML databases were considerably slower and required much more space than Couchbase. Overall, Couchbase had better response times than MySQL, especially for larger datasets. However, Couchbase requires indexing for each differently formulated query and the indexing time increases with the size of the datasets. The performances of the clusters with 2, 4, 8 and 12 nodes were not better than the single node cluster in relation to the query response time, but the indexing time was reduced proportionally to the number of nodes. The tested XML databases had acceptable performance for openEHR-based data in some querying use cases and small datasets, but were generally much slower than Couchbase. Couchbase also outperformed the response times of the relational database, but required more disk space and had a much longer indexing time. Systems like Couchbase are thus interesting research targets for scalable storage and querying of archetype-based EHR data when population-based use cases are of interest.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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“…Academic application frameworks explore the potential of ODMs within EHR systems. GastrOS [35], for example, developed an openEHR based endoscopic reporting application that is capable of dynamically generating the graphical user interfaces (GUI) from underlying domain knowledge models. EHRServer [36] provides a Service-oriented, REST based, openEHR repository for clinical data.…”

Section: Resultsmentioning

confidence: 99%

Open data models for smart health interconnected applications: the example of openEHR

Demski

Garde²,

Hildebrand

2016

BMC Med Inform Decis Mak

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BackgroundSmart Health is known as a concept that enhances networking, intelligent data processing and combining patient data with other parameters. Open data models can play an important role in creating a framework for providing interoperable data services that support the development of innovative Smart Health applications profiting from data fusion and sharing.MethodsThis article describes a model-driven engineering approach based on standardized clinical information models and explores its application for the development of interoperable electronic health record systems. The following possible model-driven procedures were considered: provision of data schemes for data exchange, automated generation of artefacts for application development and native platforms that directly execute the models. The applicability of the approach in practice was examined using the openEHR framework as an example.ResultsA comprehensive infrastructure for model-driven engineering of electronic health records is presented using the example of the openEHR framework. It is shown that data schema definitions to be used in common practice software development processes can be derived from domain models. The capabilities for automatic creation of implementation artefacts (e.g., data entry forms) are demonstrated. Complementary programming libraries and frameworks that foster the use of open data models are introduced. Several compatible health data platforms are listed. They provide standard based interfaces for interconnecting with further applications.ConclusionOpen data models help build a framework for interoperable data services that support the development of innovative Smart Health applications. Related tools for model-driven application development foster semantic interoperability and interconnected innovative applications.

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“…Whether or not the maintainability of a software can be reflected in the costs and efforts required to accomplish this task. The way the software is developed, including the type of architecture and language used, can improve its maintainability (25) .…”

Section: Discussionmentioning

confidence: 99%

Evaluation of user embracement software with pediatric risk classification

et al. 2020

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Objective: to evaluate functional performance and technical quality of user embracement software with pediatric risk classification. Method: descriptive exploratory study developed based on the quality requirements set forth in ISO/IEC 25010. The evaluated characteristics were: functional adequacy, reliability, usability, performance efficiency, compatibility, safety, maintainability and portability. Eight specialists from the area of informatics and 13 from nursing participated in the evaluation. The characteristics were considered adequate when they reached more than 70% of indication as very and/or completely appropriate in the evaluations of each group of specialists. Results: The results obtained from the evaluation of informatics and nursing specialists were: functional adequacy (100.0%, 96.2%), reliability (82.6%, 88.5%), usability (84.9%; 98.7%), performance efficiency (93.4%; 96.2%), compatibility (85.0%, 98.1%), safety (91.7%, 100.0%), and, yet, maintainability (95.0%) and portability (87.5%) evaluated by the first ones. Conclusion: the software was considered adequate regarding technical quality and functional performance.

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Evaluation of software maintainability with openEHR – a comparison of architectures

Cited by 22 publications

References 11 publications

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

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

Open data models for smart health interconnected applications: the example of openEHR

Evaluation of user embracement software with pediatric risk classification

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