Erik Sundvall

Integration of Tools for Binding Archetypes to SNOMED CT

BackgroundThe Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.MethodsLexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.ResultsAn integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.ConclusionFinding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system

BackgroundExchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format.MethodsThe openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates.ResultsAutomated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats.ConclusionThe openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

Requirements and prototyping of a home health care application based on emerging java technology

IT support for home health care is an expanding area within health care IT development. Home health care differs from other in- or outpatient care delivery forms in a number of ways, and thus, the introduction of home health care applications must be based on a rigorous analysis of necessary requirements to secure safe and reliable health care. This article reports early experiences from the development of a home health care application based on emerging JAVA technologies. A prototype application for the follow-up of diabetes patients is presented and discussed in relation to a list of general requirements on home health care applications.

Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

BackgroundThe openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored.ResultsThe main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping.ConclusionsUsing REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

Survey of openEHR storage implementations

Efficiently storing and retrieving archetype-based patient information can be a challenging task. This paper surveys current archetype-based system implementations in the world and in particular the different approaches that have been used to create 13606- or openEHR-based storage repositories. Data is reported from systems with a few records to millions of records, including both deployed systems in production and experimental systems. Worldwide 21 projects were found, 4 did not reply and 1 did not provide data. Many systems (n=11) base their storage on RDBMS, then often (n=6) with some XML data fields. Dedicated XML (n=3) and object-oriented (n=2) databases were other examples of storage used. Query formalisms used include SQL, AQL, XQuery and XPath. Service interfaces via SOAP (n=12) or REST (n=6) are common. Most systems support dynamic configuration using new/changed archetypes and templates dynamically without system restart. Some (n=7) systems use demographic archetypes. In addition to the built in DBMS indexing mechanisms, one project reports use of an additional inverted index to achieve improved performance.

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

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.

Methods and applications for visualization of SNOMED CT concept sets

Inconsistent use of SNOMED CT concepts may reduce comparability of information in health information systems. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT and also assess potential applications for such visualizations. The open source prototype presented is an interactive web-based re-implementation of the terminology visualization tool TermViz that provides an overview of concepts and their hierarchical relations. It provides terminological features such as interactively rearranging graphs, fetching more concept nodes, highlighting least common parents and shared pathways in merged graphs etc. Four teams of three to four people used the prototype to complete a terminology mapping task and then, in focus group interviews, discussed the user experience and potential future tool usage. Potential purposes discussed included SNOMED CT search and training, consistent selection of concepts and content management. The evaluation indicated that the tool may be useful in many contexts especially if integrated with existing systems, and that the graph layout needs further tuning and development.

Visualizing sets of SNOMED CT concepts to support consistent terminology implementation and reuse of clinical data

Inconsistent use of concepts is an obstacle when implementing SNOMED CT to improve comparability of information. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT in EHR-system implementation processes. The prototype presented is an interactive web-based re-implementation of the terminology visualization tool TermViz. The open source prototype contains terminological features that are of relevance when exploring and comparing sets of concepts in SNOMED CT. Future work should focus on evaluating the developed prototype in order to assess its applicability in EHR-system-implementation contexts.

ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.