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Ronchieri E, Canaparo M. Assessing the impact of software quality models in healthcare software systems. Health Syst (Basingstoke) 2023; 12:85-97. [PMID: 36926376 PMCID: PMC10013535 DOI: 10.1080/20476965.2022.2162445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 12/20/2022] [Indexed: 01/11/2023] Open
Abstract
Health and medical care are safety-critical environments. The development of a safe and reliable healthcare software system is one of the most important processes which may affect the accuracy of clinical decision making and have an impact on determining diagnoses of and treatment for diseases. The aim of this study is to assess if software quality models, such as McCall, can have an impact on healthcare software quality for the purpose of reducing software failures. We have identified the main criticalities of healthcare software systems based on existing literature, software quality models and programming language standards; we have related these criticalities to software characteristics; we have analysed the relationship between the main criticalities of healthcare software systems and their software characteristics. The following criticalities - the risk of changing hard-coded software and the importance of developing maintainable software - must be addressed at the start of the software development process.
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Investigating the Impact of Outsourcing on IT Flexibility. INTERNATIONAL JOURNAL OF HEALTHCARE INFORMATION SYSTEMS AND INFORMATICS 2022. [DOI: 10.4018/ijhisi.299955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Modern healthcare organizations try to leverage their IT infrastructures to enhance the efficiency of processes and the quality of patient services. The flexibility of the IT infrastructure is a critical factor in the process of establishing strategic and operational value. The authors examine how applied principles of Conceptual Independence (CI) in information systems (IS) influence the flexibility of IT infrastructures. Furthermore, it is presumed that IT outsourcing plays a role in IT flexibility. The second question asks whether IT outsourcing configurations change when CI has been applied or not. Quantitative and qualitative data have been collected in 9 mental healthcare organizations. Findings – based on integration of the data with a mixed-method approach - suggest that the healthcare organizations that apply the principles of CI are better equipped to adapt their IT infrastructure to changing demands, requests and needs. Likewise, results suggest that they have changed the government of IT outsourcing thereby increasing IT flexibility even further.
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Kryszyn J, Cywoniuk K, Smolik WT, Wanta D, Wróblewski P, Midura M. Performance of an openEHR based hospital information system. Int J Med Inform 2022; 162:104757. [PMID: 35395475 DOI: 10.1016/j.ijmedinf.2022.104757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 01/28/2022] [Accepted: 03/27/2022] [Indexed: 11/21/2022]
Abstract
BACKGROUND A desirable feature of hospital information systems is interoperability, which is generally quite limited due to the lack of standardization of the data model. This results in high development and maintenance costs for such systems. The openEHR standard addresses this problem. Due to its two-level modelling, it allows the separation of demographic and medical data and the storage of this data so that it can be easily processed and exchanged. However, it introduces an additional software layer that may affect system performance. This article examines the performance of a system based on the openEHR standard and compares it with the performance of a proprietary system developed in a classic way. METHODS Two hospital information systems with the same functionality were designed and developed. One was based on an openEHR server, and another was using proprietary data model having both demographic and medical data. Systems were deployed on Azure platform and load tests using JMeter were conducted to calculate statistics of elapsed time of requests as well as throughput of both systems. RESULTS Endpoints which fetch only demographic data had the same performance, but when medical data had to be queried, a decrease in performance of the openEHR based system was noticed. The system based on a proprietary data had about 6 times bigger throughput in terms of medical data fetching. CONCLUSIONS OpenEHR adds another layer to the architecture of a hospital information system which might result in performance issues. Such a system must be designed to operate on a sufficiently strong architecture if it is intended to serve many users.
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Affiliation(s)
- Jacek Kryszyn
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland.
| | - Kamil Cywoniuk
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
| | - Waldemar T Smolik
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
| | - Damian Wanta
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
| | - Przemysław Wróblewski
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
| | - Mateusz Midura
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Radioelectronics and Multimedia Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
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Li M, Cai H, Nan S, Li J, Lu X, Duan H. A Patient-Screening Tool for Clinical Research Based on Electronic Health Records Using OpenEHR: Development Study. JMIR Med Inform 2021; 9:e33192. [PMID: 34673526 PMCID: PMC8569542 DOI: 10.2196/33192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 09/27/2021] [Accepted: 09/27/2021] [Indexed: 11/28/2022] Open
Abstract
Background The widespread adoption of electronic health records (EHRs) has facilitated the secondary use of EHR data for clinical research. However, screening eligible patients from EHRs is a challenging task. The concepts in eligibility criteria are not completely matched with EHRs, especially derived concepts. The lack of high-level expression of Structured Query Language (SQL) makes it difficult and time consuming to express them. The openEHR Expression Language (EL) as a domain-specific language based on clinical information models shows promise to represent complex eligibility criteria. Objective The study aims to develop a patient-screening tool based on EHRs for clinical research using openEHR to solve concept mismatch and improve query performance. Methods A patient-screening tool based on EHRs using openEHR was proposed. It uses the advantages of information models and EL in openEHR to provide high-level expressions and improve query performance. First, openEHR archetypes and templates were chosen to define concepts called simple concepts directly from EHRs. Second, openEHR EL was used to generate derived concepts by combining simple concepts and constraints. Third, a hierarchical index corresponding to archetypes in Elasticsearch (ES) was generated to improve query performance for subqueries and join queries related to the derived concepts. Finally, we realized a patient-screening tool for clinical research. Results In total, 500 sentences randomly selected from 4691 eligibility criteria in 389 clinical trials on stroke from the Chinese Clinical Trial Registry (ChiCTR) were evaluated. An openEHR-based clinical data repository (CDR) in a grade A tertiary hospital in China was considered as an experimental environment. Based on these, 589 medical concepts were found in the 500 sentences. Of them, 513 (87.1%) concepts could be represented, while the others could not be, because of a lack of information models and coarse-grained requirements. In addition, our case study on 6 queries demonstrated that our tool shows better query performance among 4 cases (66.67%). Conclusions We developed a patient-screening tool using openEHR. It not only helps solve concept mismatch but also improves query performance to reduce the burden on researchers. In addition, we demonstrated a promising solution for secondary use of EHR data using openEHR, which can be referenced by other researchers.
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Affiliation(s)
- Mengyang Li
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang, China
| | - Hailing Cai
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang, China
| | - Shan Nan
- Hainan University School of Biomedical Engineering, Haikou City, China
| | - Jialin Li
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang, China
| | - Xudong Lu
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang, China
| | - Huilong Duan
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering, Ministry of Education, Hangzhou, Zhejiang, China
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Carpitella S, Certa A, Izquierdo J, La Cascia M. Multi‐criteria decision‐making approach for modular enterprise resource planning sorting problems. JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2021. [DOI: 10.1002/mcda.1745] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Silvia Carpitella
- Department of Decision‐Making Theory, Institute of Information Theory and Automation Czech Academy of Sciences Prague Czech Republic
| | - Antonella Certa
- Department of Engineering University of Palermo Palermo Italy
| | - Joaquín Izquierdo
- Instituto de Matemática Multidisciplinar Universitat Politècnica de València Valencia Spain
| | - Marco La Cascia
- Department of Engineering University of Palermo Palermo Italy
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Tarenskeen D, van de Wetering R, Bakker R, Brinkkemper S. The Contribution of Conceptual Independence to IT Infrastructure Flexibility: The Case of openEHR. HEALTH POLICY AND TECHNOLOGY 2020. [DOI: 10.1016/j.hlpt.2020.04.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Felipe GF, Lima FET, Barbosa LP, Moreira TMM, Joventino ES, Freire VS, Mendonça LBDA. Evaluation of user embracement software with pediatric risk classification. Rev Bras Enferm 2020; 73:e20180677. [DOI: 10.1590/0034-7167-2018-0677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 05/17/2019] [Indexed: 11/22/2022] Open
Abstract
ABSTRACT 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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Min L, Tian Q, Lu X, Duan H. Modeling EHR with the openEHR approach: an exploratory study in China. BMC Med Inform Decis Mak 2018; 18:75. [PMID: 30157838 PMCID: PMC6116359 DOI: 10.1186/s12911-018-0650-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2017] [Accepted: 07/04/2018] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The openEHR approach can improve the interoperability of electronic health record (EHR) through two-level modeling. Developing archetypes for the complete EHR dataset is essential for implementing a large-scale interoperable EHR system with the openEHR approach. Although the openEHR approach has been applied in different domains, the feasibility of archetyping a complete EHR dataset in a hospital has not been reported in academic literature, especially in a country where using openEHR is still in its infancy stage, like China. This paper presents a case study of modeling an EHR in China aiming to investigate the feasibility and challenges of archetyping a complete EHR dataset with the openEHR approach. METHODS We proposed an archetype modeling method including an iterative process of collecting requirements, normalizing data elements, organizing concepts, searching corresponding archetypes, editing archetypes and reviewing archetypes. Two representative EHR systems from Chinese vendors and the existing Chinese EHR standards have been used as resources to identify the requirements of EHR in China, and a case study of modeling EHR in China has been conducted. Based on the models developed in this case study, we have implemented a clinical data repository (CDR) to verify the feasibility of modeling EHR with archetypes. RESULTS Sixty four archetypes were developed to represent all requirements of a complete EHR dataset. 59 (91%) archetypes could be found in Clinical Knowledge Manager (CKM), of which 35 could be reused directly without change, and 23 required further development including two revisions, two new versions, 18 extensions and one specialization. Meanwhile, 6 (9%) archetypes were newly developed. The legacy data of the EHR system in hospitals could be integrated into the CDR developed with these archetypes successfully. CONCLUSIONS The existing archetypes in CKM can faithfully represent most of the EHR requirements in China except customizations for local hospital management. This case study verified the feasibility of modeling EHR with the openEHR approach and identified the fact that the challenges such as localization, tool support, and an agile publishing process still exist for a broader application of the openEHR approach.
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Affiliation(s)
- Lingtong Min
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Zheda Road, Hangzhou, 310027, China
| | - Qi Tian
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Zheda Road, Hangzhou, 310027, China
| | - Xudong Lu
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Zheda Road, Hangzhou, 310027, China.
| | - Huilong Duan
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Zheda Road, Hangzhou, 310027, China
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Li B, Li J, Lan X, An Y, Gao W, Jiang Y. Experiences of building a medical data acquisition system based on two-level modeling. Int J Med Inform 2018; 112:114-122. [DOI: 10.1016/j.ijmedinf.2018.01.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 01/19/2018] [Accepted: 01/20/2018] [Indexed: 01/08/2023]
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Teodoro D, Sundvall E, João Junior M, Ruch P, Miranda Freire S. ORBDA: An openEHR benchmark dataset for performance assessment of electronic health record servers. PLoS One 2018; 13:e0190028. [PMID: 29293556 PMCID: PMC5749730 DOI: 10.1371/journal.pone.0190028] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 12/06/2017] [Indexed: 11/19/2022] Open
Abstract
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.
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Affiliation(s)
- Douglas Teodoro
- Departamento de Tecnologia da Informação e Educação em Saúde, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
- SIB Text Mining, Swiss Institute of Bioinformatics, Geneva, Switzerland
- Department of Information Science, HEG-Geneva, HES-SO, Geneva, Switzerland
| | - Erik Sundvall
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
- Region Östergötland, Linköping, Sweden
| | - Mario João Junior
- Departamento de Tecnologia da Informação e Educação em Saúde, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Patrick Ruch
- SIB Text Mining, Swiss Institute of Bioinformatics, Geneva, Switzerland
- Department of Information Science, HEG-Geneva, HES-SO, Geneva, Switzerland
| | - Sergio Miranda Freire
- Departamento de Tecnologia da Informação e Educação em Saúde, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
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Anani N, Mazya MV, Chen R, Prazeres Moreira T, Bill O, Ahmed N, Wahlgren N, Koch S. Applying openEHR's Guideline Definition Language to the SITS international stroke treatment registry: a European retrospective observational study. BMC Med Inform Decis Mak 2017; 17:7. [PMID: 28073358 PMCID: PMC5223429 DOI: 10.1186/s12911-016-0401-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Accepted: 12/15/2016] [Indexed: 11/10/2022] Open
Abstract
Background Interoperability standards intend to standardise health information, clinical practice guidelines intend to standardise care procedures, and patient data registries are vital for monitoring quality of care and for clinical research. This study combines all three: it uses interoperability specifications to model guideline knowledge and applies the result to registry data. Methods We applied the openEHR Guideline Definition Language (GDL) to data from 18,400 European patients in the Safe Implementation of Treatments in Stroke (SITS) registry to retrospectively check their compliance with European recommendations for acute stroke treatment. Results Comparing compliance rates obtained with GDL to those obtained by conventional statistical data analysis yielded a complete match, suggesting that GDL technology is reliable for guideline compliance checking. Conclusions The successful application of a standard guideline formalism to a large patient registry dataset is an important step toward widespread implementation of computer-interpretable guidelines in clinical practice and registry-based research. Application of the methodology gave important results on the evolution of stroke care in Europe, important both for quality of care monitoring and clinical research. Electronic supplementary material The online version of this article (doi:10.1186/s12911-016-0401-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Nadim Anani
- Health Informatics Centre, LIME, Karolinska Institutet, Tomtebodavägen 18, Stockholm, SE 17177, Sweden.
| | - Michael V Mazya
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Rong Chen
- Health Informatics Centre, LIME, Karolinska Institutet, Tomtebodavägen 18, Stockholm, SE 17177, Sweden.,Cambio Healthcare Systems, Stockholm, Sweden
| | - Tiago Prazeres Moreira
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Olivier Bill
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Niaz Ahmed
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Nils Wahlgren
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Sabine Koch
- Health Informatics Centre, LIME, Karolinska Institutet, Tomtebodavägen 18, Stockholm, SE 17177, Sweden
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Demski H, Garde S, Hildebrand C. Open data models for smart health interconnected applications: the example of openEHR. BMC Med Inform Decis Mak 2016; 16:137. [PMID: 27770769 PMCID: PMC5075152 DOI: 10.1186/s12911-016-0376-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Accepted: 10/18/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Smart 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. METHODS This 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. RESULTS A 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. CONCLUSION Open 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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Affiliation(s)
- Hans Demski
- Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
| | - Sebastian Garde
- Ocean Informatics, 124 Cromwell Road, Kensington, London, SW7 4ET, United Kingdom
| | - Claudia Hildebrand
- Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
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Comparing the Performance of NoSQL Approaches for Managing Archetype-Based Electronic Health Record Data. PLoS One 2016; 11:e0150069. [PMID: 26958859 PMCID: PMC4784924 DOI: 10.1371/journal.pone.0150069] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 02/07/2016] [Indexed: 11/19/2022] Open
Abstract
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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Eguzkiza A, Trigo JD, Martínez-Espronceda M, Serrano L, Andonegui J. Formalize clinical processes into electronic health information systems: Modelling a screening service for diabetic retinopathy. J Biomed Inform 2015; 56:112-26. [DOI: 10.1016/j.jbi.2015.05.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 05/22/2015] [Accepted: 05/26/2015] [Indexed: 10/23/2022]
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Pahl C, Zare M, Nilashi M, de Faria Borges MA, Weingaertner D, Detschew V, Supriyanto E, Ibrahim O. Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics. J Biomed Inform 2015; 55:174-87. [PMID: 25900270 DOI: 10.1016/j.jbi.2015.04.004] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Revised: 03/19/2015] [Accepted: 04/10/2015] [Indexed: 10/23/2022]
Abstract
This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works.
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Affiliation(s)
- Christina Pahl
- Department of Biomechatronics, Ilmenau University of Technology, Ilmenau, Thuringia, Germany; IJN-UTM Cardiovascular Engineering Centre, University of Technology Malaysia, Skudai, Johor, Malaysia.
| | - Mojtaba Zare
- Faculty of Computing, Universiti Technologi Malaysia, Johor, Malaysia
| | | | | | - Daniel Weingaertner
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Vesselin Detschew
- Institute of Biomedical Engineering and Informatics, Department of Biomedical Engineering, Ilmenau, Thuringia, Germany
| | - Eko Supriyanto
- IJN-UTM Cardiovascular Engineering Centre, University of Technology Malaysia, Skudai, Johor, Malaysia
| | - Othman Ibrahim
- Faculty of Computing, Universiti Technologi Malaysia, Johor, Malaysia
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