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Soares A, Jenders RA, Harrison R, Schilling LM. A Comparison of Arden Syntax and Clinical Quality Language as Knowledge Representation Formalisms for Clinical Decision Support. Appl Clin Inform 2021; 12:495-506. [PMID: 34192772 PMCID: PMC8245210 DOI: 10.1055/s-0041-1731001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Objectives
This article presents a comparative study of two Health Level Seven International (HL7) standards for clinical knowledge representation, the Arden Syntax and the Clinical Quality Language (CQL), regarding their expressiveness and utility to represent knowledge for clinical decision support (CDS) systems.
Methods
We compiled a concatenated set of features from both languages and made descriptive comparisons of 27 categories covering areas of language characteristics, data, control statements, and operators.
Results
Both Arden and CQL have similar constructs that can be used for representing CDS knowledge but also have unique constructs that could support distinct use cases. They have constructs that fully or partially address several of the categories used in the comparison, except for data models and terminologies in Arden and event triggering and iteration statements in CQL.
Conclusion
These standards can facilitate the sharing, management, and reuse of computable knowledge, and permit knowledge to be represented with their languages and converted to a machine-friendly executable code that can be shared and reused by other systems. Having support for standard data models and terminologies will continue to be a differential for adoption of a language. The HL7 working groups responsible for developing these standards can direct future development to enhance the functions of the standard and address the gaps identified in this study.
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Affiliation(s)
- Andrey Soares
- Department of Medicine, University of Colorado, Aurora, Colorado, United States
| | - Robert A Jenders
- Department of Medicine, University of California, Los Angeles, California, United States
| | - Robert Harrison
- University of Colorado Health (UCHealth), Aurora, Colorado, United States
| | - Lisa M Schilling
- Department of Medicine, University of Colorado, Aurora, Colorado, United States
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Strasberg HR, Rhodes B, Del Fiol G, Jenders RA, Haug PJ, Kawamoto K. Contemporary clinical decision support standards using Health Level Seven International Fast Healthcare Interoperability Resources. J Am Med Inform Assoc 2021; 28:1796-1806. [PMID: 34100949 DOI: 10.1093/jamia/ocab070] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/08/2021] [Accepted: 04/05/2021] [Indexed: 01/07/2023] Open
Abstract
OBJECTIVE To facilitate the development of standards-based clinical decision support (CDS) systems, we review the current set of CDS standards that are based on Health Level Seven International Fast Healthcare Interoperability Resources (FHIR). Widespread adoption of these standards may help reduce healthcare variability, improve healthcare quality, and improve patient safety. TARGET AUDIENCE This tutorial is designed for the broad informatics community, some of whom may be unfamiliar with the current, FHIR-based CDS standards. SCOPE This tutorial covers the following standards: Arden Syntax (using FHIR as the data model), Clinical Quality Language, FHIR Clinical Reasoning, SMART on FHIR, and CDS Hooks. Detailed descriptions and selected examples are provided.
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Affiliation(s)
- Howard R Strasberg
- Clinical Effectiveness, Wolters Kluwer Health, San Diego, California, USA
| | | | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
| | - Robert A Jenders
- Department of Internal Medicine and Center for Biomedical Informatics, Charles R Drew University of Medicine and Science, Los Angeles, California, USA.,Department of Medicine and Clinical and Translational Science Institute, University of California, Los Angeles, Los Angeles, California, USA
| | - Peter J Haug
- Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
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Comprehensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines. Artif Intell Med 2020; 103:101741. [PMID: 31928849 DOI: 10.1016/j.artmed.2019.101741] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 10/02/2019] [Accepted: 10/04/2019] [Indexed: 12/29/2022]
Abstract
BACKGROUND The over-use of antibiotics in clinical domains is causing an alarming increase in bacterial resistance, thus endangering their effectiveness as regards the treatment of highly recurring severe infectious diseases. Whilst Clinical Guidelines (CGs) focus on the correct prescription of antibiotics in a narrative form, Clinical Decision Support Systems (CDSS) operationalize the knowledge contained in CGs in the form of rules at the point of care. Despite the efforts made to computerize CGs, there is still a gap between CGs and the myriad of rule technologies (based on different logic formalisms) that are available to implement CDSSs in real clinical settings. OBJECTIVE To helpCDSS designers to determine the most suitable rule-based technology (medical-oriented rules, production rules and semantic web rules) with which to model knowledge from CGs for the prescription of antibiotics. We propose a framework of criteria for this purpose that is extensible to more generic CGs. MATERIALS AND METHODS Our proposal is based on the identification of core technical requirements extracted from both literature and the analysis of CGs for antibiotics, establishing three dimensions for analysis: language expressivity, interoperability and industrial aspects. We present a case study regarding the John Hopkins Hospital (JHH) Antibiotic Guidelines for Urinary Tract Infection (UTI), a highly recurring hospital acquired infection. We have adopted our framework of criteria in order to analyse and implement these CGs using various rule technologies: HL7 Arden Syntax, general-purpose Production Rules System (Drools), HL7 standard Rule Interchange Format (RIF), Semantic Web Rule Language (SWRL) and SParql Inference Notation (SPIN) rule extensions (implementing our own ontology for UTI). RESULTS We have identified the main criteria required to attain a maintainable and cost-affordable computable knowledge representation for CGs. We have represented the JHH UTI CGs knowledge in a total of 12 Arden Syntax MLMs, 81 Drools rules and 154 ontology classes, properties and individuals. Our experiments confirm the relevance of the proposed set of criteria and show the level of compliance of the different rule technologies with the JHH UTI CGs knowledge representation. CONCLUSIONS The proposed framework of criteria may help clinical institutions to select the most suitable rule technology for the representation of CGs in general, and for the antibiotic prescription domain in particular, depicting the main aspects that lead to Computer Interpretable Guidelines (CIGs), such as Logic expressivity (Open/Closed World Assumption, Negation-As-Failure), Temporal Reasoning and Interoperability with existing HIS and clinical workflow. Future work will focus on providing clinicians with suggestions regarding new potential steps for CGs, considering process mining approaches and CGs Process Workflows, the use of HL7 FHIR for HIS interoperability and the representation of Knowledge-as- a-Service (KaaS).
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Transformation of Arden Syntax's medical logic modules into ArdenML for a business rules management system. Artif Intell Med 2018; 92:82-87. [DOI: 10.1016/j.artmed.2016.03.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Revised: 03/25/2016] [Accepted: 03/27/2016] [Indexed: 11/18/2022]
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5
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Executable medical guidelines with Arden Syntax—Applications in dermatology and obstetrics. Artif Intell Med 2018; 92:71-81. [DOI: 10.1016/j.artmed.2016.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Accepted: 08/10/2016] [Indexed: 11/23/2022]
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Nan S, Van Gorp P, Lu X, Kaymak U, Korsten H, Vdovjak R, Duan H. A meta-model for computer executable dynamic clinical safety checklists. BMC Med Inform Decis Mak 2017; 17:170. [PMID: 29233155 PMCID: PMC5727863 DOI: 10.1186/s12911-017-0551-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 11/19/2017] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. METHODS We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. RESULTS Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. CONCLUSIONS We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.
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Affiliation(s)
- Shan Nan
- School of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.,School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Pieter Van Gorp
- School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Xudong Lu
- School of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China. .,School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Uzay Kaymak
- School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Hendrikus Korsten
- School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Anesthesiology and Intensive Care, Catharina Ziekenhuis in Eindhoven, Eindhoven, The Netherlands
| | | | - Huilong Duan
- School of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
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Ali T, Hussain M, Ali Khan W, Afzal M, Hussain J, Ali R, Hassan W, Jamshed A, Kang BH, Lee S. Multi-model-based interactive authoring environment for creating shareable medical knowledge. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 150:41-72. [PMID: 28859829 DOI: 10.1016/j.cmpb.2017.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Revised: 07/18/2017] [Accepted: 07/20/2017] [Indexed: 06/07/2023]
Abstract
OBJECTIVE Technologically integrated healthcare environments can be realized if physicians are encouraged to use smart systems for the creation and sharing of knowledge used in clinical decision support systems (CDSS). While CDSSs are heading toward smart environments, they lack support for abstraction of technology-oriented knowledge from physicians. Therefore, abstraction in the form of a user-friendly and flexible authoring environment is required in order for physicians to create shareable and interoperable knowledge for CDSS workflows. Our proposed system provides a user-friendly authoring environment to create Arden Syntax MLM (Medical Logic Module) as shareable knowledge rules for intelligent decision-making by CDSS. METHODS AND MATERIALS Existing systems are not physician friendly and lack interoperability and shareability of knowledge. In this paper, we proposed Intelligent-Knowledge Authoring Tool (I-KAT), a knowledge authoring environment that overcomes the above mentioned limitations. Shareability is achieved by creating a knowledge base from MLMs using Arden Syntax. Interoperability is enhanced using standard data models and terminologies. However, creation of shareable and interoperable knowledge using Arden Syntax without abstraction increases complexity, which ultimately makes it difficult for physicians to use the authoring environment. Therefore, physician friendliness is provided by abstraction at the application layer to reduce complexity. This abstraction is regulated by mappings created between legacy system concepts, which are modeled as domain clinical model (DCM) and decision support standards such as virtual medical record (vMR) and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). We represent these mappings with a semantic reconciliation model (SRM). RESULTS The objective of the study is the creation of shareable and interoperable knowledge using a user-friendly and flexible I-KAT. Therefore we evaluated our system using completeness and user satisfaction criteria, which we assessed through the system- and user-centric evaluation processes. For system-centric evaluation, we compared the implementation of clinical information modelling system requirements in our proposed system and in existing systems. The results suggested that 82.05% of the requirements were fully supported, 7.69% were partially supported, and 10.25% were not supported by our system. In the existing systems, 35.89% of requirements were fully supported, 28.20% were partially supported, and 35.89% were not supported. For user-centric evaluation, the assessment criterion was 'ease of use'. Our proposed system showed 15 times better results with respect to MLM creation time than the existing systems. Moreover, on average, the participants made only one error in MLM creation using our proposed system, but 13 errors per MLM using the existing systems. CONCLUSION We provide a user-friendly authoring environment for creation of shareable and interoperable knowledge for CDSS to overcome knowledge acquisition complexity. The authoring environment uses state-of-the-art decision support-related clinical standards with increased ease of use.
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Affiliation(s)
- Taqdir Ali
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
| | - Maqbool Hussain
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea; College of Electronics and Information Engineering, Sejong University, Seoul, South Korea.
| | - Wajahat Ali Khan
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
| | - Muhammad Afzal
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea; College of Electronics and Information Engineering, Sejong University, Seoul, South Korea.
| | - Jamil Hussain
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
| | - Rahman Ali
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
| | - Waseem Hassan
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
| | - Arif Jamshed
- Department of Radiation Oncology, Shaukat Khanum Memorial Cancer Hospital and Research Centre, 7A Block R-3, M.A. Johar Town, Lahore 54782, Pakistan.
| | - Byeong Ho Kang
- Computing and Information Systems, University of Tasmania, Hobart 7001, Tasmania, Australia.
| | - Sungyoung Lee
- Department of Computer Science and Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si 446-701, Gyeonggi-do, Republic of Korea.
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Jenders RA, Adlassnig KP, Fehre K, Haug P. Evolution of the Arden Syntax: Key Technical Issues from the Standards Development Organization Perspective. Artif Intell Med 2016; 92:10-14. [PMID: 27773563 DOI: 10.1016/j.artmed.2016.08.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Accepted: 08/09/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND The initial version of the Arden Syntax for Medical Logic Systems was created to facilitate explicit representation of medical logic in a form that could be easily composed and interpreted by clinical experts in order to facilitate clinical decision support (CDS). Because of demand from knowledge engineers and programmers to improve functionality related to complex use cases, the Arden Syntax evolved to include features typical of general programming languages but that were specialized to meet the needs of the clinical decision support environment, including integration into a clinical information system architecture. METHOD Review of the design history and evolution of the Arden Syntax by workers who participated in this evolution from the perspective of the standards development organization (SDO). RESULTS In order to meet user needs, a variety of features were successively incorporated in Arden Syntax. These can be grouped in several classes of change, including control flow, data structures, operators and external links. These changes included expansion of operators to manipulate lists and strings; a formalism for structured output; iteration constructs; user-defined objects and operators to manipulate them; features to support international use and output in different natural languages; additional control features; fuzzy logic formalisms; and mapping of the entire syntax to XML. The history and rationale of this evolution are summarized. CONCLUSION In response to user demand and to reflect its growing role in clinical decision support, the Arden Syntax has evolved to include a number of powerful features. These depart somewhat from the original vision of the syntax as simple and easily understandable but from the SDO perspective increase the utility of this standard for implementation of CDS. Backwards compatibility has been maintained, allowing continued support of the earlier, simpler decision support models.
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Affiliation(s)
- Robert A Jenders
- Center for Biomedical Informatics, Charles Drew University, Los Angeles, CA 90059, USA; Department of Medicine, Clinical and Translational Science Institute, University of California, Los Angeles, CA 90095, USA.
| | - Klaus-Peter Adlassnig
- Section for Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria; Medexter Healthcare GmbH, Borschkegasse 7/5, 1090 Vienna, Austria
| | - Karsten Fehre
- Medexter Healthcare GmbH, Borschkegasse 7/5, 1090 Vienna, Austria
| | - Peter Haug
- Homer Warner Research Center, Intermountain Healthcare, 5121 South Cottonwood Street, Murray, UT 84107, USA; Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, UT 84108, USA
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Rodrigues JF, Paulovich FV, de Oliveira MCF, de Oliveira ON. On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis. Nanomedicine (Lond) 2016; 11:959-82. [PMID: 26979668 DOI: 10.2217/nnm.16.35] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
An overview is provided of the challenges involved in building computer-aided diagnosis systems capable of precise medical diagnostics based on integration and interpretation of data from different sources and formats. The availability of massive amounts of data and computational methods associated with the Big Data paradigm has brought hope that such systems may soon be available in routine clinical practices, which is not the case today. We focus on visual and machine learning analysis of medical data acquired with varied nanotech-based techniques and on methods for Big Data infrastructure. Because diagnosis is essentially a classification task, we address the machine learning techniques with supervised and unsupervised classification, making a critical assessment of the progress already made in the medical field and the prospects for the near future. We also advocate that successful computer-aided diagnosis requires a merge of methods and concepts from nanotechnology and Big Data analysis.
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Affiliation(s)
- Jose F Rodrigues
- Institute of Mathematics & Computer Science, University of Sao Paulo (USP), 13560-970 Sao Carlos, SP, Brazil
| | - Fernando V Paulovich
- Institute of Mathematics & Computer Science, University of Sao Paulo (USP), 13560-970 Sao Carlos, SP, Brazil
| | - Maria CF de Oliveira
- Institute of Mathematics & Computer Science, University of Sao Paulo (USP), 13560-970 Sao Carlos, SP, Brazil
| | - Osvaldo N de Oliveira
- Sao Carlos Institute of Physics, University of Sao Paulo (USP), CP 369, 13560-970 Sao Carlos, SP, Brazil
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Development of a clinical decision support system for antibiotic management in a hospital environment. PROGRESS IN ARTIFICIAL INTELLIGENCE 2016. [DOI: 10.1007/s13748-016-0089-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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11
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Accessing complex patient data from Arden Syntax Medical Logic Modules. Artif Intell Med 2015; 92:95-102. [PMID: 26409750 DOI: 10.1016/j.artmed.2015.09.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Revised: 09/03/2015] [Accepted: 09/03/2015] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden Syntax Medical Logic Modules must be able to retrieve patient data from the electronic medical record in order to enable automated decision making. For patient data with a simple structure, for instance a list of laboratory results, or, in a broader view, any patient data with a list or table structure, this mapping process is straightforward. Nevertheless, if patient data are of a complex nested structure the mapping process may become tedious. Two clinical requirements - to process complex microbiology data and to decrease the time between a critical laboratory event and its alerting by monitoring Health Level 7 (HL7) communication - have triggered the investigation of approaches for providing complex patient data from electronic medical records inside Arden Syntax Medical Logic Modules. METHODS AND MATERIALS The data mapping capabilities of current versions of the Arden Syntax standard as well as interfaces and data mapping capabilities of three different Arden Syntax environments have been analyzed. We found and implemented three different approaches to map a test sample of complex microbiology data for 22 patients and measured their execution times and memory usage. Based on one of these approaches, we mapped entire HL7 messages onto congruent Arden Syntax objects. RESULTS While current versions of Arden Syntax support the mapping of list and table structures, complex data structures are so far unsupported. We identified three different approaches to map complex data from electronic patient records onto Arden Syntax variables; each of these approaches successfully mapped a test sample of complex microbiology data. The first approach was implemented in Arden Syntax itself, the second one inside the interface component of one of the investigated Arden Syntax environments. The third one was based on deserialization of Extended Markup Language (XML) data. Mean execution times of the approaches to map the test sample were 497ms, 382ms, and 84ms. Peak memory usage amounted to 3MB, 3MB, and 6MB. CONCLUSION The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with an appropriate XML data format.
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Zhang Y, Li H, Duan H, Zhao Y. Mobilizing clinical decision support to facilitate knowledge translation: a case study in China. Comput Biol Med 2015; 60:40-50. [PMID: 25754360 DOI: 10.1016/j.compbiomed.2015.02.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 02/13/2015] [Accepted: 02/14/2015] [Indexed: 11/30/2022]
Abstract
BACKGROUND A wide gulf remains between knowledge and clinical practice. Clinical decision support has been demonstrated to be an effective knowledge tool that healthcare organizations can employ to deliver the "right knowledge to the right people in the right form at the right time". How to adopt various clinical decision support (CDS) systems efficiently to facilitate evidence-based practice is one challenge faced by knowledge translation research. METHOD A computer-aided knowledge translation method that mobilizes evidence-based decision supports is proposed. The foundation of the method is a knowledge representation model that is able to cover, coordinate and synergize various types of medical knowledge to achieve centralized and effective knowledge management. Next, web-based knowledge-authoring and natural language processing based knowledge acquisition tools are designed to accelerate the transformation of the latest clinical evidence into computerized knowledge content. Finally, a batch of fundamental services, such as data acquisition and inference engine, are designed to actuate the acquired knowledge content. These services can be used as building blocks for various evidence-based decision support applications. RESULTS Based on the above method, a computer-aided knowledge translation platform was constructed as a CDS infrastructure. Based on this platform, typical CDS applications were developed. A case study of drug use check demonstrates that the CDS intervention delivered by the platform has produced observable behavior changes (89.7% of alerted medical orders were revised by physicians). DISCUSSION Computer-aided knowledge translation via a CDS infrastructure can be effective in facilitating knowledge translation in clinical settings.
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Affiliation(s)
- Yinsheng Zhang
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China; School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China.
| | - Haomin Li
- Children׳s Hospital, Institute of Translational Medicine, Zhejiang University, Hangzhou 310027, China.
| | - Huilong Duan
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China.
| | - Yinhong Zhao
- China National Center for Biotechnology Development, Beijing 100036, China.
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Arcia A, Velez M, Bakken S. Style Guide: An Interdisciplinary Communication Tool to Support the Process of Generating Tailored Infographics From Electronic Health Data Using EnTICE3. ACTA ACUST UNITED AC 2015; 3:1120. [PMID: 25848634 PMCID: PMC4371489 DOI: 10.13063/2327-9214.1120] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
PURPOSE In this case study we describe key features of the structured communication tool-a style guide-used to support interdisciplinary collaboration, and we propose the use of such a tool for research teams engaged in similar projects. We employ tailored infographics to present patient reported outcome data from a community health survey back, in a comprehensible and actionable manner, to the individuals who provided it. The style guide was developed to bridge the semantic gap between the domain and programming experts engaged in this effort. INNOVATION The style guide supports the communication of complex design specifications in a highly structured format that is nevertheless flexible enough to accommodate project growth. Unlike the typical corporate style guide that has a more narrative format, our style guide is innovative in its use of consistent fields across multiple, standalone entries. CREDIBILITY The process of populating the style guide prompted the designer toward greater design efficiency and led to consistent and specific instructions that met the framework architect's stated information needs. DISCUSSION AND CONCLUSION The guiding values in the creation of the style guide were consistency, clarity, and flexibility. It serves as a durable reference to the desired look and functionality of the final infographic product without dictating an implementation strategy. The style guide format can be adapted to meet the communication needs of other interdisciplinary teams facing a semantic gap.
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Sarkar IN, Chen ES, Rosenau PT, Storer MB, Anderson B, Horbar JD. Using Arden Syntax to identify registry-eligible very low birth weight neonates from the Electronic Health Record. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2014; 2014:1028-1036. [PMID: 25954412 PMCID: PMC4419950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Condition-specific registries are essential resources for supporting epidemiological, quality improvement, and clinical trial studies. The identification of potentially eligible patients for a given registry often involves a manual process or use of ad hoc software tools. With the increased availability of electronic health data, such as within Electronic Health Record (EHR) systems, there is potential to develop healthcare standards based approaches for interacting with these data. Arden Syntax, which has traditionally been used to represent medical knowledge for clinical decision support, is one such standard that may be adapted for the purpose of registry eligibility determination. In this feasibility study, Arden Syntax was explored for its ability to represent eligibility criteria for a registry of very low birth weight neonates. The promising performance (100% recall; 97% precision) of the Arden Syntax approach at a single institution suggests that a standards-based methodology could be used to robustly identify registry-eligible patients from EHRs.
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Affiliation(s)
| | | | - Paul T Rosenau
- University of Vermont, Burlington, VT ; Vermont Children's Hospital at Fletcher Allen Health Care, Burlington, VT
| | | | | | - Jeffrey D Horbar
- University of Vermont, Burlington, VT ; Vermont Oxford Network, Burlington, VT
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Kraus S, Castellanos I, Toddenroth D, Prokosch HU, Bürkle T. Integrating Arden-Syntax-based clinical decision support with extended presentation formats into a commercial patient data management system. J Clin Monit Comput 2013; 28:465-73. [PMID: 23354988 DOI: 10.1007/s10877-013-9430-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Accepted: 01/09/2013] [Indexed: 10/27/2022]
Abstract
The purpose of this study was to introduce clinical decision support (CDS) that exceeds conventional alerting at tertiary care intensive care units. We investigated physicians' functional CDS requirements in periodic interviews, and analyzed technical interfaces of the existing commercial patient data management system (PDMS). Building on these assessments, we adapted a platform that processes Arden Syntax medical logic modules (MLMs). Clinicians demanded data-driven, user-driven and time-driven execution of MLMs, as well as multiple presentation formats such as tables and graphics. The used PDMS represented a black box insofar as it did not provide standardized interfaces for event notification and external access to patient data; enabling CDS thus required periodically exporting datasets for making them accessible to the invoked Arden engine. A client-server-architecture with a simple browser-based viewer allows users to activate MLM execution and to access CDS results, while an MLM library generates hypertext for diverse presentation targets. The workaround that involves a periodic data replication entails a trade-off between the necessary computational resources and a delay of generated alert messages. Web technologies proved serviceable for reconciling Arden-based CDS functions with alternative presentation formats, including tables, text formatting, graphical outputs, as well as list-based overviews of data from several patients that the native PDMS did not support.
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Affiliation(s)
- Stefan Kraus
- Center for Communication and Information Technology, University Hospital Erlangen, Erlangen, Germany,
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Li D, Endle CM, Murthy S, Stancl C, Suesse D, Sottara D, Huff SM, Chute CG, Pathak J. Modeling and executing electronic health records driven phenotyping algorithms using the NQF Quality Data Model and JBoss® Drools Engine. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2012; 2012:532-41. [PMID: 23304325 PMCID: PMC3540464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
With increasing adoption of electronic health records (EHRs), the need for formal representations for EHR-driven phenotyping algorithms has been recognized for some time. The recently proposed Quality Data Model from the National Quality Forum (NQF) provides an information model and a grammar that is intended to represent data collected during routine clinical care in EHRs as well as the basic logic required to represent the algorithmic criteria for phenotype definitions. The QDM is further aligned with Meaningful Use standards to ensure that the clinical data and algorithmic criteria are represented in a consistent, unambiguous and reproducible manner. However, phenotype definitions represented in QDM, while structured, cannot be executed readily on existing EHRs. Rather, human interpretation, and subsequent implementation is a required step for this process. To address this need, the current study investigates open-source JBoss® Drools rules engine for automatic translation of QDM criteria into rules for execution over EHR data. In particular, using Apache Foundation's Unstructured Information Management Architecture (UIMA) platform, we developed a translator tool for converting QDM defined phenotyping algorithm criteria into executable Drools rules scripts, and demonstrated their execution on real patient data from Mayo Clinic to identify cases for Coronary Artery Disease and Diabetes. To the best of our knowledge, this is the first study illustrating a framework and an approach for executing phenotyping criteria modeled in QDM using the Drools business rules management system.
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