Modeling of Nursing Knowledge for Multilevel Information Systems                         Joyce Rocha de Matos Nogueira, Ti...
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Poster IHI 2012

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Poster presented at the 2nd ACM International Health Informatics Symposium SIGHIT in 2012
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.

#mlhim #semantic_interoperability #health_informatics

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Poster IHI 2012

  1. 1. Modeling of Nursing Knowledge for Multilevel Information Systems Joyce Rocha de Matos Nogueira, Timothy Wayne Cook, Luciana Tricai Cavalini Multilevel Healthcare Information Modeling (MLHIM) Laboratory National Institute of Science and Technology – Medicine Assisted by Scientific Computing Logo caexAbstract. This paper presents a modeling strategy of nursing knowledge, based on multilevel modeling of healthcare systems. Through a systematicreview, nursing record instruments were obtained, and one was chosen for knowledge modeling according to the Multilevel Healthcare InformationModeling (MLHIM) specifications.Introduction. Nursing Informatics is the area of knowledge that studies the application of technological resources in nursing teaching, practice,management and care [7]. Healthcare applications designed to improve the definition of nursing informatics should take into account some specificneeds of the area, for example, meeting the demand for standardization of nursing concepts [3].An important way of standardizing information is the use of validated instruments for data collection such as questionnaires. Questionnaires offer anobjective means of collecting information and can be used as a research tool in clinical or epidemiological studies [1].Thus, the objective of this study is to review the literature related to validated questionnaires for the nursing diagnosis and nursing clinical research andto select a use case for modeling the corresponding knowledge according to the principles of multilevel modeling of healthcare information systems.Method. A systematic review was performed, searching PubMed, Scopus and the ISI Web of Knowledge. The MeSH terms used were: “Validation ANDStudies AND (Nursing Diagnosis OR Clinical Nursing Research)”. Papers published until June 2011 were included.Knowledge modeling was based on the principles of multilevel modeling of healthcare information systems. This approach ensures the features ofinteroperability, semantic coherence and long-term persistence of information for healthcare applications [4].In multilevel modeling, the Reference Model classes are generic and therefore persistent. In the Domain Model, the constraints on the ReferenceModel provide a semantic interpretation of the objects stored by the Reference Model [5].The knowledge modeling of the selected nursing concepts was performed by using the Constraint Definition Designer (CDD), a graphical mind-mapping tool that allows creation of XSD files according to the Multilevel Healthcare Information Modeling (MLHIM) specifications(https://launchpad.net/mlhim).Results. A total of 190 papers were retrieved, and 18 were selected for reading. For the present study the Fehring model for clinical validation of thediagnosis of decreased cardiac output [6] was modeled. The clinical concepts modeled were: fatigue, dyspnea, edema, orthopnea, paroxysmalnocturnal dyspnea, and elevated central venous pressure (primary characteristics), weight gain, hepatomegaly, jugular vein distension, palpitations,crackles, oliguria, coughing, clammy skin, and skin color changes (secondary characteristics).The knowledge modeling was based on the openEHR archetypes, available at the openEHR Clinical Knowledge Manager (http://www.openehr.org/knowledge).The mapping between the clinical concepts of the Fehring model and the openEHR archetypes produced the structure shown on Table 1. Table 1. Mapping between the Fehring models clinical concepts and the openEHR archetypes. Concept openEHR Archetype Fatigue Symptom (CLUSTER) Dyspnea Symptom (CLUSTER) Edema Oedema (CLUSTER) Orthopnea Respirations (OBSERVATION) Paroxysmal nocturnal dyspnea Respirations (OBSERVATION) Elevated central venous pressure Central venous pressure (OBSERVATION) Weight gain Body weight (OBSERVATION) Hepatomegaly Examination of the abdomen (CLUSTER) Jugular vein distension Examination (CLUSTER) Palpitations Symptom (CLUSTER) Crackles Auscultation of the chest (CLUSTER) Oliguria Urination (OBSERVATION) Coughing Symptom (CLUSTER) Figure 1. Modeling of the CCD for the clinical concept of Clammy skin Inspection of skin (CLUSTER) dyspnea according to the MLHIM 2.3.0. specifications. Skin color changes Inspection of skin (CLUSTER)This mapping demonstrated that many openEHR archetypes would have to be specialized in order to allow direct record of the clinical concepts of cardiacdecrease output according to the Fehring model. Based on this finding, the concepts were modeled as Concept Constraint Definitions (CCDs), according to theMLHIM specifications version 2.3.0. The graphical representation of the CCD modeled for dyspnea is shown on Figure 1.This paper presented a knowledge modeling process of nursing concepts for two multilevel modeling specifications (openEHR and MLHIM). Those results shows thepossibility of standardized representation of nursing concepts, in addition to the development of reference terminologies and controlled vocabularies.[1] Boynton, P. M. and Greenhalgh, T. 2004. Selecting, designing, and developing your questionnaire. BMJ 328, 7451 (May. 2004), 1312-1315. DOI=http://dx.doi.org/10.1136/bmj.328.7451.1312.[2] Cavalini, L. T., Cook, T.W. Health informatics: the relevance of open source and multilevel modeling. IFIP Advances in Information andCommunication Technology 365 (Oct. 2011), 338-347.[3] Coenen, A., Marin, H. F., Park, H. and Bakken, S. 2001. Collaborative efforts for representing nursing concepts in computer-based systems:international perspectives. JAMIA 8, 3 (May.-Jun. 2001), 202-211.[4] Garde. S., Knaup, P., Hovenga, E., Heard, S. 2007. Towards semantic interoperability for electronic health records. Methods Inf. Med. 46, 3 (May.-Jun.2007), 332-343. DOI= http://dx.doi.org/10.1160/ME5001.[5] Madsen, M., Leslie, H., Hovenga, E. J. and Heard, S. 2010. Sustainable clinical knowledge management: an archetype development life cycle. Stud.Health Technol. Inform. 151 (2010), 115-132.[6] Martins, Q. C., Aliti, G. and Rabelo, E. R. 2010. Decreased cardiac output: clinical validation in patients with decompensated heart failure. Int. J. Nurs.Terminol. Classif. 21, 4 (Oct.-Dec. 2010), 156-65.[7] Staggers, N. and Thompson, C. B. 2002. The evolution of definitions for nursing informatics: a critical analysis and revised definition. JAMIA 9, 3 (May.-Jun. 2002), 255-261. DOI= http://dx.doi.org/10.1197/jamia.M0946. 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