Shahram Ebadollahi
ABSTRACT
Healthcare is a data-rich but information-poor domain. Terabytes of multimedia medical data are being generated on a monthly basis in a typical healthcare organization in order to document patients' health status and care process. Government and health-related organizations are pushing for fully electronic, cross-institution, integrated Electronic Health Records to provide a better, cost effective and more complete access to this data. However, provision of efficient access to the content of such records for timely and decision-enabling information extraction will not be available. Such a capability is essential for providing efficient decision support and objective evidence to clinicians. In addition researchers, medical students, patients, and payers could also benefit from it. We present the idea of concept-based multimedia health records, which aims at organizing the health records at the information level. We will explore the opportunities and possibilities that such an organization will provide, what role the field of multimedia content management could play to materialize this type of health record organization, and what the challenges will be in the quest for realizing the idea.We believe that the field of multimedia can play a very active role in taking healthcare information systems to the next level by facilitating the access to decision-enabling information for different types of users in healthcare. Our goal is to share with the community our thoughts on where the field of multimedia content management research should be focusing its attention to have a fundamental impact on the practice of medicine.
- D. Brailer, Key-Note Speech. 2005: Healthcare Information and Management Systems Society (HIMSS) Annual Conference & Exhibition.Google Scholar
- L.T. Kohn, J.M. Corrigan, M.S. Donaldson, To Err is Human: Building a Safer Health System. 1999: National Academy Press.Google Scholar
- M. Sonka, J.M.F., Handbook of Medical Imaging, Volume 2. Display and PACSMedical Image Processing and Analysis. Vol. 2. 2002. 1250.Google Scholar
- J. Jan, Medical Image Processing, Reconstruction and Restoration: Concepts and Methods. 2005: CRC Press. 730.Google Scholar
- Y. Kim, S.C. Horii, Handbook of Medical Imaging, Volume 3. Display and PACS. Vol. 3. 2000. 512.Google Scholar
- H.K. Huang, PACS and Imaging Informatics: Basic Principles and Applications. 2nd ed. 2004: Wiley-Liss.Google Scholar
- ANSI., Health Level Seven. http://www.hl7.org/Google Scholar
- NEMA, Digital Imaging and Communications in Medicine (DICOM), http://medical.nema.org/Google Scholar
- J.H. Kaufman, I.Eiron, G. Deen, D.A. Ford, E. Smith, S. Knoop, H. Nelken, T. Kol, Y. Mesika, K. Witting, K. Julier, C. Bennett, B. Rapp, B. Carmeli, S. Cohen, From Regional Healthcare Information Organizations to a National Healthcare Information Infrastructure. Perspectives in Health Information Management, 2005. 2(10).Google Scholar
- H. Feigenbaum, Echocardiography. 1993: Lea Febiger.Google Scholar
- A.A.T. Bui, R.K.Taira, J.D.N. Dionisio, D.R. Aberle, S. El-Saden, H. Kangarloo, Evidence-based Radiology: Requirements for Electronic Access. Academic radiology, 2002.Google Scholar
- R. Smith, What Clinical Information do Doctors Need? BMJ (Clinical research ed.), 1996: p. 1062--1068.Google Scholar
- NLM, Unified Medical Language System (UMLS), http://umls.nlm.nih.gov/Google Scholar
- C. Rosse, J.L.V. Mejino, B.R. Modayur, R.M. Jakobovits, K.P. Hinshaw, J.F. Brinkley, Motivation and Organizational Principles for Anatomical Knowledge Representation: The Digital Anatomist Symbolic Knowledge Base. Journal of the American Medical Informatics Association, 1998. 5(1): p. 17--40.Google Scholar
- J.F. Brinkley, C.Rosse., Imaging Informatics and the Human Brain Project: the Role of Structure, Review. Yearbook of Medical Informatics, 2002: p. 111--128.Google Scholar
- T. McInerney, D.Terzopolous., Deformable Models in Medical Image Analysis: A Survey. Medical Image Analysis, 1996. 1(2): p. 91--108.Google Scholar
- M.G. Linguraru, M.A. Gonzalez Ballester, N. Ayache., Deformable Atlases for the Segmentation of Internal Brain Nuclei in Magnetic Resonance Imaging. Acta Universitatis Cibiniensis, Technical Series, 2006.Google Scholar
- S. Ebadollahi, S.-F.Chang., H. Wu. Echocardiogram Videos: Summarization, Temporal Segmentation and Browsing. in IEEE International Conference on Image Processing. 2002.Google Scholar
- H. Chen, S.S. Fuller, W. Hersh, Medical Informatics: Knowledge Management and Data Mining in Biomedicine. 2005. 696. 20. J. Fernandez, M.Harris, C. Meyer. Combining Algorithms in Automatic Detection of R-peaks in ECG Signals. in IEEE Symposium of Computer-based Medical Systems (CBMS). 2005. Google ScholarDigital Library
- S. Ebadollahi, S.F. Chang, H. Wu. Automatic View Recognition in Echocardiogram Videos Using Parts-Based Representation. in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR). 2004. Washington D.C. Google ScholarDigital Library
- K. McKeown S.F. Chang, J.C., S. Feiner, C. Friedman, L. Gravano, V. Hartizvassiloglou, S. Johnson, D. Jordan, J. Klavans, A. Kushniruk, V. Patel, S. Teufel. PERSIVAL, A System for Personalized Search and Summarization Over Multimedia Healthcare Information. in IEEE/ACM Joint Conference on Digital Libraries (JCDL). 2001. Google ScholarDigital Library
- N. Kauff, M. Robson, R. Barakat, L. Norton, K. Offit, Cancer-Reducing Benefits of Preventive Surgery may be Specific to Gene Mutation. American Society of Clinical Oncology, 2006.Google Scholar
- T. Syeda-Mahmood, D. Ponceleon, J. Yang. Validating cardiac echo diagnosis through video similarity. in ACM Multimedia. 2005. Google ScholarDigital Library
- T. Syeda-Mahmood, Segmenting Actions in Velocity Curve SPace. in International Conference on Pattern Recognition (ICPR). 2002. Google ScholarDigital Library
- S. Ebadollahi, Analysis of Video Content using Statistical Spatio-Temporal Models, in Department of Electrical Engineering. 2005, Columbia University: New York. p. 249.Google Scholar
- (W3C), Synchronized Multimedia Integration Language (SMIL) 1.0 Specification, http://www.w3.org/TR//REC-smil/Google Scholar
- G. Whalen, Medical Textbook Summarization and Guided Navigation using Statistical Sentence Extraction. in Proceedings of the American Medical Informatics Association Symposium (AMIA 2005). 2005.Google Scholar
- S. Muresan, J.L. Klavans. A method for Automatically Building and Evaluating Dictionary Resources. in Proceedings of the Language Resources and Evaluation Conference (LREC 2002). 2002.Google Scholar
- J. Klavans, S.Muresan, Evaluation of the DEFINDER System for Fully Automatic Glossary Construction. in Proceedings of the American Medical Informatics Association Symposium (AMIA 2001). 2001.Google Scholar
Index Terms
- Concept-based electronic health records: opportunities and challenges
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Reviews
David Gary Hill
Readers who have an active interest in the future of electronic health records (EHR) systems will find this paper essential. It presents the idea that electronic health records can be organized around anatomical concepts. The paper then discusses what concept-based anatomical knowledge representation involves and how concept-based EHR systems might materialize. Typically, health record systems deal with patient data at the document level. Yet, to improve the medical decision making process, clinicians and other users of medical records need data organized at the information level. To do this, concept-based multimedia health records can be processed with analytical engines that are guided by relevant domain knowledge; this requires the concepts and the relationships among them to be defined, so they can be organized in a coherent fashion. The biomedical domain has ontologies available, such as the National Library of Medicine Unified Medical Language System, that capture and represent anatomical concepts and the relationships among those concepts. The benefits of concept-based electronic health records could potentially lead to care process improvements, a reduction in the number and impact of medical errors, and a decrease in costs. A number of challenges exist in successfully designing and implementing concept-based electronic health records, such as the need to extend the existing ontology for concepts. This paper should serve as a springboard for debate and research on how to meet these challenges in order to be able to extract additional value from EHR systems when they finally become a common reality. Online Computing Reviews Service
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