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Technological Innovations in the Development of Cardiovascular Clinical Information Systems

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Abstract

Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.

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References

  1. Bates, D. W., Teich, J. M., Lee, J., Seger, D., Superman, G. J., Ma’Luff, N., Boyle, D., and Leape, L., The impact of computerized physician order entry on medication error prevention. J. Am. Med. Inform. Assoc. 6(4):313–321, 1999.

    Article  Google Scholar 

  2. Fraenkel, D. J., Cowie, M., and Daley, P., Quality benefits of an intensive care clinical information system. Crit. Care Med. 31(1):120–125, 2003.

    Article  Google Scholar 

  3. James, G. W., Christine, L. B., Roque, P., Rolf, M. G., and Patrick, J. S., A database management system for cardiovascular disease. Comput. Meth. Programs Biomed. 20(1):117–121, 1985.

    Article  Google Scholar 

  4. Kittredge, R. L., Estey, G., Pappas, J. J., and Barnett, G. O., Implementing a web-based clinical information system using EMR middle layer services. In: A Conference of the American Medical Informatics Association. Hanley And Belfus, 1996.

  5. Lucas, H., Information and communications technology for future health systems in developing countries. Soc. Sci. Med. 66(10):2122–2132, 2008.

    Article  MathSciNet  Google Scholar 

  6. Wright, J. G., Bieniewski, C. L., Pifarre, R., Gunnar, R. M., and Scanlon, P. J., A database management system for cardiovascular disease. Comput. Meth. Programs Biomed. 20(1):117–121, 1985.

    Article  Google Scholar 

  7. Matheny, M. E., and Ohno-Machado, L., Generation of knowledge for clinical decision support: statistical and machine learning techniques. In: Greenes, R. A., (Ed.), Clinical Decision Support: The Road Ahead (pp. 227–248). 2007.

  8. Wright, A., and Sittig, D. F., A four-phase model of the evolution of clinical decision support architectures. Int. J. Med. Inform. 77:641–649, 2008.

    Article  Google Scholar 

  9. DOH, 2008 Analysis of Cause of Death Statistics 2009. Department of Health.

  10. Gregory, P., and Samuel, Z. G., Computerized decision support for the cardiovascular clinician: Applications for Venous Thromboembolism prevention and beyond. Circulation 120:1133–1137, 2009.

    Article  Google Scholar 

  11. Amit, X. G., Neill, K. J. A., Heather, M., Rosas-Arellano, M. P., Devereaux, P. J., Joseph, B., Justina, S., and Haynes, R. B., Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: A systematic review. JAMA: Journal Of the American Medical Association 293(10):1223–1238, 2005.

    Article  Google Scholar 

  12. Bagayoko, C. O., Dufour, J. C., Chaacho, S., Bouhaddou, O., and Fieschi, M., Open source challenges for hospital information system (HIS) in developing countries: A pilot project in Mali. BMC Med. Inform. Decis. Mak. 10:22, 2010.

    Article  Google Scholar 

  13. Bellazzi, R., Montani, S., Riva, A., and Stefanelli, M., Web-based telemedicine systems for home-care: Technical issues and experiences. Comput. Meth. Programs Biomed. 64(3):175–187, 2001.

    Article  Google Scholar 

  14. Vanoirbeek, C., Rekika, Y. A., Karacapilidis, N., Aboukhaleda, O., Ebel, N., and Vader, J.-P., A web-based information and decision support system for appropriateness in medicine. Knowl.-Based Syst. 13(1):11–19, 2000.

    Article  Google Scholar 

  15. The ICCAS project homepage, http://www.iccas.de/. Adopted at 2010/12.

  16. Burgert, O., Neumuth, T., Lempp, F., Mudunuri, R., Meixensberger, J., Strauß, G., Dietz, A., Jannin, P., and Lemke, H. U., Linking top-level ontologies and surgical workflows. Int. J. Comput. Assist. Radiol. Surg. 1(1):437–438, 2006.

    Article  Google Scholar 

  17. Neumuth, T., Durstewitz, N., Fischer, M., Strauss, G., Dietz, A., Meixensberger, J., Jannin, P., Cleary, K., Lemke, H. U., and Burgert, O., Structured recording of intraoperative surgical workflows. In: Proceedings of the Society of Photo-Optical Instrumentation Engineers Conference (SPIE). 2006.

  18. Padoy, N., Horn, M., Feußner, H., Berger, M. O., and Navab, N., Recovery of surgical workflow: a model-based approach. In: Proceedings of the 21st International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS). 2007.

  19. Qi, J., Jiang, Z., Zhang, G., Miao, R., and Su, Q., A surgical management information system driven by workflow. In: Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics. 2006.

  20. Parmar, A. J., and Schaub, P. B., Workflow Integration Matrix: A framework to support the development of surgical information systems. Des. Stud. 29(4):338–368, 2008.

    Article  Google Scholar 

  21. Parmar, A. J., and Pattynama, P. M. T., A surgeon centered framework towards analyzing the surgical workflow. Int. J. Comput. Assist. Radiol. Surg. 2:154–156, 2007.

    Google Scholar 

  22. Storari, S., Lamma, E., Mancini, R., Mello, P., Motta, R., Patrono, D., and Canova, G., Validation of biochemical laboratory results using the DNSev expert system. Expert Syst. Appl. 25:503–515, 2003.

    Article  Google Scholar 

  23. Bellazzi, R., and Zupan, B., Predictive data mining in clinical medicine: Current issues and guidelines. Int. J. Med. Inform. 77:81–97, 2008.

    Article  Google Scholar 

  24. Eom, J.-H., Kim, S.-C., and Zhang, B.-T., AptaCDSS-E: A classifier ensemble-based clinical decision support system for cardiovascular disease level prediction. Expert Syst. Appl. 34:2465–2479, 2008.

    Article  Google Scholar 

  25. Hsieh, N.-C., Shih, C.-C., Hung, L.-P., and Chan, C.-H., Intelligent postoperative morbidity prediction of heart disease using artificial intelligence techniques. In: National Taipei College of Nursing, Technical Report. Taipei, 2010.

  26. Wears, R. L., and Berg, M., Computer technology and clinical work: Still waiting for Godot. J. Am. Med. Assoc. 293(10):1261–1263, 2005.

    Article  Google Scholar 

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Acknowledgement

This research was partially supported by National Science Council of Taiwan (NSC 97-2410-H-227-002-MY2).

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Correspondence to Nan-Chen Hsieh.

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Hsieh, NC., Chang, CY., Lee, KC. et al. Technological Innovations in the Development of Cardiovascular Clinical Information Systems. J Med Syst 36, 965–978 (2012). https://doi.org/10.1007/s10916-010-9561-5

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  • DOI: https://doi.org/10.1007/s10916-010-9561-5

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