Japanese EMRs and IT in Medicine: Expansion, Integration, and Reuse of Data
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Objectives: The prevalence of electronic medical record in Japan varies according to the size of the hospital which is 62.5% in major hospitals, 21.7% in medium, 9.1% in small size hospitals, and 16.5% in clinics. The complete paperless system is very limited, though some major hospitals are aiming at this system. Several regional network systems which connect different platforms of EMRs, have been developing in many districts, while the final picture of a regional network has not been clearly proposed. To develop a whole electronic health record or personal health records system from the regional network data, we have several obstacles to overcome such as standardization, a privacy act, unique national health number. Methods: Some experimental trials have just been started. The reuse of the accumulated data has also just been initiated. We exploited text mining systems (term frequency-inverse document frequency method) to find similar cases and auto-audit Japanese diagnosis related group (DRG) coding by using discharge summaries. Results: The same or even a more extreme phenomenon of huge data accumulation is occurring in genetic research and confluence of multi-disciplines of informatics is the next step,which has an enormous accumulation of data and discoveries of the relations beyond the dimension of each informatics. Conclusions: We need another approach to science apart from the conventional method, and data-driven approach with data mining techniques must be brought in for each field. Informaticians have new important roles as coordinators to link up numerous phenomena over dimensions.
Abstract
Objectives: The prevalence of electronic medical record in Japan varies according to the size of the hospital which is 62.5% in major hospitals, 21.7% in medium, 9.1% in small size hospitals, and 16.5% in clinics. The complete paperless system is very limited, though some major hospitals are aiming at this system. Several regional network systems which connect different platforms of EMRs, have been developing in many districts, while the final picture of a regional network has not been clearly proposed. To develop a whole electronic health record or personal health records system from the regional network data, we have several obstacles to overcome such as standardization, a privacy act, unique national health number. Methods: Some experimental trials have just been started. The reuse of the accumulated data has also just been initiated. We exploited text mining systems (term frequency-inverse document frequency method) to find similar cases and auto-audit Japanese diagnosis related group (DRG) coding by using discharge summaries. Results: The same or even a more extreme phenomenon of huge data accumulation is occurring in genetic research and confluence of multi-disciplines of informatics is the next step,which has an enormous accumulation of data and discoveries of the relations beyond the dimension of each informatics. Conclusions: We need another approach to science apart from the conventional method, and data-driven approach with data mining techniques must be brought in for each field. Informaticians have new important roles as coordinators to link up numerous phenomena over dimensions.
참고문헌 (15)
- "Seed planning: market research & consulting"[URL]
- Takada A, "Dolphin project: cooperative regional clinical system centered on clinical information center", J Med Syst, 29, pp.391~400 (2005)
- Jha AK, "The use of health information technology in seven nations", Int J Med Inform, 77, pp.848~854 (2008)
- van der Linden H, "Towards a generic connection of EHR and DSS", Stud Health Technol Inform, 116, pp.211~216 (2005)
- Ruch P, "Evaluating and reducing the effect of data corruption when applying bag of words approaches to medical records", Int J Med Inform, 67, pp.75~83 (2002)
- Lan M, "Supervised and traditional term weighting methods for automatic text categoriza- tion", IEEE Trans Pattern Anal Mach Intell, 31, pp.721~735 (2009)
- Lu Z, "Evaluating relevance ranking strategies for MEDLINE retrieval", J Am Med Inform Assoc, 16, pp.32~36 (2009)
- Suzuki T, "Auto-selection of DRG codes from discharge summaries by text mining in several hospitals: analysis of difference of discharge summaries", Stud Health Technol Inform, 160, pp.1020~1024 (2010)
- "MeCab: yet another part-of-speech and morphological analyzer" (2009)[URL]
- McMillan TE, "Accuracy of information on medicines in hospital discharge summaries", Intern Med J, 36, pp.221~225 (2006)
- Callen J, "Accuracy of medication documentation in hospital discharge summaries: a retrospective analysis of medication transcription errors in manual and electronic discharge summaries", Int J Med Inform, 79, pp.58~64 (2010)
- O'Leary KJ, "Creating a better discharge summary: improvement in quality and timeliness using an electronic discharge summary", J Hosp Med, 4, pp.219~225 (2009)
- Yang JY, "Promoting synergistic research and education in genomics and bioinformatics", BMC Genomics, 9(Suppl 1), pp.I1~ (2008)
- Burgun A, "Accessing and integrating data and knowledge for biomedical research", Yearb Med Inform, pp.91~101 (2008)
- "The fourth paradigm: data-intensive scientific discovery" (2009)[URL]