001447356 000__ 04323cam\a2200553Ii\4500 001447356 001__ 1447356 001447356 003__ OCoLC 001447356 005__ 20230310004114.0 001447356 006__ m\\\\\o\\d\\\\\\\\ 001447356 007__ cr\cn\nnnunnun 001447356 008__ 220609s2022\\\\si\a\\\\ob\\\\000\0\eng\d 001447356 019__ $$a1327550717 001447356 020__ $$a9789811916229$$q(electronic bk.) 001447356 020__ $$a9811916225$$q(electronic bk.) 001447356 020__ $$z9789811916212 001447356 020__ $$z9811916217 001447356 0247_ $$a10.1007/978-981-19-1622-9$$2doi 001447356 035__ $$aSP(OCoLC)1327838914 001447356 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dOCLCQ 001447356 043__ $$aa-ja--- 001447356 049__ $$aISEA 001447356 050_4 $$aRA650.7.J3 001447356 08204 $$a614.40952$$223/eng/20220609 001447356 24500 $$aEpidemiologic research on real-world medical data in Japan.$$nVolume 2 /$$cNaoki Nakashima, editor. 001447356 264_1 $$aSingapore :$$bSpringer,$$c[2022] 001447356 264_4 $$c©2022 001447356 300__ $$a1 online resource (xxix, 120 pages) :$$billustrations (chiefly color). 001447356 336__ $$atext$$btxt$$2rdacontent 001447356 337__ $$acomputer$$bc$$2rdamedia 001447356 338__ $$aonline resource$$bcr$$2rdacarrier 001447356 4901_ $$aSpringerBriefs for data scientists and innovators,$$x2520-1921 ;$$vvolume 2 001447356 504__ $$aIncludes bibliographical references. 001447356 5050_ $$aPart 1: Clinical Pathway -- Chapter 1. Real World Medical Data Clinical Pathway in Japan -- Chapter 2. Medical process analysis by using all-variance type outcome-oriented electronic clinical pathway data -Exploratory extracting critical indicator -- Chapter 3. Information and Data standard development for Clinical Pathways -- Part 2: Standard Code Mapping and Data Quality -- Chapter 4. Japan Laboratory Code (JLAC) 10 -- Chapter 5. ICD-10 and ICD-11 in Japan -- Chapter 6. Standard codes for prescribing drugs use multiple code systems depending on their purpose -- Chapter 7. Data Quality Governance Experience at the MID-NET Project -- Part 3: Phenotyping -- Chapter 8. Phenotyping in Japan -- Chapter 9. Phenotyping of Administrative Claims Data -- Chapter 10. Phenotyping study using MID-NET database -- Chapter 11. Integration of phenotyping algorithms in Japan -- Part 4: Data Analysis on Real World Data -- Chapter 12. Analysis on Real-World Data: An Overview -- Chapter 13. Problems in Japanese real-world medical data analyses -- Part 5: Ethical Issues of Data Secondary Use in Japan -- Chapter 14. Ethical, Legal, and Social Issues Pertaining to the Use of Real-world Health Data in Japan -- Chapter 15. The Next-Generation Medical Infrastructure Law. 001447356 506__ $$aAccess limited to authorized users. 001447356 520__ $$aThis book analyzes the development of medical big data projects in Japan. Japan is experiencing unprecedented population aging, and labor productivity has decreased accordingly. Big data analysis of the Japanese medical real-world database (RWD) has the potential to tackle this issue. To allow readers to gain an understanding of Japanese medical big data analysis, the book discusses the original Japanese system that generates medical RWDs in the hospital medical records system, the nationwide standardized health checkup system, and the public medical insurance system in Japan. After introducing four major big data projects in the healthcare-medical field in Japan, the book explains the importance of creating information standards to maintain data quality and to analyze medical big data. It enables readers to analyze which standards are installed in which RWDs, how the standards are maintained, and which issues are prevalent in Japan. This book also describes the ethical processes involved in big data projects involving medical RWDs in Japan. 001447356 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 9, 2022). 001447356 650_0 $$aEpidemiology$$xResearch$$zJapan. 001447356 650_0 $$aMedical informatics$$zJapan. 001447356 650_0 $$aBig data$$zJapan. 001447356 655_0 $$aElectronic books. 001447356 7001_ $$aNakashima, Naoki,$$eeditor. 001447356 77608 $$iPrint version: $$z9811916217$$z9789811916212$$w(OCoLC)1302579881 001447356 830_0 $$aSpringerBriefs for data scientists and innovators ;$$vvolume 2.$$x2520-1921 001447356 852__ $$bebk 001447356 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-1622-9$$zOnline Access$$91397441.1 001447356 909CO $$ooai:library.usi.edu:1447356$$pGLOBAL_SET 001447356 980__ $$aBIB 001447356 980__ $$aEBOOK 001447356 982__ $$aEbook 001447356 983__ $$aOnline 001447356 994__ $$a92$$bISE