Epidemiologic Research on Real-World Medical Data in Japan: Volume 2 (SpringerBriefs for Data Scientists and Innovators, 2)

Preface\nOverview\nContents\nContributors\nAbbreviations\nList of Figures\nList of Tables\nClinical Pathway\nReal World Medical Data and Clinical Pathway in Japan\n	1 Clinical Pathway in Japan\n	2 Outcome-Oriented Clinical Pathways\n	3 How to Collect Data from CP\n	4 BOM (Basic Outcome Master)\n	5 Dynamic Template [2]\n	6 How to Store the Data\n	7 How to Produce Big Data\n	8 CP and Recording\n	9 How to Analyze the Data and Improve Quality of Medicine\n	10 Future Subject\n	References\nMedical Process Analysis by Using All-Variance Type Outcome-Oriented Electronic Clinical Pathway Data-Exploratory Extracting Critical Indicator\n	1 Introduction\n	2 Critical Indicator\n	3 Analysis of Outcome Oriented CP Data-Exploratory Extracting Critical Indicator (CI)\n	4 Conclusion\n	References\nInformation and Data Standard Development for Clinical Pathways\n	1 Introduction\n	2 Overall System Design of the ePath Project\n	3 ePath Standards\n		3.1 ePath Message\n		3.2 ePath Data Repository\n		3.3 Standard Outcome-Oriented Pathway System\n		3.4 ePath Data Platform\n	4 ePath Project in the Future\n	References\nStandard Code Mapping and Data Quality\nJapan Laboratory Code (JLAC) 10\n	1 History\n	2 Structure of JLAC10Description of Activity and Work Performed\n	3 Operation and Maintenance\n	4 JLAC11\n	References\nICD-10 and ICD-11 in Japan\n	1 History of ICD and Usage in Japan\n	2 ICD-11\n	3 Application of ICD-11 to Japan and Future Prospects\nStandard Codes for Prescribing Drugs Use Multiple Code Systems Depending on Their Purpose\n	References\nData Quality Governance Experience at the MID-NET Project\n	1 Development of Procedure for Unified Management of Standard Codes\n	2 Effect of Data Quality Management Through a Governance Center\n	3 Development of Real-Time Validation Tool for Central Governance\n	References\nPhenotyping\nPhenotyping in Japan\n	1 Real-World Data, Designed Data, and Role of Phenotyping\n	2 Three Stages that Put the Use of Clinical Data on Track\n	3 Methods of Phenotyping\n	4 Evaluation of Phenotyping\n	5 What is the Best Phenotyping Algorithm?\n	6 Outcome Validation in Pharmacoepidemiology and Phenotyping\nPhenotyping of Administrative Claims Data\nA Phenotyping Study Using MID-NET Database\n	1 Introduction\n	2 Background: Phenotyping Method Development Using MID-NET\n	3 Trial: Development of Phenotyping Algorithms to Identify Interstitial Pneumonia\n	4 Future Prospects of Phenotyping Studies Using MID-NET\n	References\nIntegration of Phenotyping Algorithms in Japan\n	1 Introduction\n	2 Short Report: Phenotyping Algorithm Collection in AMED Projects\n		2.1 Study Methods\n		2.2 Results\n	3 Future Prospects for Integration of Phenotyping Algorithms\n	References\nData Analysis on Real World Data\nAnalysis on Real-World Data: An Overview\n	1 What Can We Do with Real-World Data?\n		1.1 Real-World Medical Databases Compared to Conventional Study Designs\n		1.2 Distinguish the Purposes: Prediction Versus Causal Inference\n	2 Sources of and Measures Against Biases in RWD\n		2.1 Missing Data\n		2.2 Measurement Error\n		2.3 Nonrandom Sample Selection\n		2.4 Confounding\n	3 Statistical Methods to Handle the Confounding Bias\n		3.1 Regression and Propensity Score Modeling to Approximate Stratified Analysis\n		3.2 Methods for Time-Dependent Confounding in Sustained/Repeated Treatments\n		3.3 Applicability of Machine-Learning and Quasi-Experimental Techniques\n	4 Summary\n	References\nProblems in Japanese Real-World Medical Data Analyses\n	1 A Mini Review of Studies Analyzing the Japanese Real-World Medical Data (RWMD)\n		1.1 The Method of Mini Review\n		1.2 The Results of the Review\n	2 The Problems in Japanese RWMD Analyses\n	3 Summary\n	Appendix\n	References\nEthical Issues of Data Secondary Use in Japan\nEthical, Legal, and Social Issues Pertaining to the Use of Real-World Health Data in Japan\n	1 Introduction\n	2 Protecting Privacy Through the Act on Personal Information Protection\n	3 Privacy in the Age of Big Data\n	4 Ethical, Legal, and Social Implications\nThe Next-Generation Medical Infrastructure Law\n	1 Japan’s Progress in Introducing IT in Healthcare\n	2 Operating Rules and Security\n	3 Japan’s Legal System for Protecting Personal Information\n	4 The Next-Generation Medical Infrastructure Law\n	5 Conclusion\n	References