Research Trends and Future Issues Related to Pre-analysis Data Preprocessing in Large-scale Real-World Data ―With the Goal of Using it in Clinical Research― / 薬剤疫学

In recent years, the utilization of health care databases has been increasing worldwide. It is expected that Real World Data (RWD) will soon be effectively used for clinical research in Japan. On the other hand, database studies that use accumulated existing data such as electronic medical records, Diagnosis Procedure Combinations (DPCs), and health insurance claims, require extremely high loads of data preprocessing before statistical analysis is possible. So far, there is insufficient literature that describes the challenges of RWD preprocessing from an academic point of view. In this review paper, the challenges of database study are classified into three categories：（1）data content,（2）data structure, and（3）large-volume data handling. We then investigated existing preprocessing research and systematically introduced them. Most data preprocessing research targeted the improvement and reliability of the database itself through supplementing data contents required for each clinical research. There is very little research with the primary purpose of solving problems related to data structures and large-volume data processing. As the use of RWD for clinical research increases, the importance of the data preprocessing field will be recognized. In the future, we expect to see more research focused on RWD, which can enable the growth of clinical researches using RWD.

AD-SISCOLO: a decision-support tool to aid the management of a cervical cancer screening program

AbstractIntroduction: This paper aims to develop a data warehouse (AD-SISCOLO) in order to support the management of the cervical cancer screening program in the municipality of Rio de Janeiro/Brazil. As a part of the management process, the program managers of the municipality perform tedious manual work in order to calculate a series of performance indicators and then take decisions based on them. Methods AD-SISCOLO was implemented using the Pentaho BI Suite Business Intelligence Platform and the MySQL database management system. The indicators to be calculated and visualized in the tool were based on the municipal data of the cytopathology and histopathology tests from January 2012 until December 2014, which was obtained from the Information System of Cervical Cancer (SISCOLO) after a record linkage process. The follow-up indicators were based on a simplified version of the Brazilian guidelines for the cervical cancer screening. Results AD-SISCOLO allows the visualization of a set of test-based and follow-up indicators from different views and dimensions, which enable managers to monitor all the phases of the screening process and to identify the process' failures. Conclusions Compared with the current available environments in Brazil, AD-SISCOLO is unique in its visualization of the follow-up indicators of groups of women, according to their test results and age. Thereby it provides presentation flexibility to suit the program manager's needs.

Construction and Application of Data Analysis Platform of the Hospital Based on Data Warehouse / 医学信息学杂志

The paper analyzes the deficiencies of the traditional Hospital Information System (HIS),establishes the hospital data mining and analysis platform,introduces the platform architecture,builds the data mining models themed by analysis of hospital leaders,supervision and management of antibacterial drugs,analysis of hospital quality,analysis of single disease,expenditure control by medical insurance,etc.,and puts forward the smart solutions to improve the service tevel of hospitals on the basis of above.

Development of Clinical Data Mart of HMG-CoA Reductase Inhibitor for Varied Clinical Research

BACKGROUND: The increasing use of electronic medical record (EMR) systems for documenting clinical medical data has led to EMR data being increasingly accessed for clinical trials. In this study, a database of patients who were prescribed statins for the first time was developed using EMR data. A clinical data mart (CDM) was developed for cohort study researchers. METHODS: Seoul St. Mary's Hospital implemented a clinical data warehouse (CDW) of data for ~2.8 million patients, 47 million prescription events, and laboratory results for 150 million cases. We developed a research database from a subset of the data on the basis of a study protocol. Data for patients who were prescribed a statin for the first time (between the period from January 1, 2009 to December 31, 2015), including personal data, laboratory data, diagnoses, and medications, were extracted. RESULTS: We extracted initial clinical data of statin from a CDW that was established to support clinical studies; the data was refined through a data quality management process. Data for 21,368 patients who were prescribed statins for the first time were extracted. We extracted data every 3 months for a period of 1 year. A total of 17 different statins were extracted. It was found that statins were first prescribed by the endocrinology department in most cases (69%, 14,865/21,368). CONCLUSION: Study researchers can use our CDM for statins. Our EMR data for statins is useful for investigating the effectiveness of treatments and exploring new information on statins. Using EMR is advantageous for compiling an adequate study cohort in a short period.

Integrating Brazilian health information systems in order to support the building of data warehouses

AbstractIntroductionThis paper's aim is to develop a data warehouse from the integration of the files of three Brazilian health information systems concerned with the production of ambulatory and hospital procedures for cancer care, and cancer mortality. These systems do not have a unique patient identification, which makes their integration difficult even within a single system.MethodsData from the Brazilian Public Hospital Information System (SIH-SUS), the Oncology Module for the Outpatient Information System (APAC-ONCO) and the Mortality Information System (SIM) for the State of Rio de Janeiro, in the period from January 2000 to December 2004 were used. Each of the systems has the monthly data production compiled in dbase files (dbf). All the files pertaining to the same system were then read into a corresponding table in a MySQL Server 5.1. The SIH-SUS and APAC-ONCO tables were linked internally and with one another through record linkage methods. The APAC-ONCO table was linked to the SIM table. Afterwards a data warehouse was built using Pentaho and the MySQL database management system.ResultsThe sensitivities and specificities of the linkage processes were above 95% and close to 100% respectively. The data warehouse provided several analytical views that are accessed through the Pentaho Schema Workbench.ConclusionThis study presented a proposal for the integration of Brazilian Health Systems to support the building of data warehouses and provide information beyond those currently available with the individual systems.

Construction and Application of Regional Health Decision Support System Based on Business Intelligence / 医学信息学杂志

In order to improve health management efficiency and decision-making level, regional health decision support system is constructed based on regional health information platform and business intelligence ideas.Technical plan, construction contents and ap-plication examples in health management are introduced in the paper.

Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

A clinical research strategy using longitudinal observational data in the post-electronic health records era

Adoption of electronic health records (EHRs) is increasing worldwide. The worldwide EHR adoption rate is estimated to be around 9% to 12%. Thus, the accumulation of medical records in electronic form is also sharply increasing and is expected to be a precious asset for clinical research. Longitudinal observational studies based on EHRs are also increasing. Observational studies covering more than a million people are not rare at present. However, much of the current EHR data are equivalent in form to those of paper records, but are just stored in electronic stor-age devices, rather than as electronic data that can be transferred and shared without loss of clinical semantics. Current EHR systems must be improved in many ways to be used for anal-yses to yield important clinical knowledge. These improvements, which are addressed in this review, include the adoption of clinical data warehouses, use of controlled vocabulary, avoidance of personal/departmental research databases, a standardized interface of many diagnostic devices with the EHR system, control of time-stamp granularity, preparedness for whole-genome sequencing of every patient, confederation or consolidation of multi-institutional EHR data, protection of privacy and confidentiality, and an education system for clinical informaticians.

Successful use of customer relationship management system in hospital healthcare centers

Customer relationship management (CRM) is a valuable method for establishing long-term customer relationships across different business areas. CRM system stores and analyzes a vast amount of customer information and provides alternatives to meet customer expectations using data warehouse and on-line analysis processing technology. Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of CRM systems to meet diverse customer satisfaction. Leading the adoption of information technology in the healthcare businesses has enabled the use of CRM technology to develop close patient-provider relationship. Especially, healthcare centers are using CRM system to provide better healthcare services as well as customer management services. This study aims to explore the current status and influential factors that will stimulate and drive the successful use of CRM system in healthcare centers. For this purpose, a survey has been conducted for CRM system users in 13 healthcare centers to investigate the current status of CRM system and the influential factors for successful use. The evaluation criteria include four categories; system quality, information quality, service quality and perceived usefulness. These criteria have been developed based on previous researches, especially DeLone & McLean information system success model. In addition, the system output is evaluated by user satisfaction, personal performance and organizational performance. The study showed that users evaluated information quality and service quality positively and to be higher than other factors in terms of influence. And the user evaluation proved that CRM system provides increased user satisfaction, organizational performance, and especially, individual performance. This is clear evidence that CRM system will improve organizational efficiency and effectiveness, which in turn, can provide competitive advantage for the healthcare centers.

Procedimiento para el desarrollo de un sistema de inteligencia de negocios en la gestión de ensayos clínicos en el Centro de Inmunología Molecular / Procedure for development of a business intelligence system in the clinical trials management at the Center of Molecular Immunology

La presente investigación surgió como parte de la colaboración que existe entre la Universidad de las Ciencias Informáticas y el Centro de Inmunología Molecular. El objetivo fue desarrollar un procedimiento que contribuyera al almacenamiento y análisis de los ensayos clínicos y que facilitara la aplicación integral de la inteligencia de negocios en esta actividad. Se realizó una propuesta de procedimiento para conducir el desarrollo de soluciones de inteligencia de negocios en el centro. El procedimiento fue evaluado a partir del método de experto Delphi y se obtuvo el resultado de Muy adecuado. Se contó además con un aval del centro cliente, donde se valoró de satisfactorio el trabajo realizado. La implementación de este procedimiento permitirá almacenar toda la información que se gestiona, de manera íntegra y estándar, con lo que se logrará viabilizar los análisis estadísticos que se necesitan realizar por parte de los especialistas de la institución

Present paper appeared as part of cooperation existing between the Information Sciences University and the Center of Molecular Immunology. The aim was to develop a procedure contributing to storage and analysis of clinical trials and to integral application of business intelligence service in this activity. A procedure proposal was made to manage the development of solutions in business intelligence in our center. Procedure was assessed from the method of the Delphi expert method obtaining a result qualified as very appropriate. Implementation of this procedure will allows storing all information managed in an integral and standard way, thus achieving to make viable the statistic analyses needed to be performed by the specialists of the institution

Construction of data warehouse and decision support system of periodical literature of traditional Chinese medicine / 国际中医中药杂志

This article discussed the construction methods of data warehouse in terms of the establishment of Chinese medicine journal articles on the demand survey, the data warehouse model design, data extraction, transformation and loading process, and the construction of metadata and data dictionary, and analyzed the application of the data warehouse for supporting decision-making.

Research and design of comprehensive database for optimal decision-making in military medical service / 第二军医大学学报

Objective: To provide effective information resource for military medical support during strategic war, so as to provide a basis for the evidence-informed policy making in military medical service. Methods: A large quantity of multi-source and isomerism data were integrated and organized by the techniques of data warehouse and geography markup language. Multi-dimension subject models for decision-making in military medical commanding were constructed. Results: The integration of multi-source and isomerism data was achieved and comprehensive database was established for optimal decision-making in military medical service, which includes space data warehouse and its multi-dimension model for decision-making. The design of a 6-layer structure of data warehouse was also put forward. Conclusion: The database provides a comprehensive data platform for the optimal decision support of military medical service, and can achieve the decision support for the evidence-informed decision making in military medical service.

D*D:Analytical Clinical Information Retrieval System based on Hospital Information System-Overview and Use Examples- / 薬剤疫学

<b>Objective:</b> Standardized clinical data are invaluable for secondary use of medical information. We constructed a standardized database and a data warehouse called D*D, based on the Standardized Structured Medical Information Exchange(SS-MIX)scheme. D*D enables physicians and researchers to perform complex searches with combined conditions, e.g. time to event. It contains data from 1999 for approximately 400,000 individual patients. The objective of this study was to provide an overview of the features of this database system, especially from the perspective of drug safety research.<br><b>Methods:</b> Three models of research questions were identified from established drug-risk combinations:1)gatifloxacin and hypoglycemia;2)statins and rhabdomyolysis;and 3)oral 5-fluorouracil S-1 and hepatotoxicity. D*D was searched using predefined keywords and conditions.<br><b>Results:</b> 1)A total of 3,635 patients were treated for diabetes. Among 20 diabetic patients prescribed gatifloxacin, hypoglycemia was recorded in one patient(1/38 prescriptions). 2)Among 5,926 patients who had been prescribed any statin within 10 years in our hospital, 6 patients(0.1%)experienced rhabdomyolysis. The incidence was similar to that for fibrate (1/740, 0.1%). The most confounded diagnosis was stiff shoulder. 3)Among 244 patients prescribed S-1, 19 patients(7.8%) experienced hepatotoxicity higher than CTCAE grade3 within 2 months from the prescription.<br><b>Conclusion:</b> With limited data items and search keys in standardized data storage, definitions of exposures and outcomes require careful assessment during protocol development. Considering that the system can be implemented at more than half of the hospitals that have already installed ordering systems, D*D can be one of the Japanese models for distributed research network.

Uso de informações de saúde para suporte à decisão: uma metodologia focada no consumidor da informação / Use of health information for decision support: a methodology focused on consumer information

O objetivo deste trabalho é apresentar os passos necessários para a construção de data marts / data warehouses como uma solução para um ambiente de suporte à decisão. Seu foco não é, entretanto, o aprofundamento de cada uma das etapas deste método (uma vez que existe uma ampla literatura sobre o assunto), mas realçar a importância do envolvimento do usuário – aqui denominado consumidor da informação – durante o processo de criação e manutenção destes data marts / data warehouses. O consumidor da informação é chamado a participar de um plano integrado com os membros das áreas detentoras do conhecimento necessário para a construção destas soluções de suporte à decisão, incluindo a área de tecnologia da informação. A disseminação das informações contidas nestes bancos de dados para os diversos tipos de consumidores da informação (com diferentes recursos de hardware, software e humanos disponíveis), e sua aplicação no controle social, também são discutidas aqui.

The purpose of this work is to present the required steps for the construction of data marts / data warehouses as a solution for a decision support environment. However, its focus is not to go deeper in each of the steps of this method (since there is a broadliterature about the subject), but to highlight the importance of the user – here called information consumer – engagement during the process of creating and maintaining these data marts / data warehouses. The information consumer is called to take part in an integrated plan together with the members of the areas who own the necessary knowledge to build these decision support solutions, including the information technology (IT) area. The spread of the informations contained in these databases to the different types of information consumers (with different hardware, software and humanresources available), and its application in social control, is also discussed here.

A Data Warehouse Based Retrospective Post-marketing Surveillance Method: A Feasibility Test with Fluoxetine / 대한의료정보학회지

OBJECTIVE: Post-marketing surveillance (PMS) is an adverse events monitoring practice of pharmaceutical drugs on the market. Traditional PMS methods are labor intensive and expensive to perform, because they are largely based on manual work including phone-calling, mailing, or direct visits to relevant subjects. The objective of this study was to develop and validate a PMS methodology based on the clinical data warehouse (CDW). METHODS: We constructed a archival DB using a hospital information system and a refined CDW from three different hospitals. Fluoxetine hydrochloride, an antidepressant, was selected as the target monitoring drug. Corrected QT prolongation on ECG was selected as the target adverse outcome. The Wilcoxon signed rank test was performed to analyze the difference in the corrected QT interval before and after the target drug administration. RESULTS: A refined CDW was successfully constructed from three different hospitals. Table specifications and an entity-relation diagram were developed and are presented. A total of 13 subjects were selected for monitoring. There was no statistically significant difference in the QT interval before and after target drug administration (p=0.727). CONCLUSION: The PMS method based on CDW was successfully performed on the target drug. This IT-based alternative surveillance method might be beneficial in the PMS environment of the future.

A DNA Microarray LIMS System for Integral Genomic Analysis of Multi-Platform Microarrays

The analysis of DNA microarray data is a rapidly evolving area of bioinformatics, and various types of microarray are emerging as some of the most exciting technologies for use in biological and clinical research. In recent years, microarray technology has been utilized in various applications such as the profiling of mRNAs, assessment of DNA copy number, genotyping, and detection of methylated sequences. However, the analysis of these heterogeneous microarray platform experiments does not need to be performed separately. Rather, these platforms can be co-analyzed in combination, for cross-validation. There are a number of separate laboratory information management systems (LIMS) that individually address some of the needs for each platform. However, to our knowledge there are no unified LIMS systems capable of organizing all of the information regarding multi-platform microarray experiments, while additionally integrating this information with tools to perform the analysis. In order to address these requirements, we developed a web-based LIMS system that provides an integrated framework for storing and analyzing microarray information generated by the various platforms. This system enables an easy integration of modules that transform, analyze and/or visualize multi-platform microarray data.

Application of Data Warehousing and Data Mining in HIS / 医疗卫生装备

Objective To discover the basic principle of hospital operation and predict the hospital developing trends through analysis of massive data involved in the hospital information system(HIS),with a view of providing better services to patients.Methods The Oracle Warehouse Builder was used as technical platform of date warehouse building in the process of modeling the HIS by using relational database and modeling the data warehouse by using the star model of the multi-dimensional database models.Data Miner,a data mining tool,is also applied to analyze information in the hospital related to inpatient structure and mobility,expenses structure,medical workload and economic benefits.Results Support was provided to management and decision making in hospital.Conclusion Wide applications of data warehousing and data mining are observed in HIS,resulting in remarkable economic and management benefits.

System Architecture of Data Integrated Warehouse Oriented to HIS / 医疗卫生装备

Objective To research and design a system of data integrated warehouse oriented to HIS. Methods The system was constructed by developing special data integrated warehouse, data integrated mart, XML(SQL) interface of script, etc. Results The anticipated result was achieved by applying the system architecture. Conclusion It is feasible to construct the system with special intelligent modular kits comprising data integrated warehouse, data integrated mart, and so on. The system is suitable for medical data mining and processing oriented to HIS.

Selection of data mart in the application of medical data warehouse to hospital / 医疗卫生装备

With the application of HIS in hospital,a great deal of data accumulate in database.It's very important to take advantage of these data for IT and managerial staffs.It is suggested that data mart be selected to process the data at the initial stage.

Design and implementation of hospital data warehouse / 医疗卫生装备

Data warehouse of Fuzhou General Hospital as the example, the basic conception and requirements of data warehouse are introduced in this paper. The design and construction of data warehouse are described from the aspects of subject determination, data preparation, model building, model evaluation and interpretation, and model application and consolidation. The main function of the data warehouse of Fuzhou General Hospital is also mentioned.