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.

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.

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.

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.