The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Background: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine

Web-enabled Data Warehouse and Data Webhouse

In this paper, our objectives are to understanding what data warehouse means examine the reasons for doing so, appreciate the implications of the convergence of Web technologies and those of the data warehouse and examine the steps for building a Web-enabled data warehouse. The web revolution has propelled the data warehouse out onto the main stage, because in many situations the data warehouse must be the engine that controls or analysis the web experience. In order to step up to this new responsibility, the data warehouse must adjust. The nature of the data warehouse needs to be somewhat different. As a result, our data warehouses are becoming data webhouses. The data warehouse is becoming the infrastructure that supports customer relationship management (CRM). And the data warehouse is being asked to make the customer clickstream available for analysis. This rebirth of data warehousing architecture is called the data webhouse.data warehouse, web-enabled, data mart, Internet, intranet, extranet

Database Vs Data Warehouse

Data warehouse technology includes a set of concepts and methods that offer the users useful information for decision making. The necessity to build a data warehouse arises from the necessity to improve the quality of information in the organization. The date proceeding from different sources, having a variety of forms - both structured and unstructured, are filtered according to business rules and are integrated in a single large data collection. Using informatics solutions, managers have understood that data stored in operational systems - including databases, are an informational gold mine that must be exploited. Data warehouses have been developed to answer the increasing demands for complex analysis, which could not be properly achieved with operational databases. The present paper emphasizes some of the criteria that information application developers can use in order to choose between a database solution or a data warehouse one.data warehouse, database, database management systems, information systems, data organisation in externe memory, business intelligence

Radio frequency identification (RFID) technologies for locating warehouse resources: A conceptual framework

Copyright @ 2012 Information Technology SocietyIn the supply chain, a warehouse is a crucial component for linking all chain parties. It is necessary to track the real time resource location and status to support warehouse operations effectively. Therefore, RFID technology has been adopted to facilitate the collection and sharing of data in a warehouse environment. However, an essential decision should be made on the type of RFID tags the warehouse managers should adopt, because it is very important to implement RFID tags that work in warehouse environment. As a result, the warehouse resources will be easily tracked and accurately located which will improve the visibility of warehouse operations, enhance the productivity and reduce the operation costs of the warehouse. Therefore, it is crucial to evaluate the reading performance of all types of RFID tags in a warehouse environment in order to choose the most appropriate RFID tags which will enhance the operational efficiency of a warehouse. Reading performance of active and passive RFID tags have been evaluated before while, semi-passive RFID tag, which is battery-assisted with greater sensitivity than passive tags and cheaper than active tags, has not been examined yet in a warehouse environment. This research is in- progress research and it seeks to (i) provide a general overview of the existing real-time data management techniques in tracking warehouse resources location, (ii) provide an overall conceptual framework that can help warehouse managers to choose the best RFID technologies for a warehouse environment, (iii) Finally, the paper submits an experiment design for evaluating the reading performance of semi-passive RFID tags in a warehouse environment