Patient Keeper Data Repository - Assignment Example

?Brochure and Data Repository Patient Keeper Data Repository Data Repository The patient keeper data repository is a data replicateddata from hospital information system and high performance downtime support. Direct integration and or HL-feeds helps in the aggregation of data repository especially in relaying information from multiple hospital systems. Other than delivering patient keeper applications, the data repository also allows a configuration that offers business continuity solutions for the downtime support. Patient Keeper Business Continuity This system helps in a situation that the core information systems go down either planned or unplanned. The Patient-Keeper Business Continuity will serve as a secondary access point for physicians and other hospital/clinical staff thereby keeping the hospital running. The system also supports web portal and other mobile devices; thus, enabling the clinicians accessing current information as would be in the case of downtime. Data captured from new patients during downtime using this application are automatically synchronized into the main system once they are set up. Key Features of Data Repository The backbend systems in the form of abstract application data HIS domains and multiple hospital systems aggregated data Complete patients’ information with historical data loader Purges and achieves data defined or based on parameters Benefits Lower costs for upgrading or changing HIS since there is no need of retaining physicians There is room for adding hundreds or thousands of portal users without interfering with HIS load It reduces IT costs for continuity especially during HIS downtime Helps in accessing, integrating, and solving challenges in hospitals and health care systems It performs it's intended services without replacing the existing systems It acts on the top layer in the help formation systems thereby providing simple, rich, and timely information to both patients and health care providers. Health care systems and patient can collect data concerning Patient Keeper Data Repository since they can use the same data: To analyze the system across time periods Adopt variance analysis across different scenarios Drill down into the collected data towards understanding the system Use that data for real time consolidation across varied entities Database A database is a term referring to a collection of information that are organized in an effective and effective way to allow computer programs to be selected easily according to the desired data pieces. Therefore, the database can be regarded as an electronic filing system. Traditionally, databases are often organized according to fields, records, and files. Database files are single pieces of information wile records are complete sets of fields that are contained in a collection referred to files (Kroenke, 2012). For instance, files analogously are related to telephone books that contain a list of records each of which is defined under three main fields including name, address, and the telephone number. The information in the database is usually accessed through the database management system (Kroenke, 2012). The database management system is a collection of programs that facilitate feeding, organizing, and selecting data from the database. Primary Key is a relational table that identifies each record in the database system uniquely. The Primary Key can be either a normal attribute that has unique features such the table’s social number security, or the DBMS can generate the Primary Key through globally unique identifiers. It should be noted that the primary key has a single or multiple unique attributes that are combined as a unit. The vital features of primary keys are that it must contain a unique value to each data row and it can never contain a null value (Kroenke, 2012). The foreign key is a group of columns within a relational database table. Notably, the foreign key links between any two data in two different tables. Therefore, it acts as a cross reference between these tables since it refers to a primary key of another table; hence, generating a link between involved tables. Many tables in the relational database systems often apply the use of the foreign key concepts (Kroenke, 2012). Additionally, for complex databases including the data warehouse, data in the domain must be added to the multiple tables to maintain the relationship developed with the foreign key concept. Metadata is an ambiguous term since it may be applied to define two different concepts. However, when expressed in database management, the term simply means data about data. The ideals behind about metadata is that metadata focuses on the information representation especially information from the source where the information in question is non-digital material. Nonetheless, such information may be textual or non-textual; therefore, such information can be from web pages, books, images, and video recordings (Kroenke, 2012). Notably, the metadata provided by information professionals often defined these types of information sources; therefore, metadata is the data about data or information about the data or the definition of the data source. Functions of Data Warehouses In most cases, collection of data often facilitates and support data design management towards decision-making. Therefore, since data warehouse is a collection of data that support decision-making processes. The data warehouses contain a variety of data that are usually presented in a coherent business picture at a single point in time (Kroenke, 2012). The data warehouse within the warehousing architecture used in integrating corporate data. It is an effective means of decision-making since it contains a single version of truth. The data warehouse contains massive data; thus, it is apparent that it is used as data storage. Moreover, since it contains records of the organization that are related to the management interest dimensions, the data warehouse allows data dice and slice thereby allowing summing and grouping of data immensely. Finally, it should be noted that the data warehouse often helps in improving analysis and reporting ability of data thereby providing asset managers with a single and quick view of the customers’ portfolio. Data Mart is a data warehouse subset. It is usually similar to the data warehouse; however, its scope and purpose is often aligned to one function, department, or business unit. Additionally, it is defined as a single aggregation to the domain used in reporting, analysis, and supporting decisions. A single subset or domain of data mart could be related to being a customer or supplier (Kroenke, 2012). Notably, a data mart can be extracted or be fed in a data warehouse. Differences between Unsupervised and Supervised Data Mining The unsupervised mining data are a model that provides correct results during training while supervised data mining is the data training that includes input and desired results. The unsupervised data mining can be clustered into the statistical properties of data while for the supervised data mining needs correct results from the model to be used is already defined (Kroenke, 2012). Additionally, unsupervised data mining needs significant labeling and clustering while supervised data mining calls for fast and accurate methods in its application. Reference Kroenke, D. (2012). Using MIS. Upper Saddle River, N.J: Prentice Hall. Read More