it essay unit 2 - Standardized Healthcare Data Set Unit II...

In the 1960s medical institutions began to use computers to process large amounts of data that could not be handled manually and the concept of standardization became widely recognized over the past decade. The establishment of the National Health Information Network (NHIN) will improve patient care, improve safety, and support clinical and administrative decisions. In order to effectively share health information, computers need to understand each other. In other words, you need to share data standards to effectively exchange electronic health records with other computer systems. To realize the many functions required for interoperability, various types of standards are required. With standardized data elements and definitions, you can compare the data collected at various facilities. For example, if data is standardized, the term "hospitalization" is used in urban hospitals just like university hospitals. Since both hospitals are defined in the same way, we can compare as follows. Enrollment rate and occupancy rate

Through healthcare data collection and data processing, investigate common standards related to electronic medical records and other medical technologies. We introduce the data mining method and collected data set. In addition to programming languages, other input / output topics, data types, object models, HL 7, SQL, interoperability students review the concepts of system design and programming languages ​​along with health care applications. Prerequisites: HPRS 101, HIMT 201

Health care analysis is based on data, especially datasets. Health management data sets include large amounts of medical data collected from various medical data sources, various measurements, financial data, statistical data, demographic data, and insurance data for a particular population. Due to the diversity of medical data sources, standardization of data is an important pillar of collaboration between effective and meaningful use of information and medical professionals, health care providers, insurance companies and government agencies.

Medical analysis is based on data and data sets, including medical, genetic, demographic, mono Internet, financial, and insurance information collected from multiple databases. Due to the diversity of these sources, standardization of data is the key to the effective and meaningful use of information, which cooperates between medical professionals, healthcare providers, patients, insurance companies and government agencies It improves. Nonetheless, these centralized databases have proved to be fragile and expensive and can not provide comprehensive insight needed for individualized safe and effective care. Therefore, Distributed Ledger Technology (DLT) and the most important block chain can provide a safe, invariant and distributed alternative for sharing and trading data (see below).