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Book/movie review
22/08/2022
The concept for a total electronic information system for healthcare delivery may appear to be simple, but digging deeper the design, implementation, and maintenance of such systems are extremely complex. Healthcare delivery depends on an intricate network of CIS applications that provide direct support for caregivers in providing delivery and monitoring of patient care.
But clinical applications by themselves do not make up the entirety of an electronic healthcare information system. As this chapter shows, administrative applications are equally as important in supporting the composite of healthcare delivery services.
This chapter presents a high level overview of just a few of the clinical and administrative applications that normally constitute a total electronic information system and demonstrates the synergy between these.
Chapter 4 provides an overview of health information practice in a digital environment. The EIM team identified distinctions between practices for paper-based records management and those that are essential for digital records. The contemporary model of HIM practice is based on supporting the interrelated needs for information content and capabilities of technology to support people and the processes they perform. Data are a fundamental business asset. To realize the benefits of this resource, data must be managed in a similar way as other organizational assets.
The contemporary model recognizes the organic nature and management of the data life cycle. The foundation of the data life cycle consists of identifying and understanding the data needs of the enterprise. Similar to a living organism, data goes through a series of successive steps or phases. This includes an inventory of current data resources, including policies, procedures, and technologies and the evaluation of these to determine gaps with organization needs and planning to meet these needs. Data are captured, processed transformed, stored, used and reused, maintained and finally archived. One purpose of an EIM program is to have in place policies, standards, and procedures that address data integration, quality and access issues throughout the data life cycle.
The contemporary cohort of domains incorporated into an EIM program include: data life cycle management, data architecture management, metadata management, master data management, content and document management, data security management, business intelligence, data quality management, terminology and classification management with data governance functioning as the overarching authority for enterprise data policy and standards and coordination of all EIM domains.
There is neither one organizational EIM program structure nor any one approach for implementation. The organizational structure, scope, and resources needed for a successful EIM program depend upon the vision, mission, and goals of the EIM program, which will vary among organizations.
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