Advanced Health Informatics

Advanced Health Informatics

Data dictionary’s usefulness is apparent when several definitions are given out of one word by many users within the same healthcare organization and across different health care organizations. It is usually hard during the construction of steady and accurate records of patients that are shared through organizations, without any data dictionary. The Center for Interoperable EHR (CiEHR) developed the Clinical Data Dictionary (CiDD), to be the central source of information on data including meanings, set-ups, names, type, sources, relationships, and ranges of values for every data element. Data dictionaries help in mapping local terminologies with standardized terminologies in health care institutions. As such, it was developed to be used in the information systems of hospitals.

The data dictionary can be defined to be a set of information describing the kind of data to be gathered in a specific database, format, its structure, and how the data is used as well. About this, the health care data dictionary is a functioning element with rules in which databases abide by. Databases produce information that abides by the same rules providing rise to semantics interoperability (Sukumar, Natarajan & Ferrell, 2015). Lists of definition, data elements, and names needed to be captured in the system, are provided by the data dictionary. Additionally, it incorporates metadata and additional elements concerning each of the elements which help in the organization of data at its primary level. During the organization of information collected, the data dictionary is essential in distilling large volumes of data.

Wager, Lee & Glaser, (2017) assert that the data dictionary has 155 value sets, 162,050 concepts, and over 400,000 terms with their definitions, procedures, and clinical findings of many diseases. About 160,000 of the concepts were developed by the National Health Information Task Force Team, all of the containing classification of diseases and their clinical modifications. The data dictionary was designed to enable the provision of a common healthcare coverage language to be used in indexed clinical data, which are also retrieved, aggregated, and stored across healthcare sites and other specialties. It was developed to be used in medical records that are electronic, variability reduction of the way data is captured and research.

Successful data dictionaries help in improving the dependability and reliability of data in an organization. They also reduce redundancy, make it easier to analyze data, improving control and documentation, and use the analyzed data in making evidence-based care decisions common to organizations with accountable care in advance. This is done by the production of clean data that prevents multiple entries, duplication, identifying each entry field, and assigning the specific color-coded and user rights according to the references provided.

Data dictionary delivers innovative consulting and software services that are designed to raise the bar for clinical improvement (Sukumar, Natarajan & Ferrell, 2015). These innovations help in documentation of mobile physician applications; computer-assisted coding, quality outcomes, and case mix reporting as well as management of documents. It supports these by supporting the accuracy and expansion of electronic health record (EHR) system in hospitals. It also provides health care services and products that help professionals improve their deliveries, services, and outcomes of medical care to patients, especially during drug delivery and any health care information needed. The data dictionary is more dependent on metadata which describes all the underlying data structures and the related attributes in advance.

In conclusion, the data dictionary is a set of information that describes the kind of data gathered from databases, their formats, structures, and their importance. It is an essential tool, especially in hospitals, since it provides lists of data elements, names, and definitions. They also include metadata which organizes the data at their ground level and distilling large amounts of information for their purposes. It increases as the availability of information from increased use of EHR, which enable databases in healthcare institutions to be reliable and dependable. Therefore, Data dictionary is essential for the use of an EHR to provide that in advance for the use in health organizations.



































Sukumar, S. R., Natarajan, R., & Ferrell, R. K. (2015). Quality of Big Data in health care.International journal of health care quality assurance, 28(6), 621-634.

Wager, K. A., Lee, F. W., & Glaser, J. P. (2017). Health care information systems: a practical

approach for health care management. John Wiley & Sons.

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