A data dictionary alludes to a super catalog which provides, for each element of the field of data, a list of information that describes the field, the origin of the data, rules or edits which are applicable to the field, width, and type of field, description of used codes, what applications uses that particular data element, etc. This centralized repository, which is a collection of databases from a multitude of sources within an organization that are integrated into a singular database to allow for a holistic view of the data, gives meaning, relationships to other data, origin, utilization, as well as formatting (Hermann, 2018). Data dictionaries are essential tools that provide the communication structures in a manner that operational and technical teams are capable of easily meeting the daily operational requirements of the organization as it enables the different systems to share and transmit information via standardized definition and data mapping in a manner that is streamlined. According to Biederman and Dolezel (2017), data dictionaries are tools that provide data about data. They are thus critical data systems, especially for healthcare organizations, because they provide crucial information in a structured manner in a bid to align all the users of the organization, and they should thus be incorporated into the health system, especially in enabling organizational efficiencies.
The table below is an example of a data dictionary that simulates a Patient Index for dataset visualization.
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| Table | Field | Type | Format | Length | Description |
| Patient | |||||
| Patient Last Name | Text | 25 Characters | Last Name | ||
| Patient First Name | Text | 25 Characters | First Name | ||
| Middle Initial | Text | 1 Character | Middle Initial | ||
| Gender | Drop Down | 0 (U), (M), 2 (F) | 1 Character | Patient’s Sex | |
| MRN | Numeric | XXXXXXXXXX | 10 Characters | Medical record number to signify the unique identifier of the patient. |
Table 1 . Sample Data Dictionary
Data standards within the healthcare context are principal components of informatics that are necessary for the flow of information via the national health information infrastructure. With standards, clinical as well as patient safety systems are capable of sharing an integrated information infrastructure where the data are collected and reutilized for a plethora of purposes to efficiently satisfy the scope of data collection and reporting requirements. The data standards also support the effectual assimilation of novel knowledge into tools for decision making, such as alerts on new contraindications on drugs and refinement of the process of care. One of the data federal standards is the Health Level Seven (HL7) version 2.x (Erickson et al., 2004). It is the primary data exchange standard for clinical messaging, which is adopted by 90% of large hospitals. Therefore, data dictionaries and data sets that conform to such federal standards help the hospital in maintaining compliance with government standards.
Some of the common issues associated with the implementation of data dictionaries are that they are often difficult to use, especially for non-technical users within the healthcare context. The staff members of the organization should be trained effectively in order to use data dictionaries and ensure that the organization is using them in the proper manner. Another issue is that data the costs of the data dictionaries are very high as it entails initial build and hardware change in conjunction with the maintenance costs. Organizations should thus provide adequate investments in such infrastructure in order to reap its full benefits.
Conclusively, data dictionaries are crucial elements of data management systems as they help in the management of data and information within an organization. With data dictionaries, organizations will be capable of streamlining their operational requirements as operational and technical teams can operate effectively. However, data dictionaries should follow certain governmental standards to ensure that the organization is compliant. My recommendations are that the organization should incorporate data dictionaries as part of the hospital data management systems, and thus the necessary investments in terms of hardware and software should be set in place in order to implement it.
References
Biederman, S., & Dolezel, D. (2017). Introduction to Healthcare Informatics. American Health Information Management Association.
Erickson, S. M., Wolcott, J., Corrigan, J. M., & Aspden, P. (Eds.). (2003). Patient Safety: Achieving A New Standard for Care.
Hermann, M. (2018). What is a Data Dictionary? Retrieved 31 May 2021, from https://journal.ahima.org/what-is-a-data-dictionary/#:~:text=Keep%20up%20with%20the%20latest,information%20management%20challenges%20in%20healthcare.&text=A%20data%20dictionary%20enables%20different,mapping%20in%20a%20streamlined%20approach.
