Advantages of Using RxNorm in the Healthcare Sector

Different commercial drug information systems adopt different naming conventions. Even within an organization, the departments might have information systems with varying nomenclature. Therefore, in such cases, the electronic exchange of information becomes difficult. Lives of patients were at risk due to the difficulties in sharing medical information between associated departments. Therefore, the National Library of Medicine (NLM) developed this naming system, which is currently employed to share and exchange data efficiently. More specifically, it is used in the electronic exchange of clinical health information. RxNorm offers criteria for linking standard names of drugs used in clinical settings to various drug vocabularies that are utilize in some health care facilities, such as in pharmacy management (Liu, Ma, Moore, Ganesan & Nelson, 2005). According to Liu et al. (2005), RxNorm is also used in drug interaction software. The linkage facilitates the operation of computerized systems that are designed to store or process data related to clinical drugs. 

Data Representation 

The naming system represents the name of drugs in the form that both the clinician and the pharmacist would understand. In the naming system, a clinical drug’s designation is in a meaningful and logical form that shows its ingredients, strength, and the actual state in which it will be issued (Liu et al., 2005). In the event that the elements vary, the drugs adopt a different naming designation in the nomenclature. Therefore, the naming system incorporates a designation for each dose and strength of each possible concoction of clinically relevant components. 

Concepts 

Data in the naming system is grouped into concepts. In this context, a concept refers to group of names having similar denotation at a particular level of conceptualization. Through concepts, the naming system can rearrange a string of characteristics from different origins as similar. When a name deviates from the standard naming system, RxNorm will assign a RxNorm concept unique identifier (RXCUI) to the designation (Liu et al., 2005). Drugs with similar RXCUI are considered to be the same drug, with the same ingredient, strength, and dose form. On the other hand, drugs with varying ingredients, dose form, and strength are considered to be different with different RXCUI. The naming system employs a standard naming convention to normalize clinical drugs represented in different lexicons. The standardized form of the medication incorporates several components, with each and every one defined by the value of the term type (TTY). The primary term types are: ingredient (IN), dose form (DF), semantic clinical medication component (SCDC), semantic clinical medication (SCD), and semantic branded drug (SBD), among others. 

Relationship 

There are multiple relationships between RxNorm concepts. The combination of conceptualization and relationships create a meaningful and logical network. The connection amongst various abstractions is reciprocal. In other words, a medical drug would have constituents while the elements constitute the medical drug. Therefore, if an abstraction has a term type field worth of semantic clinical drug (SCD,), it will bear the connection “consists of” to different components with a term type worth of semantic clinical drug component (SCDC). Other relationship used by RxNorm include (Liu et al., 2005): 

Dose_form_of 

Ingredient_of 

Contains 

form_of 

RxNorm Data Life Cycle 

RxNorm data life cycle has four major steps, namely inversion, insertion, editing, and production. Inversion involves the conversion of the origin provider files from their original form to RxNorm standard configuration. Once the files are received from the source provider, they are run through programs to create a Rich Release Format (RRF) which is compatible with RxNorm. The following stage is insertion and the inverted RRF information files are loaded in the naming system database. After files have been loaded into the naming system database, editing process starts. The third stage in the RxNorm data life cycle is editing. The editing process involves resolving any existing disagreements between an origin’s naming system and the nomenclature, RxNorm (Liu et al., 2005). The editing process is conducted by a human. The human editor has the responsibility of incorporating all the various origin provider opinions into a standard format as per the requirement of RxNorm. The editors are required to analyze the lists of concepts and resolve any issues causing these conflicts. Production, which is the final step, is an automated process that involves the extraction of releasable data from the RxNorm database (Liu et al., 2005). The extracted data is then produced and validated. The validated data can then be downloaded by the end-users. 

RxNorm Framework 

The National Library of Medicine developed a RxNorm framework, which is a support structure upon which other Java elements and the RxNorm governing regulations were built. The framework has RxNorm classes that have close relations regarding functionality and details, which create an autonomous product that can be reused (Liu et al., 2005). The framework adopts a layered architecture. Different RxNorm elements rely on application logical layer, which is also dependent on the persistence layer. The persistence stratum carries information access articles. The RxNorm business objects stand for tangible entities within the system that users create, accesses, and manipulates during the RxNorm data life cycle (Liu et al., 2005). The different business objects interact with each other to achieve various functionalities. The primary functions of the persistence layer in the software system can be defined by the CRUD. CRUD represents the primary function of the database (Liu et al., 2005). The RxNorm data access objects (DAO) implement the access procedures needed to operate the RxNorm system. The data access objects link the components and the data origin. 

The naming system factory layer develops the naming system’s factory articles during the operation time. The role of the layer is to protect the formation of objects from their usefulness. The factory layer carries out the accomplishment of the abstract factory design and their factory method pattern (Bennett, 2012). Other elements of the framework include the RxNorm cache and the RxNorm utilities. While the cache offers immediate entry to the system’s constant data, the RxNorm utilities offer utility methods. 

RxNorm Components 

RxNorm has multiple elements created around the database structure. Each component has particular roles and follows a precise layered design. The primary components of the RxNorm naming system include the RxNorm app, RxNorm Web, and the naming system Release generator. The naming system Web is developed and applied in Model-View-Controller program design that differentiates a program’s model users’ interface and logical regulation into three different sub-elements (Liu et al., 2005). The incorporation of three subcomponents is meant to facilitate easy modification that would not interrupt the information model element. The RxNorm app, on the other hand, offers entity bean to manage the complex persistent data for RxNorm end users. RxNorm Release Generator produces files for RxNorm in RRF format. 

RxNorm is set to become an important tool used as a foundation for a quick-capture treatment history technique. The naming system, if effectively implemented, can become an important information structure for real computing programs in the healthcare sector. The advantages of adopting the RxNorm in the medical industry can be analyzed under a four-factor framework, namely (Peters et al., 2008): 

Flexibility: The ability of RxNorm to handle multiple language formats makes it a suitable system that can handle different scenarios that may occur in real-word. 

Speed: The operation from the first step of the data life cycle to the fourth step happens very first. The end-users will not notice the steps. The high speed of conversion facilitates easier and a more effective electronic exchange of clinical information. 

Data Integrity: The naming system data offers top-notch and reliable information with steady mapping back to the source provider. Therefore, in case of any issue, one can track the flow of data throughout the entire process to identify any problem. 

Coverage: In the future, RxNorm is expected to cover every commonly prescribed medication. 

Future Research on RxNorm 

Currently, the editing stage of the RxNorm data life cycle involves humans. However, in the future, the RxNorm editing system can be expanded to provide data editors with better methodologies for processing data in the database. The new data from provider source ought to be inserted, edited, and passed through quality assurance before being shared to the end-user. Therefore, the process of standardizing the nomenclature should be quick and accurate. The emending subsystem should, therefore, allow editors to build and adjust the semantic normal form (SNF) for existent information efficient to produce information every few days. Therefore, future research should focus on the databases and prepare usable, accurate and easily accessible data. 

Conclusion 

Various departments in the healthcare sector use varied information systems with the different naming format. However, given the nature of service delivery in the sector, there needs to be a smooth communication between these departments. However, the different naming systems makes it difficult to share information between these departments. Therefore, RxNorm is meant to facilitate easy electronic sharing of clinical files. The RxNorm groups represent clinical drugs in a semantic normal form, which employs a drug’s ingredient, strength, physical form to name drugs and group them into concepts. RxNorm app, RxNorm Web, and RxNorm release generator facilitate the process of converting the drug vocabularies to a standardized nomenclature that can be understood by both clinicians and pharmacists. If effectively adopted, the RxNorm database can improve service delivery in the healthcare sector. Besides, in the future, the naming system is expected to be employed in all US federal government systems for sharing medical health data. 

References 

Bennett, C. C. (2012). Utilizing RxNorm to support practical computing applications: capturing medication history in live electronic health records.  Journal of biomedical informatics ,  45 (4), 634-641. 

Liu, S., Ma, W., Moore, R., Ganesan, V., & Nelson, S. (2005). RxNorm: prescription for electronic drug information exchange.  IT professional ,  7 (5), 17-23. 

Peters, L., & Bodenreider, O. (2008). Using the RxNorm web services API for quality assurance purposes. In  AMIA Annual Symposium Proceedings  (Vol. 2008, p. 591). American Medical Informatics Association.