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Running head: NURSING INFORMATICS 1

Nursing Informatics

Name

Institutional Affiliation

NURSING INFORMATICS 2

Nursing Informatics

Introduction

Nurses, like other healthcare experts, need a range of information to undertake their duty

professionally as expected. It is necessary for them to have information about the specific

patient, assemblies of patients, the setting in which nurses operate, and the existing

circumstances (Sewell & Thede, 2015). Nurses apply this information for various purposes such

as communicating with others, making informed decisions, forming novel concepts through

combination, and discovering other relevant data. A more significant percentage of the data

conventionally produced and applied by nursing professionals assumes the form of an ordinary

semantic such as handwriting and speech. Natural language is essential for nurses. Despite the

fact that natural semantic allows clinical data to be obtainable by medical professionals, it

remains vastly challenging to access through applications of the computer that influence

scientific data figuratively, for instance, numerical data or programmed resolution aid

(Nibbelink, Young, Carrington, & Brewer, 2018). Such kind of applications requires data that are

encrypted in keeping with ‘standardized’ terminology systems and structures of the information.

The nursing profession has established various terminological approaches that support

diversity and complexity of the data requirements. The distinctions in the framework and subject

of the terminology approaches inhibit effective communication, sharing of information, a

combination of recording techniques, and comparing elements of healthcare statistics at a

worldwide level (Nibbelink, Young, Carrington & Brewer, 2018). There are two main types of

terminology systems: the enumerative approach and the combinatorial system. These systems

have been developed due to the need of ensuring that the systems are established to promote the

nursing activities within a multidisciplinary service. Besides, the terminology systems were

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created to make sure that the influence of the task is denoted in an accumulated healthcare

statistics.

The Enumerative and Combinatorial Systems

Enumerative phrase approaches are either presented as or are given indices through, a

constrained set of pre-organized terminologies, whereby philosophies and conceptual ideas are

modified to allow the formation of relevant clinical phrases (Hardiker, Bakken, Casey, & Hoy,

2002). Furthermore, they are systematized in a list and possibly prearranged in alphabetical order

or a hierarchical manner. Therefore, all probable phrases are overtly itemized. Parenthetically,

the North American Nursing Diagnosis Association Taxonomy I (NANDA-I) is one of the

examples of enumerative terminology systems.

Various clinical phrase techniques use combinatorial approaches to develop complicated

terminological phrases from basic concepts. For instance, the NANDA phrase previously

described can be exemplified as a combined idea involving three components: ineffectual, from a

group of judging ideas; single, (patient ideas); and managing (human reaction philosophies)

(Hardiker, Bakken, Casey, & Hoy, 2002). The Omaha System is one of the models of

combinatorial terminology methods.

NANDA Terminology System

NANDA is an enumerative terminology that focuses primarily on nursing diagnoses.

Under NANDA, nursing diagnoses represent clinical judgments about how clients or client

groups respond to health matters (Hardiker, Bakken, Casey, & Hoy, 2002). The modern version

of NANDA symbolizes 155 clinical analyses, and every single diagnosis has a pre-synchronized

expression like Ineffectual Single Handling as a label, a brief definition, describing

characteristics, and risk factors. The concise description is inscribed in an ordinary semantic

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instead of an elaborate prescribed illustration of nursing conceptual ideas and interactions.

Besides, a single clinical diagnosis is situated in an uncomplicated unifying system comprising

of nine patterns of human response (Hardiker, Bakken, Casey, & Hoy, 2002).

NANDA was created in 1982 primarily to allow identification and classification of health

issues within the domain of nursing. Currently, it consists of more than 216 published clinical

diagnoses. One of the missions of NANDA-I system is to enhance the required terminological

development, modification, distribution, and usage of standardized clinical analytic language. It

also offers the top fact-based clinical analyses for usage in the nursing profession, and it

determines interventions and results. Moreover, NANDA system is typically used with Nursing

Outcomes Classification (NOC) and Nursing Interventions Classification (NIC), commonly

known as NANDA/NIC/NOC (NNN). This scenario allows NANDA system to give more

detailed, research-oriented, uniformly categorized for clinical analyses, medical interventions

and curative- sensitive client’s results.

The Omaha Terminology System

Omaha System is a standard terminology that offers interoperability and enables

communication across the continuum of community health (Hardiker, Bakken, Casey, & Hoy,

2002). It is one of the initial clinical taxonomies to be established, and it is highly regarded since

it was developed objectively to describe community healthcare, and it can be used for scientific

research. Besides, it is highly regarded since it was designed to be used in electronic

documentation systems and has been extensively tested for reliability and validity.

The Omaha approach gives a structure for documenting materials both in home-based

and public-based health management practices. The Omaha intervention approach is structured

into intellection categories: 4 main interventions classes, 62 objectives or goals of the clinical

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activity, and patient-focused data which are produced by a professional in the field of healthcare

(Hardiker, Bakken, Casey, & Hoy, 2002). Besides, each category of the intervention has a label

and a definition inscribed in an ordinary semantic, and they look for means of providing a

consolidating framework for defining nursing activities. These classes include Case

management, Guidance and counseling, Treatments and Procedures, surveillance, and Health

Teaching.

In comparison, both the NANDA and Omaha approaches are considered equally

significant since they provide a framework for the retrieval and usage of nursing information

from a computer-based data system (Whittenburg, 2015). Similarly, they are both essential,

especially NANDA system, when evaluating statistical data. They are both globally used and are

research-based systems. However, there are some drawbacks associated with both systems. As

stated earlier, nursing practice generates numerous and comprehensive information hence a vast

amount of distinct terminologies used in nursing would be required to embody the entire

potential data. Nevertheless, NANDA system limits the number of clinical phrases due to the

constraints imposed in its development and usage. In an attempt of addressing this challenging

scenario, NANDA-I has been compelled to combine effort with NOC and NIC systems hence

forming another system referred to as NNN. On the contrary, even though Omaha system

addresses this challenge by allowing a more substantial amount of complicated concepts to be

represented, it also suffers a problem of not adhering to the rules. According to Whittenburg

(2015), the lack of regulations for identifying relevant combinations makes Omaha system

challenging to use since this situation increases the burden of searching for elements from

different lists.

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The Codification of Nursing Data in EHRs

The primary of objective of Electronic Health Record systems (EHRs) is to enhance

efficiency, promote the high-quality integration of healthcare, support independence of the place,

and time of healthcare delivery. A larger number of expected benefits from the codification of

nursing data depend mainly on the systematization of the information. It is predictable that the

implementation of information and communication technology (ICT) in managing nursing data

can lead to safer healthcare, more responsive to the needs of the patients, and increased

efficiency (O’Malley, Draper, Gourevitch, Cross, & Scholle, 2015). The range of plausible

codification of nursing data in the sector of healthcare has increased exponentially, with

remarkable progressions from the local level to national level health information exchange. The

codification of nursing data is observed to support clinical care activities, facilitates new

technologies for improving patient’s safety and quality of the healthcare. Besides, it enables

quality checking of the health service procedures and locally or nationally managing evidence-

based nursing issues by augmenting statistical data collection. Similarly, the codification of

nursing data is considered to allow easier participation of people in their healthcare activities.

Moreover, ICT is beneficial to the nursing profession since it enables codification of data

in real time for easy retrieval. Besides, coding of the nursing information makes the ordering

course more efficient since nurses do not require to inquire for more explanation or to ask for the

lost data from incomprehensible or partial clarifications (O’Malley, Draper, Gourevitch, Cross,

& Scholle, 2015). Therefore, some of the grave medical mistakes can be minimized through the

implementation of data codification. The computerized physician order entry (CPOE)

techniques enable the suppliers to order medical things such as medicines, research laboratory

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experiments, physical treatment, and radiology, using a computer instead of using papers. This

kind of computerization eradicates possible precarious medical errors instigated by poor

penmanship.

Similarly, the codification of nursing data in clinical decision support (CDS) tools assists

the provider to make well-informed decisions concerning patient care. The CDS system

provides the most recent information about medication. It also cross-references a client’s

reaction to certain drugs, as well as gives warnings for medicine relations (O’Malley, Draper,

Gourevitch, Cross, & Scholle, 2015). Moreover, the coding of nursing data in health information

exchange (HIE) enables the information about a patient to share. Through protected and actual

dissemination of health details of a patient, HIE minimizes costly redundant health checks which

are recommended since it is not possible to obtain the required medical details put in safekeeping

by other providers. Parenthetically, HIE enables sharing of patient health records through EHRs,

which ultimately give rise to a relatively economical and high-quality health care. Consequently,

there is a great need for codification of nursing data in the electronic health record system since

this is the future of nursing informatics.

Conclusion

The two terminology systems described above are considered to the formal clinical-

language approaches that symbolize new bullets against the challenges facing the current

terminological approaches. They strive for supplementing the existing systems, improve their

efficacy and make them have the initiative of becoming a more principled organization. In

general, the formal terminological approaches embody an innovative model for developing

languages used by nurses. These formal approaches do not attempt to standardize clinical phrases

rather they try to formalize the phrases used in the nursing profession. Moreover, with

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recognized systems of terminology, it will allow the data that the nurses record to be fully

utilized and to create practiced-based clinical information. Considerably, it will enable

progression of nursing informatics to a level where innovative submissions, for instance, a

completely computer-oriented client record can be developed. Therefore, these systems are

means of fulfilling conceivable prospects for nursing informatics and the nursing activities in

general.

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References

Hardiker, N. R., Bakken, S., Casey, A., & Hoy, D. (2002). Formal nursing terminology systems:

a means to an end. Journal of biomedical informatics, 35(5-6), 298-305.

Whittenburg, L. (2015). Use of standard terminologies in healthcare It. Mastering Informatics: A

Heatlhcare Handbook for Success, 253.

O’Malley, A. S., Draper, K., Gourevitch, R., Cross, D. A., & Scholle, S. H. (2015). Electronic

health records and support for primary care teamwork. Journal of the American Medical

Informatics Association, 22(2), 426-434.

Sewell, J., & Thede, L. Q. (2015). Informatics and nursing: opportunities and challenges.

Lippincott Williams & Wilkins.

Nibbelink, C. W., Young, J. R., Carrington, J. M., & Brewer, B. B. (2018). Informatics Solutions

for Application of Decision-Making Skills. Critical care nursing clinics of North

America.

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