Data, Knowledge, Information and Wisdom Continuum

The Data/Information/Knowledge/Wisdom Continuum The Data/Information/Knowledge/Wisdom Continuum Data, information, and knowledge are words used to assign meaning to our complex nursing work. In the field of information technology, these words are used to give meaning and direct the flow of organizational knowledge (Thompson & Warren, 2009). The concept of the data-information-knowledge-wisdom (DIKW) continuum is the transformation of data into wisdom through cognitive processes, which are supportive of the nursing practice.

Schleyer and Beaudry (2009) discussed how nurses in this growing specialty are accountable to provide the best evidence-based care advice possible, transform the data collected to information, and apply that knowledge with wisdom to address the patient’s unique needs. The purpose of this paper is to display the progression through the four steps of the data, information, knowledge, wisdom continuum that occurs through research information to answer a clinical question pertinent to nursing in an acute care setting. Electronic Medication Administration in Acute Care Setting

Implementation of the electronic health record, computerized physicians order entry and decision support systems within the health care industry have attributed to a decrease in documentation and transcription errors, while making measurable improvements in our nation’s health care. The clinical research question for this paper is; has implementing the use of the electronic medication administration (eMAR) improved the safety of medication administration in the hospital setting? This technology at present has not been implemented in our hospital organization, but will be in the near future.

Poon et al. (2010) explained that serious medication errors are common in hospitals and often occur during the transcription or administration of medication. In order to help prevent such errors, the development of technology has been instituted to verify medications by incorporating barcode verification technology within an electronic medication-administration system, which is referred to as bar code medication administration (BCMA). Database Resources Ackoff (1989) proposed that data are defined as symbols that represent properties of objects, events and their environment.

They are the products of observation, and are of no use until they are in a useable (i. e. relevant) form (as cited in Rowley, 2007). For this paper, the Walden Library Health Science and Nursing Databases were utilized to conduct a search for data related to the clinical question “has implementing the use of the electronic medication administration (eMAR) improved the safety of medication administration in the hospital setting? ” The databases for CINHAL/Medline and PUBMED were queried by using the search words eMAR, bar code technology, medication administration, and safety.

The search generated four complete articles in the CINHAL/Medline databases that were pertinent to the topic. Another four sources were generated in the PUBMED database, of which one was a free text article, the other three sources were abstracts; however, two of those sources were successfully retrieved from Google Scholar (find in Walden Library). Although, no full text was available for one of the abstracts found for this source in the search, the information within the abstract was deemed relevant. Transforming Data into Information

Information is inferred from data (Rowley, 2007). Upon evaluating the plethora of data from said resources, it was determined that a substantial amount of relevant information could be extracted from this accumulation of data to support the clinical question in progress. In other words, said data would be considered information, as it had context to the reason the literature search was being performed. Medication errors cause an estimated 7000 deaths each year and cost the nation $2 billion annually (Paoletti, Suess, Lesko, Feroli, Kennel, Mahler, & Sauders, 2007).

A significant reduction of medication errors was evidenced by the use of bar code technology and the eMAR. A study funded by the Agency for Healthcare Research and Quality (Healthcare Benchmark & Quality Improvements, 2010) reported that by incorporating bar-code verification technology within an eMAR system, a significant reduction in medication errors was demonstrated. Connecting Information to Knowledge According to (Thompson & Warren, 2009) knowledge occurs when we apply the data and information to obtain relevant and purposeful meaning.

The transformation of information to knowledge occurs when information is combined so that connections can be identified and formalized if you will. Some methods used to achieve this transformation would be through comparison. How does this information compare to other known data? Example: Were there fewer transcription and medication errors with the use of eMAR and bar code technology as opposed to paper documentation and administration? Another method would be through making associations or connections. Example: How does the use of eMAR with bar-code technology relate to reduced transcription and medication errors?

There was a significant amount of information gleaned from database resources that supported the conclusion, that implementation of such technology could greatly reduce transcription and medication administration errors, as well as adverse drug events, although it did not propose to eliminate such errors. Wisdom Pertaining to Knowledge Can the use of information technology be utilized to gain wisdom? Achieving wisdom via the application of knowledge to manage and solve human problems is essential for health.

Major (2002) discussed how wisdom involves recognizing what is most important, by making distinctions among alternatives. It comprises the application of experience, intelligence, creativity, and knowledge, as mediated by values, toward the achievement of a common good (as cited in Matney et al. 2011). It would be a reasonable assertion that clinicians and researchers may conclude that information and knowledge derived from this data will be accurate and can reliably support research, clinical nursing practice, and nursing decisions. Summary

In that nurses are knowledge workers, it is only natural that they would require a fundamental knowledge to support their practice and profession. As knowledge workers, nurses collect data and information and make decisions that affect individuals, families, and communities at large. An understanding of how the concepts of the data-information-knowledge-wisdom (DIKW) framework overlap and interact will beneficial for nurses performing research studies. Given that wisdom is supported by knowledge, different manifestations of wisdom may exist.

Wisdom may be manifested in nursing through “professional expertise”(Baltez & Staudinger, 2000) or “clinical judgment” (Benner, 2000), (as cited in Mateny et al. 2011). References Healthcare Benchmarks & Quality Improvements (2010). Bar-code/eMAR combo reduces errors. Healthcare Benchmarks & Quality improvements, 17(9), 100-102. Matney, S. , Brewster, P. J. , Sward, K. A. , Cloyes, K G. , & Staggers, N. (2011). Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework.

Advances in Nursing Science, 34(1), 6-18. DOI: 10. 1097/ANS. 0b013e3182071813 Paoletti, R. D. , Suess, T. M. , Lesko, M. G. , Feroli, A. A. , Kennel, J. A. , Mahler, J. M. & Sauders, T. (2007). Using bar-code technology and medication observation methodology for safer medication administration. American Journal of Health System Pharmacy, 64,(5), 536-543. Poon, E. G. , Keohane, C. A. , Yoon, C. S. , Ditmore, M. , Bane, A. , Levtzion-Korach, O. , … Gahdhi, T. K. (2010). Effect of bar-code technology on the safety of medication administration.

The New England Journal of Medicine, 362, 1698-1707. DOI: 10. 1056/NEJMsa0907115 Rowley, J. (2007). The wisdom hierarchy: Representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163-180. DOI: 10. 1177/0165551506070706 Schleyer, R. , & Beaudry, S. (2009). Data to wisdom: Informatics in telephone triage nursing practice. AAACN Viewpoint, 31(5), 1, 10-3. Thompson, T. L. , & Warren, J. J. (2009). Are they all data? Understanding the work of organizational knowledge. Clinical Nurse Specialist, 23(4), 185-186. DOI: 10. 1097/NUR. 0b013e3181aae374