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The Relationship of Data, Information, Knowledge, and Wisdom and Automated Systems: version 2.

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The Relationship of Data, Information, Knowledge, and Wisdom and Automated Systems: version 2.

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(Nelson's Model)

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How Nursing Informatics (NI) uses Data and Knowledge.

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How Nursing Informatics (NI) uses Data and Knowledge.

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relationship between information and data

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The Future of Technology

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Scopes of Practice NI according to the ANA

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Patient Safety and Quality Improvement of Outcomes.

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Patient Safety and Quality Improvement of Outcomes.

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Improving health outcomes with big data | Ronda Hughes | TEDxUofSC

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Organize appropriate interventions and training programs with the assistance of informatics specialists to improve nurses’ NI competency particularly in the field of information management skills (Homeyer et al., 2018).

Identify and describe specific attribute of Quality Data to integrate into the nursing Informatic education and practice.

Incorporate more reflective practices  "learn by doing" throughout the training of  informatics specialist.

Although the ANA is furthering the scope of practice for NIs, further recommendations they may consider include promoting deeper interprofessional collaboration within the varied health care fields to produce holistic technology and data that meets the patient’s health needs as a whole. Flynn and Stevenson (2018) discuss the importance of pharmacists working with patients and across the spectrum of healthcare workers to enhance safety and precautionary measures to prevent avoidable medication errors and interactions; this should be a priority standard for the entire health care team.

·Another consideration would be recognizing that the rapid changing technology and equipment can be overwhelming to those having to move quickly from using the old version to being proficient with the new. The ANA should have at least one task force, and possibly even regional task forces, to monitor policies and standards of operation (SOP) so that antiquated terminology and practices are properly updated and communicated with the nursing industry. Pimental Reis et al. (2020) performed a study in which they looked at how outdated SOPs, and the knowledge and training on the equipment for certain nursing procedures, affected the nursing practice and standardization of care provided.

·Also, the ANA should consider spearheading communications for nurses to be change agents and embrace changes in HIT, assist in funding campaigns that encourage patients to embrace changes in HIT, and introducing research that increases the knowledge on how to get results for better health and improved safety for patient care by using both proposals. Crush (2018) writes about technology use in accordance with Britain’s National Health Service and discusses the need for clinicians and patients to be willing and able to use the technology that will ultimately provide the best health outcomes.

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1.) What is the role of nursing informatics in data management?

2.) What would you recommended in your practice to ensure data quality? What recommendations would you make for improvement?

3.) Has the Technology Acceptance Model been previously introduced into your practice? What is your opinion regarding the model’s concepts?

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American Association of Colleges of Nursing. (2012). Graduate- level QSEN competencies knowledge, skills and attitudes. https://www.aacnnursing.org/Portals/42/AcademicNursing/CurriculumGuidelines/Graduate-QSEN-Competencies.pdf

American Health Information Management Association. (2015). Data quality management model practice guidelines for managing health information. Journal of AHIMA, ₈₆(10), 62–65.

American Nurses Association. (n.d.). Health IT. Retrieved May 31, 2021, from https://www.nursingworld.org/practice-policy/health-policy/health-it/

American Nurses Association. (2015). N ursing informatics: Scopes & standards of practice (2nd ed.).

Belief. (2021, May 27). In Wikipedia. https://en.wikipedia.org/w/index.php?title=Belief&oldid=1025419743

Broomfield, C. B. (2015, September 21). Theory 1 Topic 4.1.1 Data Information and Knowledge [Video]. YouTube. https://www.youtube.com/watch?v=QsP5WGv0aQc&t=7s

Crush, P. (2018). The future of practice. Community Practitioner, 91(8), 34-38.

Data Flair. (2021). How big data is reshaping the healthcare industry– Top applications. Retrieved May 31, 2021, from https://data-flair.training/blogs/big-data-in-healthcare-applications/

Flynn, A. J., & Stevenson, J. G. (2018). The future of data, analytics, and information technology. American Journal of Health-System Pharmacy, 75(2), 31-34.

Case Western Reserve University. (2020). Graduate QSEN Competencies. Retrieved May 25, 2021, from https://qsen.org/competencies/graduate-ksas/#informatics

Homeyer, S., Hoffmann, W., Hingst, P., Oppermann, R., & Dreier-Wolfgramm, A. (2018). Effects of interprofessional education for medical and nursing students: Enablers, barriers and expectations for optimizing future interprofessional collaboration – A qualitative study. BMC Nursing, ₁₇(1). https://doi.org/10.1186/s12912-018-0279-x

Indian Institute of E-Commerce Business School. (n.d.) Your guide to data quality management. Retrieved May 31, 2021, from https://tutorials.one/your-guide-to-data-quality-management/

Jouparinejad, S., Foroughameri, G., Khajouei, R., & Farokhzadian, J. (2020). Improving the informatics competency of critical care nurses: Results of an interventional study in the southeast of Iran. BMC Medical Informatics & Decision Making, 20(1), N.PAG. https://doi-org.ju.idm.oclc.org/10.1186/s12911-020-01244-5

Kalodikis, C. (2020, March 27). Data Quality - Accuracy, Timeliness & Accessibility [Video]. YouTube. https://www.youtube.com/watch?v=6syeSsAp5Us&feature=youtu.be

Mashoufi, M., Ayatollahi, H., & Khorasani-Zavareh, D. (2018). A review of data quality assessment in emergency medical services. The Open Medical Informatics Journal, ₁₂(1). https://dx.doi.org/10.2174%2F1874431101812010019

McBride, S., & Tietze, M. (2019). Nursing informatics for the advanced practice nurse (2nd ed.). Springer Publishing.

McGonigle, D., & Garver Mastrian, K. (2021). Building blocks of nursing informatics. Nursing Informatics and the Foundation of Knowledge. http://samples.jbpub.com/9781449631741/92367_CH01_Pass2.pdf

National Academies of Sciences, Engineering, and Medicine 2021. (2021). The future of nursing 2020-2030: Charting a path to achieve health equity. The National Academies. http://nap.edu/25982

Nelson, R. (2018). Informatics: Evolution of the Nelson Data, Information, Knowledge and Wisdom Model: Part 1. OJIN: The Online Journal of Issues in Nursing 23(3). https://ojin.nursingworld.org/MainMenuCategories/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/Vol-23-2018/No3-Sept-2018/Informatics-Evolution-of-Nelson-Model-Part-1.html

Pimental Reis, N. da S., da Silva Dias, C., de Oliveira Monteiro, V., Garcia Barreto, C. T., de Souza Santos, R., & Sant’anna Nunes, A. (2020). Insertion of nursing diagnostic technologies: Innovations in secondary health care. Revista de Pesquisa; Cuidado e Fundamental, 12(1), 29-36. https://doi-org.ju.idm.oclc.org/10.9789/2175-5361.rpcfo.v12.6309

Profisee. (2021). Data quality - What, why, how, 10 best practices & more! https://profisee.com/data-quality-what-why-how-who/.

Rensburg, J. T. J., & Goede, R. (2019). A model for improving knowledge generation in design science research through reflective practice. Electronic Journal of Business Research Methods, ₁₇(4), 192–211. https://doi-org.ju.idm.oclc.org/10.34190/JBRM.17.4.001

Sipes, C. (2019). Application of nursing informatics: Competencies, skills, decision making. Springer Publishing

TEDx (2018, December 5).  Ronda Hughes: Improving health outcomes with big data [Video].YouTube. h ttps://youtu.be/uWGmAZOX6gU

Tian, Q., Han, Z., Yu, P., An, J., Lu, X., & Duan, H. (2021). Application of open EHR archetypes to automate data quality rules for electronic health records: A case study. BMC Medical Informatics & Decision Making, ₂₁(1), 1–11. https://doi-org.ju.idm.oclc.org/10.1186/s12911-021-01481-2

University of Basel. (2018). Annette DeVito Dabbs: Theories of technology acceptance [Video]. Vimeo. https://vimeo.com/266324628

Zementis, Inc. (2017, July 13). Dr. Michael Zeller: Definition of Data Science [Video]. YouTube. https://www.youtube.com/watch?v=JBf7-yGyCWk&feature=youtu.be

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How Big Data is Changing Healthcare

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Relationship Of Quality of Data and Information and Competencies

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American Association of College of Nursing (AACN) Expectations for MSN NI graduates  

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American Association of College of Nursing (AACN) Expectations for MSN NI graduates  

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QSEN's competencies for MSN Graduates of  Informatics 

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QSEN's competencies for MSN Graduates of  Informatics 

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Data Quality - Accuracy, Timeliness & Accessibility

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 Epistemology, Science, and the Generation of New Knowledge.

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 Epistemology, Science, and the Generation of New Knowledge.

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Epistemology is a concept used to describe how people think about knowledge. It is described as the essence of how we create new knowledge and the study of knowledge which is defined as the  justified true belief  (Rensburg & Goede, 2019). If there is no justification then the result is an opinion. In order to get to the justified truth, science is used as a method to promote objective examination of scientific findings  (McBride & Tietze, 2019).

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Advanced techniques in data mining, “big data,” and analytics implications.       

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Advanced techniques in data mining, “big data,” and analytics implications.       

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According to McBride and Tietze (2019) data mining first focuses on identifying anomalies/ correlations/ patterns/ trends in data and, once found, the focus shifts to determine directions that create dimensionality and gives the data its characteristics; this forms the picture(s) for assessing predictive or systematic behaviors. That data is further refined by removing deviation and sorting root sources to disregard distracting clutter in the data (graphic representations often portray this information).

McBride and Tietze (2019) explain that different techniques of data mining include anomaly detection (i.e.: detect public health trends for disease outbreaks), association rule learning (i.e.: may be used as precursor to predictive modeling), cluster analysis (i.e.: analysis of patients’ use of healthcare), classification (i.e.: classifying data that may further support HIT development), regression modeling (i.e.: predicting factors associated with healthcare), and summarization (i.e.: aggregate data by category and outcome measures).

McBride and Tietze (2019) state that “… advanced data-mining tools are capable of visualizing the higher order dimensions in complex data by displaying them in the lower order dimensions of 3D space” (p. 664). “These graphics include such things as 3D-animated scatterplots, multidimensional Trellis arrays, multidimensional heat maps, and multidimensional probability density gradient topological maps” (McBride & Tietze, 2019, p. 664).
“Big data” in a simplified definition is too much information to be stored in conventional databases and contain enormous amounts of a variety of data (transactional, structured, unstructured), which may lead to barriers in all functionalities of operation; different types of “big data” includes indexes, images/ videos, social networks, company records, and medical records (McBride & Tietze, 2019). “Big data” can be used to improve decision making and end-results, extend viewpoints on patients, real time cybersecurity measures, and increase operational efficiency (McBride & Tietze, 2019).
“Big data” and data mining interconnect and complement each other, which allows for significant implications for analytics’ teams to combine the qualities from both concepts to improve patient outcomes by getting to know the individuals and store their entire medical history, as well as increase security measures to protect this precious information. There is a place for nursing in this advancement of HIT to help identify problems produced by technology and provide solutions while, also, championing the benefits that patients and healthcare workers may appreciate and find beneficial.
Another important, and long overdue, component in emerging health care trends is working harder to find balance in health equity so that all communities benefit from safe and effective care. The National Academies of Sciences, Engineering, and Medicine (2021) 2021 report put a microscope to these inequities and made recommendations for more nursing curriculums to consider the importance of closing health care gaps by focusing on value-based care and use of technology. This combination can be utilized by NIs to identify social determinants of health and overcome barriers for access to quality healthcare, while ensuring that no community member gets left behind in burdensome or inaccessible technology.

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The importance of nursing informatics competencies and the roles that these nurses are well suited to perform.

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The importance of nursing informatics competencies and the roles that these nurses are well suited to perform.

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McBride and Tietze (2019) explain nursing informatics combine knowledge from information science, cognitive science, computer science, as well as a variety of technology interface characteristics, and for technology to be best utilized by the end-user means to incorporate various theories and constructs.

According to the ANA (n.d.), some of the emerging roles for nurses in HIT include nursing leaders to represent the profession on HIT committees and workgroups, creating the policies and operating procedures that encompass HIT initiatives, working with HIT alliances, and advancing education in HIT.

NIs ensure data is reliable and has integrity, aggregate and analyze data, perform outcomes recognition, stay alerted to technology barriers (ANA, 2015).

ANA (2015) states that NIs are in constant communication with the interprofessional clinical team and the IT team to help create platforms or documentation systems through retiring obsolete systems and data storage, providing the viewpoint of healthcare workers as well as advocating for the patients.

NI completes workflow analysis to better understand how processes are helping or hindering the efficiency and safety of nursing work, along with patient care and health (Sipes, 2019).

NI must be able to interpret and combine workflow processes and technology solutions; this knowledge allows for the NI to lead in the development of processes that create and improve interactions of technology and the end-user (ANA, 2015).

NI can use knowledge discovery in databases (KDD) by incorporating the data mining techniques previously discussed to identify meaningful patterns through statistical analysis (ANA, 2015).

ANA (2015) describes the significance of analyzing clinical vocabularies, languages, and taxonomies and assessing these for relevancy and accuracy in an evolving health system.

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Identify Attributes for Quality and Data information 

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Identify Attributes for Quality and Data information 

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Quality Data is difficult to describe because data in its self is broad. Quality Data plays a role in integrating evidence and research into practice (American Nurses Association [ANA], 2015). In general, data is considered high quality if relevant for its purpose in operations, leading to purposeful planning and implementing action. The main characteristics of quality data have been described as:

Accurate

Complete

Reliable

Relevant

Timely

Many of these characteristics have predetermined requirements of quality data. It is the foundation that leads to applied knowledge. If you have bad data quality, you will have poor information quality, which means you will have inadequate information to act on. Then your applied knowledge as an advanced practice nurse could lead to adverse outcomes (Profisee, 2020).   In a case study by Tian et al. (2021), ensuring data is of appropriate quality is essential. A beneficial method is by automating data quality rules (DQRs) to replace the time-consuming manual process of creating DQRs, which results inaccurate human errors.

Quality information is built on quality data. Attributes of Quality information defined by Sipes (2019) are:

Credibility

Accuracy

Free from bias

Reputable source

Beneficial to the task

Appropriate and valuable for the job on hand

Of an age that it can be suitable for use

Sufficient in detail or completeness for the task

Appropriate in amount

Clearly defined and in a usable form

Unambiguous

Consistent in format to allow comparison

Compact and concise

Subject to easy and quick retrieval

Secure

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https://profisee.com/data-quality-what-why-how-who/

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Science is the process of gaining knowledge by making observations, posing questions, and testing through experimentation.  To determine if its knowledge or opinion there are theories utilized in the development (McBride & Tietze, 2019). The following are levels of theory development:

A phenomenon is observed

An interpretation is proposed

A model is created outlining key concepts and their relationships to the phenomenon, including processes and interactions between the concept

The model is checked and refined. A hypothesis emerges and grows as a result of this iterative investigation.

To keep up with the evolving and fast-paced information in nursing healthcare,  Healthcare Information Technology (HIT) relies on the generation of knowledge of nursing theorists and researchers to disseminate their expertise. Knowledge generation is guided by human expertise, input, and how the input is transformed into useful, actionable results.

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Theory 1 Topic 4.1.1 Data Information and Knowledge

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http://samples.jbpub.com/9781449631741/92367_CH01_Pass2.pdf

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To keep up with the evolving and fast-paced information in nursing healthcare,  HIT relies on the generation of knowledge of nursing theorists and researchers to disseminate their expertise. Knowledge generation is guided by human expertise, input, and how the input is transformed into useful, actionable results.
In a study by Rensburg and Goede (2019), it supports that reflective practice, or "learning by doing," which improves new knowledge generation in the preparation of information technology (IT) students for their chosen career.