DQ: Discuss two strategies that would help a researcher manage and organize the data

NRS 433 Topic 2 DQ 1

DQ: Discuss two strategies that would help a researcher manage and organize the data

The National Database of Nursing Quality Indicators and the VA Nursing Affairs Outcome Database are two software programs that collect and store information to be evaluated and used by professional nurses as strategies to store research data that will be used to delivery evidence-based care. These databases were “designed for evaluating nursing care in the acute setting” (Montalvo, 2007). When this data is retrieved, it is referred to as data mining. “Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results” (Yang, 2020). Professional nurse researchers are no longer having to manage their own data because information technology manages them electronically. Because nursing demands ethical professional guidelines in EBP, whatever strategy a nurse chooses to use, they must pull from a trusted research database otherwise, they may risk unethical outcomes. When searching for strategies to store and retrieve data, nurses must be aware of the possibility of “scientific misconduct, particularly as it pertains to falsification, fabrication, and plagiarism” (Ulrich, 2015). In cancer epidemiology studies a program often used is SEERS, or Surveillance, epidemiology, and end results. This clinical information helps clinical researchers provide efficient, convenient, and clear access to data. Strategies for managing data in 2022 include advanced technologies. Respectfully, Jana

DQ: Discuss two strategies that would help a researcher manage and organize the data

Montalvo I. (2007). The National Database of Nursing Quality Indicators (NDNQI). Online Journal of Issues in Nursing12(3), 13p.

Ulrich, C. M., Wallen, G. R., Cui, N., Chittams, J., Sweet, M., & Plemmons, D. (2015). Establishing good collaborative research practices in the responsible conduct of research in nursing science. Nursing outlook63(2), 171–180.


Yang, J., Li, Y., Liu, Q., Li, L., Feng, A., Wang, T., Zheng, S., Xu, A., & Lyu, J. (2020). Brief introduction of medical database and data mining technology in big data era. Journal of evidence-based medicine13(1), 57–69.

Jumyr Kangleon

replied toJana Garcia

Apr 14, 2022, 8:44 PM

Replies to Jana Garcia

Hi Jana, Themes analysis, grounded theory, and literature reviews are some of the approaches used in qualitative research, and evaluating qualitative data may be overwhelming and complex. The examination of huge amounts of data in order to identify meaningful patterns and rules is an essential aspect of scientific discovery because patterns are required for the development of scientific hypotheses and causal models (Berber & Berber, 2004). Qualitative research results are useful because they provide a better understanding of the facts that describe people’s behaviors, routines, lives, and minds. Data mining tries to explain and clarify behavioral patterns in massive volumes of data. A large volume of data is extracted (mined) for useful knowledge. Such knowledge will allow for the establishment of relationships between attributes or data sets, the clustering of similar data, the classification of attribute relationships, and the display of information that would otherwise be hidden or lost in a massive amount of data if data mining were not used (Pastrana et al., 2019). When working with large amounts of data, particularly data from nursing research, the task of analyzing can be difficult to manage and organize. In nursing research, data mining as a method of data analysis can aid in the finding of causal factors and the demonstration of outcome effectiveness (Berger & Berger, 2004). This technique can turn a huge amount of data into useful information that can improve clinical practice. It is critical to recognize the value of data that can enhance the lives of others when we are able to locate it. The opportunity for nurse researchers to acquire useful insight into patterns and trends has the potential to improve nursing knowledge and progress.

DQ: Discuss two strategies that would help a researcher manage and organize the data

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Thank you for responding to my post. Data mining in research was especially important during the Covid-19 pandemic because it was and still is imperative that the public are health care literate to understand Covid-19 and prevention measures. However, the

DQ Discuss two strategies that would help a researcher manage and organize the data
DQ Discuss two strategies that would help a researcher manage and organize the data

“pandemic of COVID-19 shows that low health literacy is a public health problem that has long been underestimated worldwide” (Qi, 2021). It is the responsibility of Public Health professionals to present education on Covid-19 in a manner that the public will understand and review the results to prove that education is useful and more importantly that the public is utilizing the information to prevent the spread of infection. Data mining is used in this process. Countries with low health literacy would require more education and perhaps more field work from Public Health officials. Data mining has shown researchers that “a systematic approach is needed to address health literacy issues, together with a strengthened framework of collaborative networks for health literacy at all regional, national and global levels” (Qi, 2021). Researchers use data mining to determine country by country and region by regions what implementations are needed to help the public understand the Covid-19 disease. The information gathered by data mining keeps us all safer when strategies are developed to prevent the spread of infection based on the publics level of understanding. Thank you, Jana

Qi, S., Hua, F., Xu, S., Zhou, Z., & Liu, F. (2021). Trends of global health literacy research (1995–2020): Analysis of mapping knowledge domains based on citation data mining. PLoS ONE16(8), 1–23.

  Gale Storm-Bryant

replied toJana Garcia

Apr 16, 2022, 9:49 PM

Replies to Jana Garcia


Thanks for your post.

An area of concern came to mind with thought of using data management services and software for storage of a research project. Accuracy of the information that will be found in this data system as although it is a computer-based program it is humans that enter the information into the system. It is great to have assistance in managing the information that has be collected by the researcher as organizing data can be very time consuming if using interviews, charts, graphs, and visuals as your process (Guetterman, et al., 2021). I can imagine a researcher being very possessive over their work, making sure everything is in order. They would have to have extensive training and knowledge in the use of the data management software and services. There are many libraries within the academic world investing in research data management services and piloting programs for information on its usefulness in the academic world (Muellenbach, 2021).

DQ: Discuss two strategies that would help a researcher manage and organize the data

It is very important that all software services and researchers maintain ethical behavior as it relates to patients, society, and the healthcare profession. Maintaining privacy, dignity, having informed consent and insuring participants understand the use and storage of their information (Dimitrios & Antigoni, 2018). The use of a research software and data base may give access to others if not properly secured and this could pose an ethical issue of breach in confidentiality.

Qualitative data refers to non-numerical data that is collected through observations, interviews, focus groups, and other forms of inquiry that seek to understand complex phenomena. Qualitative data are often voluminous and complex, making it challenging for researchers to manage and organize the data effectively. In nursing research, qualitative data are frequently collected to explore the experiences, perspectives, and meanings of individuals in relation to health and illness.

Two strategies that can help researchers manage and organize qualitative data are coding and memoing. Coding is the process of systematically identifying themes and patterns within the data, while memoing involves writing down personal reflections and interpretations of the data as the researcher progresses through the analysis process (Hsieh & Shannon, 2005). These strategies can help researchers to reduce the complexity of the data, identify key concepts and themes, and develop a deeper understanding of the research participants’ experiences.

In nursing research, coding and memoing are commonly used to manage and organize qualitative data. For example, in a study exploring the experiences of cancer patients receiving chemotherapy, researchers used coding and memoing to analyze interview data and identify themes related to the patients’ emotional experiences (Pereira et al., 2019). The researchers found that coding and memoing helped them to organize the data, identify key themes, and develop a more nuanced understanding of the patients’ experiences.

Managing and organizing qualitative data can be challenging for researchers due to the complexity and volume of the data. Strategies such as coding and memoing can help researchers to reduce complexity, identify key themes, and develop a deeper understanding of the research participants’ experiences. These strategies are particularly useful in nursing research, where qualitative data are often collected to explore the experiences of patients and healthcare providers in relation to health and illness.


Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative health research, 15(9), 1277-1288.

Pereira, M. G., Roque, A. T., Maroco, J., & Monteiro, E. (2019). Emotional experiences of chemotherapy: A qualitative study with breast cancer patients. European Journal of Cancer Care, 28(3), e13044.