The Availability of Open Data Sources for Nursing Professionals

Subject: Nursing
Pages: 6
Words: 1501
Reading time:
6 min
Study level: Bachelor


The availability of open data sources has tremendously changed the entire health care industry providing new opportunities and unique challenges for nursing professionals. This paper reviews research conducted by Kobayashi et al. is dedicated to the issues of accessibility and information protection of various databases. The consideration of the applied methodology and sampling techniques shows the benefits of the conducted study and the areas of its possible improvement. It also contains an analysis of the credibility of obtained results and states the ways of its enhancement. Based on the conclusions provided in the original research, the paper indicates the desired directions for further studies and their possible practical applications.


The rapid development of information technologies has concerned all spheres of professional activities. Bringing both new opportunities and unique challenges, these means require a thorough assessment. Among the numerous areas of their application, the one related to health care proves to be probably the most promising, but sensitive. Many researchers have devoted their attention to finding the balance between privacy and accessibility of open data for nursing professionals. An example of such a study, which is worth a specific consideration, is the paper by Kobayashi et al. (2018), containing several significant observations.

The analyzed research is dedicated to open data application, privacy, and protection in various health care systems. This is a critical aspect of the health informatics in general, which allows combining nursing science and current data processing technologies. Health informatics is valuable in identifying the risks of specific illnesses for patients and their families (Saqib et al., 2018). Moreover, it constitutes a convenient replacement for a paper document containing the history of prior diseases (Tobiano et al., 2016). Besides, the depersonalization of specific data categories within health informatics enables developing knowledge bases, providing unique opportunities for practitioners throughout the world.

Based on the general understanding of health informatics with all its limitations and sensitivity, the primary research question covered in the paper is to find the proper balance in ensuring information availability. This mainly concerns the contradicting requirements of maintaining personal data protection and enhancing the global health care level by sharing treatment strategies (Kobayashi et al., 2018). The research question was further supplemented by the goal to analyze the actual openness of various datasets and use specific cases to show privacy considerations. Therefore, the researchers aimed at providing a comprehensive review of the current state of open data application in health care.

The issue raised in the article is critical for any nursing professional who has to find the right solutions for a patient. The possible benefits of open data application have been recognized worldwide. They include “improving the efficiency in the delivery of care, a reduction in overall costs to the health care system, as well as a marked increase in patient outcomes” (Kruse et al., 2016, p. 2). Besides, open databases provide quick access to the data on “the efficacy, safety, and outcomes of new medical innovations, thereby also promoting transparency of research methodologies” (Bhavnani et al., 2017, p. 2704). On the other hand, privacy issues remain a significant concern for many. Like the one when over a million records were inappropriately given to Google via DeepMind, technical failures still occur (Kobayashi et al., 2018). Therefore, a nursing professional should seriously consider all the arising complications when providing free access to the available data.

The focus on the internet databases significantly influenced the setting for the research. Since the reviewed issues did not require direct communication with patients or their treating physicians, the study was entirely conducted in an online form. That was a reasonable decision based on the need to obtain some general conclusions on the data accessibility and applicability. This approach was supported by a review of widely known cases, the data on which is available in various sources. Besides, the article indicates that it is the product of several working groups within the International Medical Informatics Association (Kobayashi et al., 2018). Such global cooperation is reasonable for analyzing the conditions in various nations with diverse levels of development. Extending the research outside the scope of a few highly-sophisticated countries is a valuable step in making the results generalizable for a wider population. Therefore, the selected setting fully supports the goals stated by the researchers.

Another critical aspect is the selection of a proper sample. For this research, the declared method was a “snowball sampling technique,” which included searching various internet sources for the open health databases mentioned in them (Kobayashi et al., 2018, p. 43). This is a feasible starting point considering the variety of available data repositories ranging from general to specialized ones. However, there is no indication of any criteria used for the selection of the particular databases. A possible example would be the accessibility of a given portal and its frequency in various sources. Still, the sample does not include a World Health Organization dataset, which is among the widely-known ones. Besides, the selected repositories are the ones from the highly-developed countries. This limits the applicability of the obtained results since the issues that may appear in other societies remain unrevealed. Therefore, the sampling methodology is not completely defined and could be improved for the overall benefit of the study.

To analyze the selected databases and review the issues of their accessibility and privacy, the researchers decided to apply qualitative methods. As declared in the paper, it is a “combination of Open Source Working Group discussions and desk research” (Kobayashi et al., 2018, p. 42). In general, qualitative research is applied to answer the questions of “experience, meaning and perspective” and includes small-group discussions, interviews, and document analysis (Hammarberg et al., 2016, p. 499). It constitutes an especially important source of evidence for nursing practice in cases where personal attitudes are valuable. It is also helpful when the relevant data are limited. The application of such methodology in the study is justifiable by the need to address various aspects of the issue, including the widespread ideas about insufficient data protection. Besides, group discussions allowed sharing different opinions and raising valuable questions.

However, the qualitative methods could also be supported by some quantitative research, which generally constitutes a proper way of identifying profound trends and relations between different phenomena. First, it would be beneficial to add some figures demonstrating the variety of data stored in the repositories reviewed in the article. Besides, the discussion about data protection issues would become more objective if certain indicators were used. For instance, this could include the amounts of leaked data and the frequency of such events. Therefore, the selected approach is generally feasible for the research but could be further enhanced.

The applied methodology is closely tied to the research design used by the authors. In this case, it is primarily grounded theory research with case study elements. The grounded theory is usually viewed as the one bringing the necessary rigor to the qualitative analysis. The phenomenon to be reviewed in this paper was the increased availability of open health data. The collection of the evidence was aimed at determining its true spread and consequences. However, one of the most common issues with this research design, which is also evident in the study, is the lack of a cyclical approach. The analysis did not influence the sampling process, which resulted in losing an opportunity for adjusting it. The addition of the case study part slightly compensated for it but made the conclusions more subjective. Therefore, the research design helped obtain the desired results but did not ensure full confidence towards them.

The conclusions reached by the researchers could be divided into two primary groups. The first one is dedicated to the availability and contents of the health data. They indicated that there is a large number of portals providing such information, and the amount of data stored there is rapidly increasing. This is mentioned as a driver for further innovations and transparency. The other part is related to the achieved level of privacy. In this regard, there are some contradictions throughout the paper. The authors indicate that the analysis of privacy policies did not reveal any issues. However, they also mention that “the level of openness of health datasets needs to be restricted” (Kobayashi et al., 2018, p. 45). This conclusion is not based on the materials provided in the paper, which makes it relatively subjective.

Finally, the overall assessment of the article leads to a mixed attitude towards it. On the one hand, it raises an essential issue of driving innovations and increasing the quality of treatment through big data. This indicates an excellent source of ideas for any nursing professional to apply in complicated cases. On the other hand, the critical topic of data protection is not completely covered. At this point, the article only raises additional questions concerning the databases’ safety without providing the needed guidance for the practitioners. Therefore, this research can merely be considered as an opening of an important issue, and a further detailed study is required.


Bhavnani, S. P., Parakh, K., Atreja, A., Druz, R., Graham, G. N., Hayek, S. S., Krumholz, H. M., Maddox, T. M., Majmudar, M. D., Rumsfeld, J. S., & Shah, B. R. (2016). 2017 roadmap for innovation – ACC health policy statement on healthcare transformation in the era of digital health, big data, and precision health: A report of the American College of Cardiology task force on health policy statements and systems of care. Journal of the American College of Cardiology, 70(21), 2696–2718. Web.

Hammarberg, K., Kirkman, M., & Lacey, S. (2016). Qualitative research methods: When to use them and how to judge them. Human Reproduction, 31(3), 498–501. Web.

Kobayashi, S., Kane, T. & Paton, C. (2018). The privacy and security implications of open data in healthcare: A contribution from the IMIA open source working group. Yearbook of Medical Informatics, 27(1), 41-47. Web.

Kruse, C. S., Goswamy, R., Raval, Y., & Marawi, S. (2016). Challenges and opportunities of big data in health care: A systematic review. JMIR Medical Informatics, 4(4), 1–12. Web.

Saqib, N., Raza, M. & Ikram, L. (2018). Role of online data from search engine and social media in healthcare informatics. In M. D. Miltiadis, P. Papadopoulou (Eds.), Applying Big Data Analytics in Bioinformatics and Medicine, (pp. 272-293). IGI Global.

Tobiano, G., Bucknall, T., Marshall, A., Guinane, J. & Chaboyer, W. (2016). Patients’ perceptions of participation in nursing care on medical wards. Scandinavian Journal of Caring Sciences, 30(2), 260-270. Web.