The organization of modern medical practice in such a way as to ensure the highest possible patient safety seems to be the cornerstone of nursing. In the modern world, digital methods of storing information are becoming a new established tradition and progress is made mainly through the development of computer technologies. In this context, the safety of the patient largely depends on the reliability of the methods of organizing and storing information about the patient, maintaining its reliability and confidentiality. Storing and maintaining streams of information called big data turns out to be a constant auxiliary tool in modern nursing activities.
Big Data in Contemporary Medical and Nursing Context
Big data in the medical environment is emerging due to the changing medical landscape, which requires an increasingly high quality of care. This is largely due to the financial model on which the national health care system is based, which is initially commercial. In order not to scare people away from receiving qualified medical care, it is really necessary to develop it to such a level that it is worth its money – such a modern perception requires the achievement of a result as proof that the work can and should be paid. In the context of these increased demands on the system, the Institute for Healthcare Improvement has developed a triple goal framework.
This is a kind of credo for modern medicine in the United States, consisting of three principles. Modern medical goals are to improve the patient experience, increase the effectiveness of treatment, and lower the cost of treatment for an individual. All these qualities of modern medicine are to some extent detectable at the moment, but it should be emphasized how much big data played a role in this improvement.
Big Data in Diagnostic Software
In the context of medicine, data means that factual and statistical information that can contribute to decision-making and the conclusion of judgments. Currently, no truly qualified treatment process can do without big data. All information about the patient’s medical history, their previous medical services should be available to both the doctor and the nurse. The development of the basic methodology of treatment and the prescription of drugs in America is often carried out with the intervention of computer systems integrated into the work of the hospital.
The patient is diagnosed and the data on its results are entered into a special analytical software. Further, based on the results of the analyzed data, the computer mechanism is able to present the most probable diagnoses and several acceptable treatment strategies (Linnen, 2017). One may be concerned about the question of how much this deprives the nurses and diagnostic doctors themselves of the work. However, the idea is being created that such a software should be perceived as an auxiliary device rather than an irreplaceable development that will supplant the very figure of a doctor.
The results given by such programs should always be critically assessed by a person in order to avoid error, failure or an inadequate and incompatible course of treatment with the patient’s health. In particular, the value of independently interpreting the information generated by the mechanism is high in executive leaders, whose task is to issue balanced and enforceable directives to their wards. The real reliability of patient care lies precisely in the ability to interpret data independently, even if using computer programs, but not blindly relying on them.
Another type of information processing that regularly and ubiquitously uses big data is Electronic Health Records, or EHRs. These records may be updated over time and offer interpretive analyzes of symptoms that are too complex to be analyzed accurately due to subjectivity and variability (Rajabion et al., 2019). By collecting changing symptoms from a large number of patients from large-scale clinical repositories, it becomes possible to organize and visualize this data for a clearer picture of the clinical picture. Thus, storing multimillion-dollar EHRs can facilitate diagnosis and create a large objective picture for further interpretation. This is yet another example of how big data is helping to better diagnose a patient, improving their experience and maximizing their safety.
Safety of Patient’s Confidentiality
Along with the increased technologization of medical institutions and the treatment process, there is a need to revise the principles by which the patient’s safety is ensured, which includes the safety of the information stored about them. Confidentiality and private information are essential to ensure that the patient’s rights are truly preserved, since the right to private property is at the heart of the benefits of a developed social culture.
Thus, any information contained about the patient must have a closed, strictly limited access precisely in order to provide the patient with a safe environment for treatment. Violation of the confidentiality of information is unacceptable because it can violate the truth and authenticity of information (Kim, 2018). Also, patient information must be securely stored in order to avoid the risk of leakage and disclosure of this information, which, like healthcare, lies in the field of basic social rights.
Speaking about the benefits of collecting and using big data, it is nevertheless necessary to stipulate the ethical contradictions of this large-scale process. In modern realities, data collection can be applied to virtually everyone using a mobile device, for example, through applications for measuring blood pressure or pulse, filling out questionnaires and analytical programs (Househ et al., 2019).
The policy of the agreement on the use of the application by the consumer only externally implies that this agreement will be read and, most importantly, completely correctly perceived. As a result of reckless agreements on the collection of information, it can be assumed that many databases are collected virtually without the knowledge of those whose data are used. Thus, a large date may imply the patient’s unawareness of the loss of confidentiality of information about his health, which is undoubtedly an ethical flaw that needs to be corrected.
In conclusion, it is required to say about the need for a balance between the right to maintain confidential information and the use of big data. Of course, in the modern world, whose life is especially complicated by the conditions of a pandemic, the medical system must use all available information in order to produce the most accurate and balanced strategies of action. Learning new things and the ability to quickly diagnose and give instructions to nursing wards is extremely valuable in a modern specialist. However, the right to private information refers to the authority of the patient – one of the main, if not their main right, which doctors are obliged to protect. The use of big data in diagnostics is proving to be extremely effective, but the patient’s safety can also mean his right to privacy of information.
Househ, M., et al. (2019). Big data, big challenges: A healthcare perspective: Background, issues, solutions and research directions. Springer.
Kim, W.-K. (2018). Knowledge-based diagnosis and prediction using big data and deep learning in precision medicine. Investigative and Clinical Urology, 59(2), 69-71. Web.
Linnen, D. (2017). The promise of big data: Improving patient safety and nursing practice. Nursing, 46(5), 28-34. Web.
Rajabion, L., et al. (2019). Healthcare big data processing mechanisms: The role of cloud computing. International Journal of Information Management, 49, 271-289.