Due to unraveling changes in disease-causing agents and improving care delivery to the patient, recorded data have developed into a critical clinical, epidemiological tool in health care in modern times. The concept of big data arose because of technological advancements and the need to connect data from various healthcare institutions to improve care. In the context of data analysis, big data refers to the sharing of data sets across networks of multiple databases or within a single country. The imperative of extensive data in modern times has led to a growing scholarly interest in the idea of a highly technologically centered perspective to a healthy population. Big data analytics have resulted in significant advantages in health care operating, management, organization, strategic planning, and acquisition. The world is moving quickly from a disease-centered to a patient-oriented model, which means that a comprehensive analysis of client behavior is necessary, given the rapid growth of the healthcare sector. This paper discusses the advantages, the electronic health records and the application of big data in healthcare informatics.
Advantages of Big Data Analytics in Healthcare Informatics
Data analytics in the healthcare sector have been described as a mixture between innovation and technology. These healthcare data are considered to be highly sensitive and need sufficient attention to avoid loss or interference. Such substantive information is intended for future use to enable healthcare companies to establish relationships when addressing different illnesses. The use of this big data in the institutions also provides the proper inferences ( Islam et al, 2020) . Big data has provided new insights like use of electronic health records in which healthcare institutions can coordinate their emerging trends and value their results in less time, given the identification of the assessment process, which can be improved through big data. Consequently, extensive data have been identified to offer many opportunities for treating disease patterns correspondingly.
Delegate your assignment to our experts and they will do the rest.
Electronic Health Record used in Big Data Analytics in Healthcare Informatics
The EHR system first offers health care professionals and all health professionals in the hospital the ability to maintain up-to-date and accurate information on patients' treatment in the hospital. The concept for electronic health records promotes other techniques such as telemedicine and other care facilities in the area of technological health care The EHR system maintains all patient records and enables them to be shared on-demand with other health care stakeholders. Data from patients is managed properly within the electronic health record system. The system enhances that doctors diagnose patients, improve prescription services, and reduce medical errors significantly, making the clinical system safer.
The use of an electronic health system makes patient data safer from unauthorized access, especially by naked eyes. Health has achieved convenience in the administration of healthcare as patient data records can be accessed from any branch of a clinical system with an integrated electronic record-keeping system ( Islam et al, 2020) . All the patient treatment data is contained in the patient's profile hence accuracy in operations like billing and patient reports generation—reducing medical errors making the clinical system safer. The use of an electronic health system makes patients' data safer from unauthorized access, especially by naked eyes. Health has achieved convenience in the administration of healthcare as patient data records can be accessed from any branch of a clinical system with an integrated electronic record-keeping system. All the patient treatment data is contained in the patient's profile hence accuracy in operations like billing and patient reports.
Applications of Big Data Analytics in Healthcare Informatics
In the healthcare industry, big data is used to improve safety monitoring methods. Data analytics is commonly used in hospitals to evaluate real-time events and patterns of health issues. This allows health professionals to monitor disease occurrences and predict the condition's future using data. This enables the creation of fraud analysis reports, in which they use data analytics to evaluate the various numbers of identified claims and cases. This analysis has been identified to be an effective measure of the reduction of health disparities.
Biomedical informatics concepts use big data concepts to solve human health problems by supporting medical research operations. Biomedical informatics uses obtained patient or population data and subjects it through medical science analysis to aid in the formulation of a sensible decision on a pending health issue. Implementation of biomedical informatics in a clinical system is that various disciplines can be pooled together, including clinical practices, statistical methods, bioengineering, and epidemiology in a computer system, operated by software to give biomedical solutions to the healthcare system ( Islam et al, 2020) . Solutions emanating from biomedical informatics in healthcare include imaging informatics, bioinformatics, clinical informatics, and clinical translation science. These solutions are very helpful in the healthcare sector.
Ethics and the Future of Big Data
Implementation of big data in clinical systems comes with various risks. The major risk discusses in this context is a data breach involving compromised data privacy. The electronic health records data managed by bid data capabilities can be accessed by unauthorized parties leading to exposing a healthcare system to ethical and legal battles from the patients and other stakeholders. Technological infrastructure remains vulnerable to complicated data security infringements like hacking. A health system held data could be accessed authoritatively and for the wrong reasons leading to disclosure.
Moreover, the medical data coded in big data packages can be compromised by malware, leading to the entire clinical system's malfunctioning. Any interference of big data in a clinical system can lead to devastating consequences. Alteration of the data records can lead to misinformation and biased medical processes like drug prescription ( Islam et al, 2020) . The alteration or any other form of a data breach is a big data system can negatively impact medical practitioners like nurses. The nurses, especially a nursing informaticist, are key to the security and maintenance of all nursing informatics systems in a hospital. Hence, any setback resulting from a failed big data informatics system can compromise the professional profiles of the involved healthcare personalities.
The challenges facing the use of big data in a clinical setting can be mitigated in various ways. One of the best methods to secure the bid data-backed system like the electronic health system is vetting the people who manage the system. The editing, updating, and sharing of the patients' data should be done by very few authorized persons who enable in case of any data breach. Some data breaches in other organizations whose operations are backed by big data emanate from disloyal employees who share their data with malicious persons like competitors. The people handling the hospital big data should e vetted and stringent punishments imposed on those who compromise the statutory healthcare laws on data security. Big data analytics has the capability to transform the health care system by helping doctors make informed decisions.
Conclusion
Big data is identified to be beneficial for different organizations in the world. The healthcare industry has used the data to analyze different disease patterns and trace the events and their respective occurrences. This has made it possible for big data to be widely applied in medical practice. The education on health care and nursing provided is based on the different occurrences of diseases and other health conditions.
Reference
Islam, M., Karim, R., Khatun, M. A., & Reza, S. (2020, November). A research on big data analytics in healthcare industry. In 2020 International Conference on Information Science and Communications Technologies (ICISCT) (pp. 1-5).
