Introduction
The exponential growth of the global population and increased scientific research on health have created a database of massive healthcare data. Technological advancement enables medical practitioners to access and leverage data to improve health outcomes. Big data plays a significant role in healthcare and offers unique opportunities for personalized medicine because it provides data such as treatment outcomes using critical lifestyle information.
Big Data
Hospitals that utilize big data can offer predictive medication and manage population health effectively. Since the data can be used to identify patterns in health and outbreaks, the information can be manipulated to provide accurate and timely decisions.
Further, detecting fraud and offering a cost-reducing mechanism through leveraging big data is possible. The decision to improve privacy in handling healthcare data was made after a thorough investigation of how several institutions failed to use big data without considering data breaches. Data mining is essential to healthcare management because it offers insights into accurate decision-making and improves care delivery models.
Business Problem and Its Importance
Globalization of healthcare delivery through the lens of big data offers people worldwide a chance to access healthcare. The introduction of telehealth enables people to access quality healthcare services regardless of their geographical location as long as the places they are have adequate internet connectivity. The operational shift in medical healthcare leverages big data to improve healthcare delivery, decision-making, and treatment of chronic diseases. Generally, big data is helpful in clinical business models because it can be used to predict and prevent diseases, improving health quality (Abouelmehdi et al., 2018). Big data is the antidote for developing modern healthcare facilities that efficiently fight diseases and improve the quality of health among the population.
Despite the benefits of big data in healthcare, some challenges might jeopardize care delivery. The main challenge associated with big data in the healthcare domain is data privacy, as patient information may be exposed to unauthorized personnel who may use the data for selfish gains. Further, the concept of big data breaches ethical conduct because imminent issues such as data ownership and informed consent are not considered for safety. Data quality, integrity, and bias affect the usefulness of big data in healthcare facilities (Abouelmehdi et al., 2018). Further, the infrastructural requirements and resources to maintain big data may need to be more affordable to upcoming healthcare facilities. Healthcare businesses must, therefore, overcome the threats posed by big data to enjoy the benefits associated with big data in improving healthcare outcomes.
Selection of Data Sources to Glean Information
The quality of research is directly proportional to the methods selected to gather data. The symbolic gathering of information shows how big data have been leveraged in different parts of the world to improve healthcare outcomes. Information on the accuracy of extensive data was obtained from different cases worldwide using big data to improve healthcare outcomes and analyze the associated risks. Data mining from other sites, such as the South Tyneside NHS Foundation, provided data on the health status of the community in England, UNC healthcare data in North Carolina, and the Indiana Health Information Exchange (Abouelmehdi et al., 2018). Extensive data systems from various parts of the world were analyzed in terms of operations and how they used the data to improve healthcare outcomes in the region.
The Italian medical agency was also consulted on how different information was available for use and how the info breached the privacy issues raised by the users. The risk associated with mHealth was evaluated using data from the World Health Organization on how information about people from various parts of the world would be leveraged for better outcomes. Minutes from the annual meeting on big data in healthcare conducted by the American College of Medical Genetics and Genomics were a valuable source of information to understand the dangers posed by big data in healthcare (Abouelmehdi et al., 2018). The selection of the data source was specific to the need of the research as it offered insights into how big data was leveraged in improving care outcomes.
Data Evaluation and Visualization
Once data has been collected in research, the most crucial part is to evaluate and present its findings in the form of visuals to communicate the outcome quickly. The data was evaluated based on the breaches that were incurred in the process of accessing the extensive data to improve care outcomes. The number of breaches was 325 in PHI, affecting over 16 million patient records. Further, the breaches were categorized per year, and it was noted that over 3 million breaches happened in a single year due to unauthorized access to medical information. The organizations that leveraged big data without considering the patients’ privacy were liable to ethical and legal action for the breaches.
Privacy was the primary concern when handling big data, and the visualization of the data was to show how data breaches were experienced during the use of the big data. The main visual aids used in the data presented were tables where the number of breaches and their implications in healthcare were presented. Further, figures in pie charts were used to show the dangers and challenges associated with big data in healthcare (Abouelmehdi et al., 2018). The figures depicted whether the use of big data posed a high, moderate, or low danger.
Solution Presented
The overall solution provided was to ensure privacy when using big data. Although big data is helpful in the decision-making of healthcare facilities, privacy breaches are one of the critical threats that negatively affect the credibility of using big data to offer a solution in healthcare. The proposed solution was, therefore, to model data and use the latest technologies to filter and encrypt data to ensure that it is only visible to people who are allowed to view the solution (Abouelmehdi et al., 2018). One solution was to enhance ticket granting and data protection to ensure only those with tickets can access the data. The overall solution is that all hospitals leveraging big data to improve healthcare outcomes and decision-making should always ensure privacy.
Overall Process Evaluation and Solutions Effectiveness
Gathering information on how big data has been used in different regions gave an international perspective on big data. Since data was collected from other countries on how large data poses a threat, it proves that although extensive data is essential for delivering care, it must be protected. The solution is effective because it allows hospitals to use big data without being implicated in breaches. The provided solution is universal and can be used anywhere in the world to offer a better solution.
Conclusion
The healthcare domain is ever-evolving, and data mining continuously becomes crucial for decision-making. Leveraging big data is an essential trend in healthcare since it enables hospitals to predict health patterns and offer evidence-based solutions. However, the use of big data is marred with numerous challenges of privacy and data integrity, which may jeopardize a facility’s ethical standards. The critical solution is, therefore, to use privacy measures to ensure that personal data is safe and unavailable to unauthorized personnel. Data mining to determine the importance of privacy helps business models protect patient information, upholding integrity and ethical considerations.
Reference
Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: Preserving security and privacy. Journal of big data, 5(1), 1-18. Web.