Using big data can help reduce healthcare costs. Big data enables doctors or physicians to better diagnose and treat chronic diseases better due to comprehensive information on their history. Galetsi et al. (2019) affirm that previously, there was limited patient history information to doctors that hampered progress in planning, especially in cases of multiple symptoms such as autoimmune diseases. Better and efficient treatments reduce the number of times the patients have to undergo treatment and reduce healthcare costs. For example, big data helps effectively manage and treat diabetes through the numerous uses of numerous data generated by glucometers, wearable exercise monitors, smart blood pressure cuffs, and smart insulin pens. People with diabetes can track, with ease, their glucose levels in real-time using glucose monitoring systems.
One of the biggest challenges or risks of using big data is data security and privacy breaches. Medical information has high value to hackers and other attackers. It makes healthcare vulnerable, especially in this era of increasing rapid-fire series of ransomware, hackings, and high-profile breaches. In 2019, Dominion national reported cases of close to a decade hacking on its servers that breached the data of its 2.96 million patients (Cave et al., 2020). The data breached included enrollment and demographic information, individuals’ dental data, benefits, data plans for plan producers and health providers.
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Strategy to mitigate the challenges or risks of using big data
To ensure data security and protection of data for healthcare institutions, there are strategies that organizations can implement to limit or prevent insecurity and compromise on the data. Such measures include ensuring transmission security, controls over access, auditing, integrity measures, and authentication protocols. Organizations should consider strict adherence to foundational security, such as using only updated anti-virus software, encryption of sensitive data, setting up firewalls, and using multi-factor authentication (Groves et al., 2016). Since even with these measures, there is a possibility of breaches, it’s crucial for the healthcare organizations and institutions always to train their employees and regularly remind them of their role in ensuring they follow data security protocols.
References
Cave, A., Brun, N. C., Sweeney, F., Rasi, G., Senderovitz, T., & Taskforce, H.‐E. J. (2020). Big data–how to realize the promise. Clinical Pharmacology & Therapeutics, 107(4) , 753-761.
Galetsi, P., Katsaliaki, K., & Kumar, S. (2019). Values, challenges and future directions of big data analytics in healthcare: A systematic review. Social Science & Medicine, 241 , 112-553.
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare: Accelerating value and innovation.
