Assessment of big data opportunities and risks

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Reference no: EM133701701

Answer by offering one or more additional mitigation strategies or further insight into your colleagues' assessment of big data opportunities and risks. Provide Two references

Big Data in clinical systems is defined as massive datasets with vast amounts of clinical data that are generated at an incredibly high speed and require specific technology to break up and uncover their covert value because they cannot be analyzed using traditional tools (Olaronke & Oluwaseun, 2016). The healthcare industry generates substantial data from electronic medical records, hospital information systems, image centers, laboratories, pharmacies, and other health service agencies. Big data analytics will aid healthcare organizations in disease surveillance, public health management, and more. It can also predict future events by creating trends about the past. With its traceability, big data analytics can keep track of real-time information created by devices, such as Telehealth Response Watch in-home care services. This accessibility allows for gathering information on location, event, and physiological data from patients wearing the device respectively (Batko & Slezak, 2022).

One potential challenge to using big data in the clinical system is synthesizing data from diverse sources. Hence, groundbreaking and strategic solid management is essential to ensuring quality control, security, and real-time processing (Wang et al., 2019).

Reference no: EM133701701

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