Big Data Risks and Rewards
Big data in healthcare is abundantly available due to the vast amounts of health data collected from numerous sources such as electronic health records, payers, medical imaging, health research, patient portals, telehealth, and monitoring services (NEJM Catalyst, 2018). Optimally organizing this data and deriving meaningful information can enable the delivery of better healthcare services. Given this, the data produced by current healthcare organizations can have tremendous benefits, despite the challenges of using big data. This discussion will address some of the potential benefits and risks of big data.
Potential benefits
In healthcare, big data can be analyzed to obtain crucial information that can be shared on a real-time basis to enable the provision of appropriate care (Dash et al., 2019). With the increased cost associated with healthcare, organizations and institutions are moving towards providing outpatient care. In this model of care, however, timely interventions are yet to be offered, resulting in increased avoidable use of hospital facilities. Big data and analytics can enable the provision of real-time information that enables timely care. For example, with the increasing use of wearables and other technologies that support remote monitoring of patients, data is sent directly to the cloud for storage (Dash et al., 2019). This data can be analyzed in real-time to enable the identification of trends. For instance, if an alarming increase in the patient’s blood pressure is detected, an alert is sent to the healthcare provider on a real-time basis. Timely interventions such as reaching out to the patient can then be taken to lower the blood pressure.
Long-term trends in the patient’s condition can also inform the most appropriate interventions that produce the most desirable outcomes. This is in addition to enabling data-driven services, where healthcare providers rely on existing data to determine the risk factors faced by the patient and the additional screenings and tests as needed (NEJM Catalyst, 2018). This will improve the treatment options provided to patients.
Potential Risks and Challenges
One of the potential challenges of big data is data aggregation (NEJM Catalyst, 2018). Patient data is spread across different organizations, including hospitals, government agencies, payers, servers, and administrative offices. Due to this aggregation, it is challenging to organize the data since it requires tremendous effort and collaboration between and among the organizations and institutions involved. Another challenge is the varying degrees of data accuracy and quality. Given that the data is recorded and stored in varying formats, others in paper format and others using the electronic health records system, accuracy varies from organization to organization (NEJM Catalyst, 2018). This presents another challenge when analyzing and utilizing big data to inform healthcare outcomes.
Potential Solutions
One of the possible solutions to the identified challenge is to use big data warehouses. Big data warehouses can store massive amounts of data from different sources such as the EHR, clinical data, payers, and public health records (Dash et l., 2019). With the data stored in one place, analytic algorithms can analyze the data and obtain meaningful and smarter healthcare options. Ensuring that the data is structured and accurate is also crucial to ensure compatibility and simplified. This can be attained by ensuring that big data is pooled together or contextualized to increase its relevancy to a specific group or category (Fatt & Ramadas, 2018).
In summary, big data has the potential to revolutionize healthcare and offer solutions to improve patient care. However, all stakeholders, including providers, payers, and policymakers, must collaborate and work together to reinvent efficient and compatible healthcare systems. Accordingly, the role of data experts such as nursing informaticists, IT experts, and data engineers will continue to grow.
References
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6, 54. https://doi.org/10.1186/s40537-019-0217-0
Fatt, Q. K., & Ramadas, A. (2018). The Usefulness and Challenges of Big Data in Healthcare. Journal of Healthcare Communications, 3(2), 21. https://doi.org/10.4172/2472- 1654.100131
NEJM Catalyst. (2018). Healthcare Big Data and the Promise of Value-Based Care. https://catalyst.nejm.org/doi/full/10.1056/CAT.18.0290
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Big Data Risks and Rewards
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