Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why.

Big Data Risks and Rewards in Healthcare Systems

Big data in the healthcare sector refers to the data generated from all interactions between the healthcare system’s patients, healthcare providers, and stakeholders. These data are mainly collected from various healthcare systems and fields, such as medical devices, electronic health records, ward rounds records, pharmaceutical research, and clinical trials (Dash et al., 2019). As part of healthcare organizations, nurses may also obtain these big data from the internet, patient portals, public records, and other relevant healthcare fields.

According to the study of Big Data in public health, “Telemedicine and Healthcare of European Commission” (Habl et al., 2016), the outcome indicated several potential benefits to the health sector. The availability of big data increases the early diagnosis of several conditions, promoting quality and effective early treatment. These data when available, a patient with a specific condition is detected in the early stages (Habl et al., 2016). A disease at an early stage is confined within a particular region within the body regions. The outcome of such early diagnosis is a selection of appropriate treatment methods for the identified condition that will tend to eliminate it. Other potential benefits include identifying prevention tools against certain diseases and increasing pharmacovigilance and patient monitoring.

The major challenge of data fragmentation and lack of digitization uniformity is obstructed efficiency. The data fragmentation results in many small data being overlooked either because the data was not recorded or they were lost (Hong et al., 2018). This results in the unavailability of accurate data on many records, impeding their credibility; hence, applying such data in clinical stages is not easy. For example, in the US, the decentralization of various health facilities makes obtaining all the required data difficult, as some facilities still operate manually. The data can easily get lost, or the machines to record them might not be available. Increasing the levels of digitization in such areas by installing computers and trained personnel will aid in curbing such challenges.

References

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis, and prospects. Journal of Big Data, 6(1), 1-25.

Habl, C., Renner, A. T., Bobek, J., & Laschkolnig, A. (2016). Study on Big Data in public health, telemedicine, and healthcare. https://jasmin.goeg.at/893/

Hong, L., Luo, M., Wang, R., Lu, P., Lu, W., & Lu, L. (2018). Big data in health care: Applications and challenges. Data and information management, 2(3), 175-197.