Benefits and Challenges of Big Data

Benefits and Challenges of Big Data

Big data can be defined as the large and complex electronic health data sets that are difficult to handle with traditional software/hardware or common data management methods and tools. Big data includes clinical data from CPOE and clinical decision support system (physician’s written notes, prescriptions, laboratory, medical imaging, insurance, pharmacy, and other administrative data), patient data in electronic patient records, machine generated data (monitoring vital signs, social media posts, and web pages), and less patient-specific information (emergency care data, articles in medical journals, and news feeds) (Raghupathi & Raghupathi, 2014). Big data analytics in healthcare is evolving rapidly. As technology has advanced, healthcare organizations now can collect, analyze, and mange large amounts of data. There was a report saying that the data from United States healthcare system alone reached 150 exabytes in 2011. At this rate, it is soon going to reach the zettabyt and yottabyte scale. Kaiser Permanente, the California-based health network, has more than 9 million members, and they have approximately between 26.5 to 44 petabytes of data from EHRs, including annotations and images (Raghupathi & Raghupathi, 2014).

Nowadays, big data analytics in healthcare helps improve quality of care and patient outcomes and reduce healthcare costs by finding patterns, associations, and trends within the data. One of the most current and relevant big data analytic examples in healthcare is quick development of COVID-19 vaccines. Since researches could share information with each other, they were able to develop advanced medications very rapidly. Big data analytics in healthcare also helped us predicted and analyzed the spread of disease. It allowed us to manage and fight this pandemic more efficiently.

Although the potential of big data is enormous, there are also remaining challenges to overcome. For instance, healthcare cybersecurity and information privacy are one of the concerns that come with the big data. Data security is one of the priorities in the healthcare organizations, which are at high risk of rapid-fire series of high profile breaches, ransomware episodes, and hackings. In addition, many healthcare organizations are lack of adequate databases, systems, and the skilled staffs to mange big data (Touro College Illinois, 2021).

Strategies of Using Big Data

Many healthcare organizations and healthcare searchers are working to address and find solutions to these issues and to facilitate the use of big data analytics in healthcare field. Some strategies will include following (Kent, 2020).

1. Provide comprehensive, quality training data.

2. Eliminate bias in data and algorithms.

3. Develop quality tools while preserving patient privacy.

4. Ensure providers trust and support analytics tools.

References

Kent, J. (2020, October 2). 4 Emerging Strategies to Advance Big Data Analytics in Healthcare. Retrieved from https://healthitanalytics.com/news/4-emerging-strategies-to-advance-big-data-analytics-in-healthcare