Is Big Data the Wave of the Future in Healthcare Analytics?
The rising use cases of big data in numerous biosciences applications, particularly genomic sequencing and drug discovery, have also aided the growth of big data in healthcare market. Furthermore, the healthcare industry is seeing an increase in demand for low-cost big data software and services.
IoT
The use of IoT and big data in healthcare analytics has many benefits. These technologies enable hospitals and healthcare systems to collect and analyze data from various sources, including sensors and patient data. As a result, these technologies can be used to understand patient data better, improve the quality of care, and improve personnel health monitoring.
For example, IoT and big data can help doctors monitor patients remotely. With these technologies, physicians can send live health videos to patients unable to attend appointments. As a result, it can help to decrease the risk of serious conditions going unnoticed. Additionally, connected devices and smart sensors can help doctors to detect accidents and medical anomalies. For example, if an elderly patient falls at home, a connected device can send a signal to a doctor, allowing an emergency team to reach them as quickly as possible. Connected devices can also give doctors accurate information about patients in transit, such as their critical conditions.
Cloud
Big data and cloud analytics have many benefits for medical organizations. They help medical organizations better understand the data they collect and enable the medical industry to share that information with others. Medical professionals can make better decisions for patients with this data, and they can improve treatment processes and preventive measures. Using cloud-based data analytics allows medical organizations to keep up with the fast-changing medical field while reducing their initial capital costs.
One example is the use of big data in electronic health records. These records include patient demographics, medical history, medications, and diagnoses. The information is stored in secure information systems, and physicians can view it to make informed decisions. The data can also trigger alerts and track prescriptions.
Challenges
Big data in healthcare analytics offers new opportunities and challenges for healthcare organizations. Organizations need to create a comprehensive platform for healthcare data exchange to take advantage of big data. This ecosystem should integrate healthcare data from hospitals and clinics into a single repository. However, this approach will require a significant investment of resources.
Data from various systems must be sorted and shared appropriately to create meaningful and actionable insights. Healthcare organizations often use artificial intelligence (AI) and machine learning to process data. This data is often vast and difficult to manage. As a result, it is important to ensure the right people have access to it.
Benefits
Using big data analytics in the healthcare industry has several benefits for patients, physicians, and medical facilities. The resulting information can improve the quality of patient care, lower healthcare costs, and optimize the staffing and resources of healthcare providers. The data can also improve the supply chain and forecast resource needs, such as drugs.
One example of this is prescription error reduction. Prescription errors can lead to serious medical problems. These mistakes can lead to death or injury for patients. Fortunately, big data helps reduce these errors by analyzing patient records and flagging anomalies.
Security
Big data security in healthcare analytics is an important issue because a personal data breach can have dramatic consequences. Fortunately, many organizations are using analytics to protect themselves from security threats. These analytics tools can identify suspicious patterns in network traffic, which may be indicators of a cyber-attack. While these analytics tools can be helpful, they also introduce security issues. Some fear that using big data will leave organizations more exposed to threats. However, advances in security technology can help.
To secure big data in healthcare analytics, a hospital must consider its security practices. Big data in healthcare analytics is a complex technology, and strict security measures are critical. Healthcare institutions must invest in the appropriate technology and staff to create an effective security system. For example, hospitals should employ data scientists to secure their analytics platforms. Ultimately, big data analytics can improve healthcare quality and make organizations more efficient.
