April 15, 2023, by Paola Reyes
Doctors, politicians, scientists, and the general public are highly interested in improving the quality of life for human beings, as is the desire to improve the health of people around the world.
Big data plays a fundamental role in this task through the implementation of the collection of patient data, health surveys, researchers of medical conditions, and others.
Huge part of the country resources is sent to monitor health outbreaks, eliminate potential dangers to societies, educate communities.
For the health industry, the governments give a huge part of the country resources to monitor health outbreaks, eliminate potential dangers to societies, educate communities such as schools, universities, and companies to prevent infection transmission, and policies to take care of the health quality of the citizens. To have all the mentioned task complete, technologies such as Hadoop are needed and use.
Use and Incorporation
As seen in Figure 1, Hadoop can be used in a variety of areas in the healthcare industry. For example, in demographics, where based on patients' stored data by sex, location, and symptoms, new illness developments can be detected, as it was with COVID-19. On the other hand, researchers can use historic patient data to identify patterns using machine Figure 1. Hadoop uses in Healthcare (Goel, 2023).
learning and identify what conditions lead to a specific illness or what treatments are successful for a disease.
One key use is the electronic records that allow patients to have their medical history as conditions, medications, procedures, diagnoses, and exam results (Goel, 2023). Thanks to this, the doctors can keep track of the patients' health status and recommend what they consider to be the best treatment plan for them. Also, if the patients decide to change their doctor or move to a different country, they just must take their health history, continue with the treatment, or ask for another point of view.
Another popular use is on fitness trackers. For example, the smart watch and iPhone can track the customer's physical activities, sleep habits, and vital signs and give advice on how to improve your habits, as well as give you alerts when they detect any vital sign outside of your healthy range.
Pros and cons of Hadoop in the healthcare industry
Some of the advantages of Hadoop in the healthcare sector are flexibility, scalability, speed, cost, compatibility, and support for multiple languages.
Scientists that specialize in human health research as well as programmers who make apps for patients use Hadoop's flexibility to access new data sources and switch between them. Furthermore, data can be in a variety of shapes, such as tables, photos, videos, and so on, and this data is well-accepted for Hadoop's architecture because it can store both structured and unstructured data.
Another feature that is well received in the industry is scalability. Each day, more data is available to increase studies, understand human health, and improve it. Therefore, all this data must be stored. Hadoop can store enormous amounts of distributed data across numerous computers running in parallel (Goel, 2023).
The speed of Hadoop is essential for processing health data, since the faster the task can be done, the faster the results can be given to patients, investigators, or apps. Even though the performance is faster, and the storage is bigger than traditional data bases, the costs of Hadoop are lower, which makes more capital available for investigation and the resources needed by the companies.
Most contemporary big data technologies, such as Spark, Flink, and others, are Hadoop-compatible, andin addition, developers can program in different languages such as C++, Python, Ruby, and others, which is highly helpful for the healthcare industry since there are no limitations on the programs and developers that can work on it (dataFlair, 2019).
Even though Hadoop has a long list of benefits, there are certain drawbacks to consider when using this technology in the healthcare sector. These drawbacks include security and the problem with small files. As is common knowledge, medical records contain sensitive information that must be kept secure, especially for patients. However, Hadoop lacks encryption at the storage and network levels. Nevertheless, because Hadoop struggles to handle short documents, developers must spend more effort putting documents together so that Hadoop can use them effectively.
References
DataFlair (2019). Top advantages and disadvantages of Hadoop 3. https://data-flair.training/blogs/advantages-and-disadvantages-of-hadoop/
DataFlair (2020). Top 12 Real Time Big Data Hadoop Applications. https://data-flair.training/blogs/hadoop-applications/
Goel, K. (2023, January 30th). Hadoop Tutorial – Complete Hadoop Guide in 2023. https://intellipaat.com/blog/tutorial/hadoop-tutorial/
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