Handbook on Intelligent Healthcare Analytics

The main challenge in big data is to handle and manage the huge amount of assorted, complex, and interconnected information. It is difficult to sort out the data and prioritize the data because of its volume and variety.

Major big data challenges are as follows:

• Lack of proper understanding of the big data

• Data growth

• Combining data from various sources

• Selection of big data tool to capture, store, process, and analysis

• Data security

The healthcare data and its analytics have problems like data accuracy, data security, data sharing, data capturing, and data visualization. The following are the major challenges faced by healthcare organizations with big data [10, 21, 22, 28].

The main problems in healthcare big data are capturing data. The qualities of the clinical decisions are based on how well the big data is captured. The healthcare organization improves their data capture method by prioritizing the data based on the values.

Data cleaning is essential as medical data is captured at a variety of data sources. The data cleaning process checks the data for accuracy and correctness and also ensures whether the data are relevant.

The volume of healthcare data grows exponentially with time. It is difficult for the healthcare organization to store the big healthcare data with the traditional database and in a single system.

Data security is the major challenge in the healthcare industry because of the frequent hackings. The challenges of healthcare providers are data encryption, data masking, and other protection methods for the limited data access to the outside people.

Sometimes, there is a gap between the administrative data and the clinical system. Example: variation in the treatment code and the care given to the patients.

The standard of collecting and storing the big data is different from one healthcare organization with another healthcare organization. The sharing and integrating the different formats of medical records are the real problem with medical data.

The healthcare data is not fixed. Most of the patient data requires frequent updates. For better treatment the up to date and real-time patients’ data is necessary. For example, the BP of the patient will vary every day. The old data will lead to wrong decisions in patient’s healthcare practice.

The main challenge in healthcare data is maintaining balance between protections of patient’s sensitive information, data integrity, and the usage of data for the knowledge discovery process [23]. All these challenges of healthcare data are not insoluble. The advanced technologies and new innovations will address all the abovementioned challenges of big data.

The objective of this chapter is to give a general idea about overview and characteristics of big data, different steps for deriving value from big data, big data technologies used for every step in the value chain process, use of knowledge systems in big data healthcare, various big data applications, and big data challenges in healthcare organizations. The healthcare organization needs to devote time and resources for implementing the big data value chain. Health is the precious gift of God to humans. A personalized and sustainable patient care service is the need of the hour. Big data analytics is capable of providing knowledge and valuable insights in medical data, which are useful for clinical decision, disease prediction, better treatment, etc. Healthcare big data is a permanent and continuously increasing phenomenon, which needs newer tools and technologies to analyze the data and to get knowledge for the present use and future research works.

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