Welcome to the New World: Data Mining in Healthcare

In the ancient world, people used recording books and parchment papers to file confidential information and they kept them locked in storehouses. However, they could not prevent them from being worn, lost, burned, stolen, or etc. In today’s world, things have changed substantially.

‘Knowledge is power’ is therefore not only a famous Game of Thrones line but also an expression describing today’s digital world in total. In today’s society, almost everyone can hold the power and keep it. Thanks to digitalization, “mining” is not only a term used for the definition of digging gold or gemstones anymore. It also has a digital meaning about obtaining and collecting the data, therebeside, storing it safe and secure.

 

With the growth of technology, data mining is a much easier and more practical way of knowledge discovery in the database process. Thus, data science methodology is used for gathering, processing and analyzing the data when practicing the data mining methods. Thanks to data mining, there can be an analysis of historical data in business intelligence (BI) and advanced analytics applications.

Furthermore, data mining is effective in fraud detection, risk management, and cybersecurity planning. Regarding all of this, it plays a major role in healthcare, government, scientific research, mathematics, sports and so on.

 

 

What is Data Mining in Healthcare?

 

Today, the data mining process has a great deal of importance especially in healthcare. As much as the pool of health information keeps growing, the processing and interpreting of medical big data becomes much more difficult. For this reason, data mining in healthcare is basically used for optimizing costs, improving patient outcomes and preventing fraud.

Thanks to the use of data mining in healthcare, data can be formed into a compiled, meaningful and large block of information from segmented data by exploring and analyzing it, so any medical organization can have a major strategic advantage. Owing to a huge amount of data, doctors can compare their patients’ history and symptoms with current clinical research or similar cases so that doctors can make more conclusive and evidence-based diagnoses in a short time.

For the early detection of symptoms and abnormalities, data mining helps blood tests and X-Ray or MR images get analyzed and classified as soon as possible. With the speed and accuracy of interpretation of the patients’ condition, the available treatment plans, comparing their efficiency, and selecting the best one become much easier.

Data mining helps the detection of not only the symptoms but also the risks of using dangerous drugs. All medical staff and patients can benefit from a system that can track the chemical composition of medications and analyze the research and clinical data.

 

Hospitals can schedule follow-up visits and prevent readmissions because they can predict the possible complications and recovery timelines according to the detected previous similar cases. Besides, customers’ pharmacy purchases can be tracked as well, which enables the doctors to follow patient’s treatment plans.

 

 

The Future of Data Mining in Healthcare

 

Now, with the use of electronic health records, the knowledge across all sectors of healthcare can be much more reachable. Approximately 30% of all global data has been produced by the healthcare industry and according to the predictions, this quantity will reach 36% by 2025. This means that there will be more developments in the reducement of medical errors and improvements of patients’ care and satisfaction.

It is quite possible to say for the future of healthcare that the decreasing of healthcare costs, identifying treatment plans and best practices, measuring effectiveness, detecting fraudulent insurance and medical claims, and improving the standards of patient care might depend on the use of data mining.