Healthcare and Data Mining

Data mining is the extraction of all data of a person may it be from previous, present and future data. This also helps predict future trends and behaviors from past events to make better knowledge-driven decisions which could help businesses to be more proactive. Data mining can help organize the clustered data and make it easier for experts to find all the information they need faster than before. There are two methods given in order to understand deeper the algorithms that are being used up to this day. These two methods are; classical techniques: statistics, neighborhoods and rules, and next generation techniques: tree networks and rules.

All of this basically means that with all the previous information given, they are all summarized and arranged by categories making data easier to be found. By this you are able to “discover hidden value in your data warehouse”. This industry has benefited many industries improve their business to browse and locate a large database to find the information that they need.
With data mining, the most commonly used techniques are artificial neural networks, decision trees, genetic algorithms, nearest neighborhood method and rule induction. All these technologies have been used for more than a decade but with only a small volume of data. But now, these capabilities are developing to incorporate with industry-standard data warehouse and OLAP platforms in order for them to store a higher volume of data.

In healthcare, data mining is a great way to be used. Given that they may have a new patient with cancer they can use data mining to gather all the information from previous patients that they have treated and gather the facts that can help their new patient. This is called the clustering technique. This is a possible way to determine which country contains a certain type of illness or which kind of illness affects a majority amount of people in a certain time or season. Data mining is a faster way for them to get that information and may be able to formulate a possible cure. If for example the hospital wants to know more details about how to treat cancer, you can have an answer for one way of treating the cancer but you then apply a new technique of treating the cancer and you do not know the outcome, that type of data mining is called modeling.

Hospitals in the United States of America use data mining tools to gather information from laboratories where the data mining tools have algorithms that tallies results which will be processed to be analytical values to show the trends of a spreading infection. Before, they manually track infections, but they saw the idea of having IT (Information Technology) integrated with their laboratories. These tools will save a lot of time for infection control professionals to detect the patterns of an infection increasing its number of victims. (via)

Some hospitals use data mining for optimization of patient flow. They implemented computerized bed management systems and electronic medical records, large databases are created that could support improved managerial and clinical decision making to improve patient access and quality of care. (via)

Although different hospitals use different data mining tools and different models of DBMS (Database Management System), but how their HIS (Hospital Information System) processes the data and information are highly similar.

In a business point of view, data mining will truly have an advantage in the future and be a success. Before, there may have been possible errors with the way they gather data or information but now with this new technology, people will be able to gather information and come back with less or maybe even zero errors. Market basket analysis is another example of data mining for business. A store may record which kinds of footwear are sold more, may it be shoes or slippers, a data mining system may be able to predict which ones prefer shoes or slippers. They can use this example to calculate the behavior of customers which then they are able to increase their sales, make discount plans, promotions and make a store design. Another possible example for data mining in business is that when stores call random people about a certain sale, the data mining technique may already predict ahead of time which people would most likely respond to that sale. Therefore, there may be more outcomes and more benefits to that company with the help of data mining technology.


Data mining is fast therefore it saves time and man power which shows how effective it will when it is applied to an industry. It will also return less errors because it's automated thus it shows its efficiency. Heavy algorithms can be applied for analysis. Years of computation can be done in months, months in days and days in seconds. It is an industry's surveillance, its memory, its calculator, it's a part of an industry's brain.

Overall, data mining will surely be a benefit to technology.