Data mining is the extraction of hidden predictive information from large database which helps in predicting future trend and behavior thereby helping management make knowledge driven decisions. The data mining tool designed is to aid in quick access and retrieval of patients information to avoid time wasted in retrieving of such data from hospitals data warehouse. The data mining tool was also designed to discover hidden pattern that helps in decision making by management. Structured System Analysis and Design Methodology were used in the analysis of the existing system which also provided a guide for the design of the proposed system.
PHP programming language and my SQL was used in the creation of a data warehouse for patientâ€Ÿs information and data mining tool for the retrieval of such information when needed.
1.1 BACKGROUND OF STUDY
Data mining, is the extraction of hidden predictive information from large database, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge driven decisions. The automated, prospective analysis offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. The scour databases for hidden patterns, finding predictive information those experts may miss because it lies outside their expectations.
Most companies already collect and refine massive quantities of data. Data mining techniques can be implemented rapidly on existing software and hardware platforms to enhance the value of existing information resources, and can be integrated with new products and system as they are brought on-line. Which implemented on high performance client/server or parallel processing computers, data mining tools can analyze massive database to deliver answers to questions such as “Which client are most likely to respond to my next promotional mailing, and Why?”
Data mining techniques are result of a long process research and product development. This evolution began when business data was first stored on computers, continued with improvement in data access, and more recently,
generated technologies that allow users to navigate through their data in real time. Data mining takes this evolutionary process beyond retrospective data access and navigation to prospective and proactive information delivery.
Data mining is ready for application in the business community because it is supported by three technologies that are sufficiently mature: massive data collection, powerful multiprocessor computers and data mining algorithms. In this evolution from business data to business information, each new step has built upon the previous one. For example, dynamic data access is critical for drill-through in data navigation applications, and the ability to store large database is critical to data mining.
The file management is obsolete in developed countries like the United States where and in developing countries like Nigeria the file system is still processed manually in most medical centers; this is as a result of low standard of technology. It was clear that computer is everywhere in Nigeria. These computers are for money making and as a result of this, our hospitals lack computerized services, but with the help of data mining we can also computerize our hospitals.
1.2 STATEMENT OF THE PROBLEM
The problem of data mining has become very crucial in areas of privacy of data. Specifically regarding the source of the data analyzed for certain purpose. My research in Owerri General Hospital here reveals that patients visit the hospital and they waste a lot of time. The patients waits for the nurses or the attendants to get their data and there are volumes of files to search through before the patients files is finally retrieved or the patients might forget his/her card when visit the hospital. It there means that the patientâ€Ÿs data cannot be found due to the fact that the Nurse
does not know the patients number. In this case it is either that the patients is denied treatment by the Doctor or the Nurses will check through the volumes of files in order to retrieved his/her data, this is time consuming problem. There is a problem of misplacing of patients data, the non-availability of relevant forms like x-ray/laboratory forms and chats (pressure chats temperature) and requirement of more workers to carry the folders into the consulting rooms as an evident.
Moreover, there are mistakes in entering patientâ€Ÿs records. Two patients might be given the same number and there could be wrong spelling and loss of important information. There is also lack of space for storing all the files and also due to carelessness on the part of staff.
Furthermore, volume of work for the hospital staff is much; this is because the ratio of patients to staff of Owerri General Hospital is so much. So staffs are over worked and they hurry through their duty, hence they carry out such duties lousily which makes the Doctors unfriendly to their patients.
1.3 OBJECTIVE OF STUDY
Objectives of this research work are to: Create a data warehouse for storage of patientâ€Ÿs information thereby eliminating manual file storage of patientâ€Ÿs records. Design a good data mining tool that will help in easy retrieval of patient information thereby reducing time wastage and improve service delivery. The data mining tool will be able to discover hidden pattern in large volume of data which will help in good decision making.
1.4 SIGNIFICANCE OF STUDY
This research will cover the creation of good database system for the management of patientâ€Ÿs records in Owerri general hospital and also provide efficient data mining tool for easy retrieval of data and discovery of hidden patterns in large volume of data.
1.5 SCOPE OF STUDY
This research work will be carried out on data mining for medical record system of Owerri General Hospital. The work reported in this research could be viewed as a step towards enhancing databases with functionalities.