Information Technology In Healthcare

I. INTRODUCTION

Healthcare organizations today are capable of generating and collecting a large amounts of data. This increase in volume of data requires automatic way for these data to be extracted when needed. With the use of data mining techniques it is possible to extract interesting and useful knowledge and regularities. Knowledge acquired in this manner, can be used in appropriate area to improve work efficiency and enhance quality of decision making process. Above stated points that there is a great need for new generation of computer theories and tools to help people with extracting useful information from constantly growing volume of digital data [1]. Information technologies are being increasingly implemented in healthcare organizations

Development and implementation of new information technologies that allow global networking, give modern medicine the epithet of “informatical medicine”. Information technologies increasingly provide the help in system approach of solving medical problems [16]. Disposition of the right information enables the preparation of accurate reports, for example, usage of hospital capacities, or number of occupied beds. At the same time it is easier to monitor treatment and to check the information exchange. Use of information technologies enables change of the healthcare system - how to improve public health, the healthcare of the system users, reduce costs, save time and

This is different from standard data mining practice, which simply begins with a set of data without obvious hypothesis [19]. While the traditional data mining is focused on patterns and trends in data sets, data mining in healthcare is more focused on minority that is not in accordance with patterns and trends. The fact that standard data mining is more focused on describing and not explaining the patterns and trends, is the one thing that deepens the difference between standard and healthcare data mining. Healthcare needs these explanations since the small difference can stand between life and death of a patient.

Analytical techniques used in data mining, in most cases have long been known mathematical techniques and algorithms. Although data mining is a young technology, the process of data analysis is nothing new. The thing that linked these techniques and large databases is a cheaper storage space and processing power. Here are some of the techniques of data mining, which are successfully used in healthcare, such as artificial neural networks, decision trees, genetic algorithms and nearest neighbor