Database of Scriptum

At a hospital we find daily activity correspond to medical treatment and other health care business. For example some patients come to internist get some medicine or just routine health check up, some physician get busy treating emergency patient at emergency room, at another place the patient's family go to cashier for paying the bill, etc. It is critical to understand the benefits and limitations of using these large-scale administrative databases. From an evidence-based medicine perspective, these data are important for generating hypotheses but not cause and effect relationships. In other words, the data itself are not specifically collected to address a clinical question, but rather represent a quality assurance process.

The phrase, ‘hospital information system’, is frequently used in discussions about the flow of information throughout a hospital with the assumption that everybody has the same concept in mind. Closer examination shows that this is not necessarily the case. 

Many organizations including modern hospitals are capable of generating and collecting a huge amount of data. This explosive growth of data requires an automated way to extract useful knowledge. Thus, medical domain is a major area for applying data mining. Through data mining, we can extract interesting knowledge and regularities. The discovered knowledge can then be applied in the corresponding field to increase the working efficiency and improve the quality of decision making.

Nowadays, data stored in medical databases are growing in an increasingly rapid way. Analyzing that data is crucial for medical decision making and management. It has been widely recognized that medical data analysis can lead to an enhancement of health care by improving the performance of patient management tasks. There are two main aspects that define the need for medical data analysis.

1. Support of specific knowledge-based problem solving activities through the analysis of patients’ raw data collected in monitoring.
2. Discovery of new knowledge that can be extracted through the analysis of representative collections of example cases, described by symbolic or numeric descriptors.