Client-Server Computing

Client-server architecture is a local area network (LAN) based computing environment in which a central database sever or engine performs all database commands sent to it from client workstations, and application programs on each client concentrate on user interface functions. Client-server computing is a phrase used to describe a model for computer networking. In this shared processing model, a server has an intelligent database engine functioning as a service on the network. This model offers an efficient way to provide data/ information and services to many users as needed. A network connection is only made when a user needs to access the information or obtain the needed service. This lack of a continuous network connection provides network efficiency. Any change made in the server is transparent to clients.

Understanding Success and Failure of Healthcare Information Systems

Some health care information systems (HCIS) do succeed, but the majority are likely to fail in some way. To explain why this happens, and how failure rates may be reduced, the chapter describes the “ITPOSMO” model of conception-reality gaps. This argues that the greater the change gap between current realities and the design conceptions (i.e., requirements and assumptions) of a new healthcare information system, the greater the risk of failure. Three archetypal large design-reality gaps affect the HCIS domain and are associated with an increased risk of failure: • Rationality—reality gaps: that arise from the formal, rational way in which many HCIS are conceived, which mismatches the behavioral realities of some healthcare organizations. • Private—public sector gaps: that arise from application in public sector contexts of HCIS developed for the private sector. • Country gaps: that arise from application in one country of HCIS developed in a different country.

An Intelligent Data Mining System to Detect Healthcare Fraud

There are various forms of fraud in the health care industry. This fraud has a substantial financial impact on the cost of providing healthcare. Money wasted on fraud will be unavailable for the diagnosis and treatment of legitimate illnesses. The rising costs of and the potential adverse affects on quality healthcare have encouraged organizations to institute measures for detecting fraud and intercepting erroneous payments. Current fraud detection approaches are largely reactive in nature. Fraud occurs, and various schemes are used to detect this fraud afterwards. Corrective action then is instituted to alleviate the consequences. This chapter presents a proactive approach to detection based on artificial intelligence methodology. In particular, we propose the use of data mining and classification rules to determine the existence or non-existence of fraud patterns in the available data. The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice.

The Use of Artificial Intelligence Techniques and Applications in the Medical Domain

In recent years we have witnessed sweeping developments in information technology. Currently, the most promising and interesting domain seemed to be the artificial intelligence. Within this field we see now a growing interest in the medical applications. The purpose of this article is to present a general review of the main areas of artificial intelligence and its applications to the medical domain. The review will focus on artificial intelligence applications to radiology, robotically-operated surgical procedures and different kinds of expert systems.

Telemedicine and the Information Highway

Health systems broaden their importance in the midst of the ongoing international communications revolution. Health services are a natural candidate to become an integral part of the “information highway”. Terms such as telemedicine, telehealth, teleradiology, and teledermatology have been integrated into technical and academic jargon and have become the object of research and organizational planning. Telemedicine is the utilization of electronic technology to send medical data from one location to another. Supporting technology may be anything from a simple telephone, to complex communication satellite, and modern, videoconference equipment. The term telemedicine is used to define the practice of medicine through communication technology. These two ancient words, medicine and communication, were first linked at the beginning of the 20th century, when ships used radio communication to receive medical assistance. It was only in the early 1960s, however, that link became truly significant. When we discuss communication from the technological aspect, we refer to the means permitting widespread transfer of information.

Health Information Management and Individual Privacy

The chapter reports on recent developments in the management of health information in New Zealand and the implications these initiatives have raised regarding individual privacy. Set up in 1993 to implement the country’s health information strategy, the New Zealand Health Information Service (NZHIS) has recently established a national health register. At the heart of this development are three national databases: the National Health Index, the Medical Warnings System and the National Minimum Data Set. These applications and their functions are presented. Also discussed is a number of other health information management initiatives currently being explored. The chapter contends that these initiatives under the guise of advancing the nation’s health may, instead, be infringing the privacy and confidentiality of the nation’s citizens. The chapter further considers the application of New Zealand’s privacy legislation (the Privacy Act 1993 and the Health Information Privacy Code) to the development of centralised health information management systems. It concludes by considering the possibility of hidden agendas despite the provisions of the nation’s privacy rules.

Diabetes Mellitus - Evaluating the Diagnostic Probabilities

The article examines the behavior of the human decision-maker. It surveys research in which about 90 physicians specializing in various fields and with different degrees of seniority participated. It tackles the question of whether it is possible to found the majority of the knowledge bases of the expert systems on the Bayesian theory. We will discuss the way of decision making conforming to the probabilities evaluated according to the Bayesian theory. The logical conclusion, therefore, is that the development of a knowledge base for an expert system founded on probabilities calculated in accordance with the Bayesian theory must be carried out in a controlled manner and depend on the parameters mentioned above.

Information Security Framework for Health Information Systems

This chapter outlines the major issues related to the security of medical information systems. Medical information systems are unique in this sense that integrity of the records and privacy issues are dominant. The presentation includes the formulation of the basic medical information security tenets as well as the discussion of the major components of the security subsystem: patient identification, access mechanism, reference monitor, communication subsystem and database subsystem. Also examples of privacy law are quoted and discussed.

Designing Hospital Information Systems

Anyone working in the area of hospital information systems is sooner or later amazed about the intrinsic complexity of the field. Finding ways to handle this complexity seems utterly important. In this chapter we present a user-oriented, document-based approach being developed and proven in cooperation projects with hospitals. The advantage of the proposed approach lies in the provision of means for handling different sources of complexity. The approach is characterized by an intended continuous switch between an organizational and workplace perspective in order to reduce complexity by changing the levels of detail. It initiates and supports ongoing negotiation processes among the heterogeneous user groups by providing user-oriented, easy-to-understand documents. Furthermore, it enables developers and users alike to represent and discuss current and future work practices including interim solutions of future system support.

Healthcare Process Redesign

In this chapter, we present key principles and the limitations of business process reengineering (BPR) in general, and the use of BPR in healthcare in particular. We then present a case study of reengineering a healthcare process. The purpose of this case study is to explore the reality of how a BPR project is initiated, formulated, and implemented in a hospital setting and how it can fail. In the final discussion, we analyze the possible reasons for the failure of the BPR project and discuss their implication to the implementation of BPR in general.