Developing An IT Risk Assessment Framework

In today’s business environment, almost all information is captured and stored in electronic form. This digital storage of data in a networked environment provides far greater access to information than ever before. But unfortunately, this also exposes the organization to a variety of new threats that can have impact on the confidentiality, integrity, and availability of information. Organizations need a way to understand their information risks and to create new strategies for addressing those risks. A systematic approach to assessing information security risks and developing an appropriate protection strategy is a major component of an effective information security and risk management program. This paper outlines an Analytic Hierarchy Process based approach for analyzing risk factors and sub factors and ascertaining the major areas of security elements where an organization should focus on

Risk Management For Health Information Security And Privacy

The challenge of securing large amounts of electronic medical records stored in a variety of forms and in many locations, while still making it available to authorized users, is huge. Pressure to maintain privacy and protection of personal information is a strong motivating force in the development of security policies. It is essential for health care organizations to analyze, assess and ensure security policies to meet these challenges and to develop the necessary policies to ensure the security of medical information

Approaches To Electronic Health Record Implementation

During last few years, healthcare organizations have been increasingly focused on implementation and use of electronic health records. This article identifies the benefits and challenges in implementing electronic health records utilizing service-oriented architecture. The paper also explores the potential of service-oriented architecture in the development of interoperable electronic health records

A neural network driven fuzzy system approach to decision making

It is necessary to model and manage uncertainties efficiently and effectively in solving decision-making problems. Fuzzy reasoning and logic offers a natural means of handling uncertainty. This paper discus.\u27ses the development of an architecture that utilizes the advantages of fuzzy logic and neural networks that can be used in decision-making. The present paper outlines the reasons that motivate development of models that integrate fuzzy logic and neural networks. This discussion is followed by a brief overview of fuzzy logic and its concepts that are essential in understanding the application presented in the paper. The paper then describes the classification procedure used by the model, which is followed by its application to the decision making problem in construction modularization

Technologies To Improve The Decision-Making Process Of Real Estate Appraisers: XML, Intelligent Agents, Avms, And Web Services

Pressure to expedite mortgage originations has prompted the need to accelerate the appraisal process for residential real estate.  The appraisal aspect of a mortgage origination is one area where decision support can play a major role in redefining the process. This study presents propositions that incorporate new technologies into the decision-making process of a residential real estate appraiser.  The four propositions deal with intelligent agents, XML, automated valuation models (AVMs), and web services. Intelligent agents have the ability to redefine how appraisal firms create, maintain, and update their databases.  XML offers enhanced data handling capabilities, while automated valuation models offer the ability to drastically reduce the time required to render an estimate of value. These two technologies can be combined with web services to make the real estate appraisal application available anywhere and anytime of the day

A neural network model for decision making With application in construction management

In this paper, an innovative approach is presented to decision making using self-organizing multi-layered neural networks. The model helps make a decision whether to use a conventional stick-built method or to use some degree of modularization when building an industrial process plant - a problem considered very important in construction management because of its economic impact. The objective of this paper is to show that both expert system and neural network approaches can be useful for decision making problems. However, in some situations a neural network approach can outperform the expert system approach. A brief overview of prior approach to modular construction decision making is provided in this paper and the reasons for using a neural network approach are also discussed. The architecture, knowledge representation, and training procedure for the neural network paradigms used are described. The performance of the trained neural network system and its comparison with the recommendations provided by human experts and the expert system are also presented

Enhancing Knowledge Management With XML

Knowledge Management involves gathering, categorizing, storing and sharing of knowledge. There are several available tools that can be used to build a knowledge management infrastruc-ture to achieve its goals. This paper discusses issues involved in designing an information Portal using XML-based tools. As compared to traditional HTML-based portals, use of XML offers several benefits - it provides a great way of efficiently aggregating, classifying, and presenting both structured and unstructured content over the Internet or similar networks

Electronic Health Records: Challenges and Opportunities

During the last three decades, healthcare expenditure in the U.S. has substantially increased. If this pace of increase is not controlled, it will lead to disastrous results for the healthcare system. An effective use of health information technology would not only improve the quality of healthcare but help reduce healthcare costs considerably. However, risks of privacy and security of patient electronic health records are great. It is recommended that healthcare organizations use IT management best practices, follow proper risk assessment and management guidelines, and keep up with latest technological advances to ensure the privacy and security of patient data

Knowledge-based simulation model for performance analysis and reliability of computer networks

Modeling and analysis of performance of computer networks is essential for ensuring smooth operation of an organization\u27s networks and preventing major failures. Mathematical analysis and simulation modeling are the common procedures for network system performance analysis. In this paper, a knowledge-based simulation model is developed that can be used for predicting network performance and reliability

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty