Is Your Automated Healthcare Information Secure?

Author(s):  
Mhamed Zineddine

Information security issues are a serious matter that organizations from all industries have to deal with. The healthcare industry is no exception. Personally identifiable healthcare information automated by the healthcare industry can be stolen, intercepted, altered, and misused. Acceptable safeguards, therefore, have to be in place in order to ensure the privacy and protection of this information. Without governmental intervention however, it seems unlikely that the healthcare industry will voluntarily implement such safeguards. The Health Insurance Portability and Accountability Act (HIPAA) security rule has emerged and been mandated by Congress from the need of such intervention. The quantitative investigation in this chapter is aimed at determining if covered entities in Washington State are HIPAA security rule ready after two years from the compliance deadline, and if the factors identified through the literature review are a hindrance to HIPAA security rule compliance. This research study revealed that HIPAA Security Rule full compliance is far from achieved; many factors have emerged as impediments to the compliance process, and the way to compliance is complex and costly. Tracking the compliance progress within healthcare institutions in Washington State over the last five years revealed that the reaction to the HIPAA Security Rule was strong around the mandated date; the response after the mandated date, however, has been weak. Covered entities should brace themselves to the new level of enforcement due to the recent American Recovery Reinvestment Act (ARRA).

Author(s):  
Carla Farinha ◽  
Miguel Mira da Silva

Healthcare Information Systems (HIS) are essential in the healthcare industry since they manipulate vital information. For example, HIS may keep track of the patient’s medical history, avoiding mistakes with medications, dosages, and treatments. However, the traditional methods for identifying HIS requirements focus on specifying functional requirements for the software. Moreover, system scope should be fully understood by stakeholders, such as healthcare workers and hospital managers, something extremely difficult to achieve in practice. As such, many requirements are incomplete, missing, or not needed, leading to expensive and inadequate HIS. The authors identify requirements for Healthcare Information System using Focus Groups. They evaluate this method with experiments, applying a variety of techniques and having encouraging preliminary results. In particular, they verify that stakeholders can reach consensus on high-level requirements by discussing different perspectives about the system scope. The authors conclude that Focus Groups are really effective.


Author(s):  
V. Jeevika Tharini ◽  
S. Vijayarani

One of the best-known features of IoT is automation. Because of this, IoT is a much-needed field for many applications, namely emergency and healthcare domains. IoT has made many revolutionary changes in the healthcare industry. IoT paves the way to numerous advancements for healthcare. The possibilities of IoT have reached their peak in the commercial industry and health sector. In recent years, serious concerns have been raised over the control and access of one's individual information. Privacy and security of the IoT devices can be compromised by intruders. Apart from the numerous benefits of IoTs, there are several security and privacy concerns to consider. A brief overview of different kinds of security attacks, solution for the attacks, privacy and security issues are discussed in this chapter.


2020 ◽  
pp. 370-394
Author(s):  
Say Yen Teoh ◽  
Shun Cai

Despite many attempts to introduce computerization in the healthcare industry, the majority of the current healthcare information systems still fail to meet the rising expectations of patients for service. This study aims to understand how agility and innovation capabilities can be strategically nurtured, developed, and managed to upgrade the quality of healthcare services. Based on a case study, a process model is developed to explain that an agile innovation strategy is a complex helix process involving a firm's sensitivity and responsiveness to integrating and reconfiguring its resources to cope with innovative change. Three key managerial contributions for IT and medical practitioners are presented.


2020 ◽  
Vol 12 (24) ◽  
pp. 10662
Author(s):  
Chih-Hao Yang ◽  
Hsiu-Li Lee ◽  
Wen-Hsien Tsai ◽  
Sophia Chuang

Smart city and smart hospital development comprise a mainstream strategy worldwide to enhance the achievement of Sustainable Development Goals (SDGs) and Corporate Social Responsibility (CSR) practices. The smart healthcare industry needs to optimize its smart healthcare information strategies, creating the process-activity value and reducing the cost of healthcare without sacrificing the quality of patient care. This study proposes an decision model of Activity-Based Costing (ABC) concept and Multi-Criteria Decision-Making (MCDM) techniques that integrates the Decision-Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Processes (ANP), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Zero-One Goal Programming (ZOGP) to achieve optimal smart healthcare information system portfolio strategy decisions. The resulting data shows that the perspective of government policy support and the criterion of Minimize Equipment Maintenance Costs are the most significant evaluation factors, and that the Health Data Informational System and Hospital Device and Drug Management System comprise by far the optimal portfolio of smart healthcare information system which strengthen the connection between ABC and MCDM techniques in evaluation process. The major contributions of this study are as follows: (1) the proposed model contributes to the management accounting innovation development of a sustainable city and Operation Research (OR) application; (2) the integrated model can promote the smart healthcare industry development and help decision makers to more accurately understand how to allocate resources and planning for intelligent-related activities to each smart healthcare information system through appropriate cost drivers.


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