The IDN-Based Universal System of Information and Discordance Process

The US, while spending far more of its GDP on health care, ranks among the worst performing members of all the western industrial nations. According to CMS, that figure was 4.4 trillion dollars in 2022 and is expected to exceed 6.8 trillion by 2030. Despite these figures, 44 percent of all Americans struggle to pay for their health care. The purpose of this book is to define most important sources for this excessive health-care costs and inefficiency in the US and describe methods to rectify those serious shortcomings. Human error is one of the leading causes for health-care ineffectiveness and wastefulness and is brought about by factors such as fatigue, time pressure, workload, omission, repetition, distraction, and insufficient knowledge. Among other contributing factors include shortage of staff mostly because of too much paperwork routines, administrative burdens, material management, and so on. The described universal system of information works closely with its users and substantially lightens all the above alluded to overheavy burdens. This system uses an interdepartmental network (IDN) method for managing a total patient care in all arenas of care. It constantly monitors the entire health-care data and interacts with its users. Any piece of information is quantified with a score and used as an option (operating factor) that must discord (compete) with other related options to best satisfy a specific objective (core factor). This process is called contextual quantification. The system is constantly in touch with the users, and if there is a need, it continually recommends corrective steps. However, it is always the user who ultimately must make the final decision. Being a physician, in this book, my focus has been on health sciences subgroup A (human medicine). With some modification, however, this IDN-based universal system of information can be applicable to other disciplines as well.