Monitoramento de pacientes homecare: uma abordagem utilizando banco de dados em tempo real

Abstract

Lately the amount of people who need care in public and private hospitals is growing due, among other factors, the increase of the world population and the delay in the treatment of patients. This is a serious problem faced by administrators of hospitals that each day is more difficult to provide a quality service to those who demand. One of the ways to improve the quality of patient care may be through the development of systems of homecare that empowers the patient receives a clinical treatment of quality directly into their residence. However, the home environment can become complex, since many times the caregiver is someone's own family and doesn’t have the correct technique of monitoring or is inattentive in function of the wear caused by intense care to the patient Thus, it is important for the development of solutions that reduce the overhead of the caregiver, the step in which the patient continue being monitored. One way to achieve such solutions is through the application of concepts of pervasive computing environments at home. In this way, the environment is only populated for sensors and other computing devices, where the patient can be monitored constantly and the environment can adapt to the needs of this user, anticipating to situations of risk according to the current context. Thus, the proposed architecture uses concepts of pervasive computing by providing access to information at any time and regardless of the place where the patient is, once an environment homecare has a high degree of dynamics of the people involved. For the treatment of the data that will be collected by the sensors is need of a technology that perform the data in real time, id est, in a timely manner so that it made the decision-making by health professionals. In this way, it uses a real-time database to deal with data and transactions in real time while ensuring the logical consistency and temporal of same, in addition to managing large volumes of data. Thus, the specification of the system was modeled in UML and consequently the definition