A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

Length of Stay in Intensive Care Units - A Case Base Evaluation

As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge.

Self-care in older people with functional deficit: needs of long-term care.

The group of 65-year-olds is becoming more numerous and with greater needs for health care. So, is necessary the reflection about new models of provision, organization, and allocation of health resources. According to the United Nations Organization, 2015, in 2050 elderly people will reach two million people (20% of the world’s population), what mean that the number of people over 60 years old will exceed a population of young people under 15 years. Parallel to aging, less healthy lifestyles have contributed to the prevalence of chronic diseases, especially cerebrovascular diseases. Hypertension and diabetes mellitus are risk factors and increase predisposition to other diseases. With aging, there is an increased risk for developing chronic, oncological and degenerative diseases, which account for more than 50% of the burden of diseases, with profound implications on independency, use of health care and services.