Abstract
The safety of critically ill patients in intensive care units is an important aspect of medical care. Many human factors contribute to deficiencies and errors in patient care in the intensive care setting, such as long working hours, high levels of stress, lack of enough people, may cause human errors and affecting the effectiveness of the decisions of the physician. Several attempts have been made to increase the effectiveness of such decisions by issuing early alerts on adverse patient conditions. However, such alerts are based on single parameter variations, and not on the relationship between multiple parameter variations. We developed a computer-based model is an integrated solution which identifies adverse patient events based on multiple parameter variations, and then provides predictive treatment suggestions based on the likely clinical conditions which result in the parameter variations. The proposed system follows an interactive communication cycle in order to properly notify the responsible treating physicians at different tiers of responsibility. Our model is capable of early identification of adverse conditions and providing suitable treatment suggestions, thus acting as a decision support system to assist the treating physician. DOI: 10.4038/sljcc.v1i1.942
Highlights
The safety of critically ill patients in intensive care units (ICUs) is an important aspect of medical care
A variety of factors influence the occurrence of human error, such as the level of training and experience of the doctor/nurse, their attitudes and dedication towards work, whether the doctor/nurse is tired or overworked, lack of adequate staff, and technical issues, such as delay in investigations reaching the bedside from the laboratory, and simple human error
The rule based system consists of a rule shown in Figure 4. which defines the relationship between set of above monitored parameters and the set of conclusions and treatment suggestions that would prompt when such relationship is identified
Summary
The safety of critically ill patients in intensive care units (ICUs) is an important aspect of medical care. In ICU, several parameters are measured in real time to monitor the progression of illness. These different parameters are all intricately linked to each other, each parameter affecting the other, and vice versa. These interactions are governed by complex but standard physiological principles, and are predictable. Human error occurs all too frequently in patient care, especially in ICUs. Parameters or parameter trends which forewarn the development of serious adverse outcomes can be missed by the attending doctor or nurse. A variety of factors influence the occurrence of human error, such as the level of training and experience of the doctor/nurse, their attitudes and dedication towards work, whether the doctor/nurse is tired or overworked, lack of adequate staff, and technical issues, such as delay in investigations reaching the bedside from the laboratory, and simple human error
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