Resumen de Development of an Ambient Intelligence Environment to improve Patient Safety in Critical Care
In the late 1990’s, when sophisticated personal computers and electronic devices with miniaturized sensors were being mass produced, the concept of ambient intelligence (AmI) emerged. An environment that has AmI is a space containing objects which includes technologies that are not visible to users, and which generates intelligent responses when appropriate. When people interact with an AmI environment, they intuitively use technologies according to their own needs and gain more awareness of their actions, thereby improving their quality of life, comfort, and empowerment.
Currently, healthcare professionals work inside a complex adaptive system in which the clinical environment and the health status of patients vary dynamically, and resources are limited. This can generate an increasing number of adverse events as well as medical errors and consequently patients are more exposed to potential harm during a hospital stay. Many researchers are creating new AmI tools to overcome these challenges. This is especially important in intensive care units (ICUs), where there are seriously ill patients who need advanced infrastructure and equipment to receive continuous clinical monitoring and treatment in as safe a way as possible. Three out of every ten patients in an ICU suffer some type of clinical safety issue, which puts their lives at risk.
In this context, the main aim of the work I present in this thesis is to develop an AmI environment for improving the efficiency of processes related to patient safety in ICUs.
I have written this thesis with the collaboration of the clinical and engineering team of the Smart ICU at the Hospital Clínic in Barcelona (HCB). That AmI environment is equipped mainly with technologies related to the Internet of Things (IoT) that provide an adaptive and dynamic distribution of clinical information based on the role and location of each professional as well as the clinical health status of patients.
I divided the development of this thesis into three phases. Firstly, I designed, built, and tested a prototype to simulate the AmI environment in a laboratory setting, considering the main patient safety issues which arise in ICUs. I considered 5 patient safety issues: a code blue, a code red, a code pink, control of nosocomial infections and drug-related errors. Secondly, that prototype was adapted and implemented in a Smart ICU at HCB.
Thirdly, I collected and analysed data generated by the AmI. It is important to highlight that part of the data collection and analysis related to the AmI environment took place during the SARS-CoV-2 epidemic (Covid-19).
To summarize, my thesis evaluates the efficiency of the use of new technologies to improve patient safety processes in critical care. It improves clinical and educational standards in terms of patient safety processes at the unit concerned. Moreover, it enables quantification of events related to patient safety as well as heightening awareness of them.
