SHB: Collaborative Research:Context-aware, dynamic, smart checklists: key cyber-infrastructure for systems delivering quality health care

点击翻译按钮获取中文摘要

This project will develop and evaluate a prototype system to provide on-line process monitoring and guidance to the performers of health care processes. An Institute of Medicine report has estimated that nearly 100,000 people per year die in US hospitals from preventable errors, and subsequent reports have suggested that many of these errors arise due to the complexity of hospital processes. The project will demonstrate how contextual information (retrospective, current, and prospective) can be used to provide process performers with timely information that could reduce errors, provide expedited warnings of impending hazards, and improve outcomes. Techniques to accumulate and represent historical data will be developed and will feed into profile-based analysis techniques that will evaluate probabilities and support making fine-grained process distinctions. These capabilities will provide a strong technological foundation for evidence-based, continuous process improvement.Project technologies will be evaluated first using synthetic event streams generated by process model driven simulations, then by human simulations with nursing students using patient mannequins, and finally with medical professionals in simulated clinical settings. Processes to be examined include blood transfusion, chemotherapy, medication administration, and patient identification verification. Early community success in applying medical checklists and recent experimental results with proactive process guidance in a hospital emergency department are positive indications that the approaches proposed here have an excellent chance of gaining acceptance and improving medical outcomes. Moreover, the technologies developed here, although evaluated specifically for health care, will also apply to human-intensive systems increasingly employed in a wide range of domains in society. The validated medical processes and the proposed prototype will be an effective framework for educating medical professionals in current best practices. This project will also educate computer science and engineering students about the challenges posed by the medical domain, encouraging a new generation of specialists in this emerging interdisciplinary field. Its societal appeal will also help engage bright, energetic minority and female students thereby helping broaden the participation of underrepresented groups in STEM generally and in computer science and engineering particularly.