Artificial Intelligence for Adaptive Planning of Healthcare Projects

Abstract

Planning and managing healthcare projects involves making decisions in conditions of high uncertainty due to a complex and turbulent environment, technological transformation, and the use of largely subjective resources of tacit knowledge possessed by project managers as a result of accumulated years of experience. It is desirable to look for solutions that allow for the creation of flexible and agile systems supporting the management of updated knowledge resources, enabling dynamic adaptation to current problems and changing environmental conditions. One possible solution is using intelligent systems that would support adaptive planning. The paper aims to present an AI model for knowledge management in adaptive planning of healthcare projects, which are usually complex, expensive, and require efficiently updated interdisciplinary scientific knowledge. Additionally, such projects often only have generally formulated goals and planned results, which makes their definition, planning, and initial evaluation much more difficult. Thanks to the conclusions drawn from this research, it is possible to reduce the number of errors made during project planning, which usually significantly affect the implementation and success of projects. It is justified to develop interdisciplinary research conducted on the border of healthcare project planning and AI computing systems because expert planning methods dominate, and there is a lack of adequate support. Implementing this type of research and its further continuation allows for the creation of knowledge and methodological solutions related to introducing AI computation to healthcare projects to assist agile decision-making.