Factors influencing machine learning application procurement in healthcare organisations

Abstract

In the evolving landscape of healthcare, the advent of artificial intelligence (AI) has ushered in a transformative era, particularly with the prominence of machine learning (ML) applications. This research delves deep into the nuances influencing procurement decisions related to ML applications, drawing insights from interviews with five industry experts. Guided by the Technology-Organization-Environment (TOE) framework, this study clarifies the intricate factors for the successful adoption and seamless integration of ML applications in healthcare settings. The main findings highlight the paramount importance of data security, the weight of stakeholder perspectives, the rigorous of regulatory compliance, and the dynamics of inter-vendor relationships. The study further sheds light on healthcare organisations' complexities when steering through the procurement process, underscoring the value of nurturing strategic alliances with vendors. Concluding, the research offers actionable recommendations for healthcare entities and ML vendors, advocating for a seamless convergence of technology and healthcare.