Socio-Technical Risk Analysis for the Digitalized Transfusion Process: the e-TRAST Tool

The digital transformation of the healthcare sector, while innovative for diagnoses and treatments, presents new challenges related to patient safety and the need to maintain a patient-centered approach. Among complex healthcare contexts, the transfusion sector, inherently both safety-critical and mission-critical, is increasingly characterized by the integration of digital solutions. These technologies, which play a crucial role in managing clinical data and supporting medical decision-making, are essential for ensuring the safety and efficiency of the transfusion process. However, the adoption of such tools has highlighted the need to consider Human and Organizational Factors (HOFs) to ensure the effective and safe integration of technology in high-risk healthcare settings. Although studies and hemovigilance reports have pointed out significant errors—including interoperability issues and inadequate management of IT alerts—that increase process complexity and risks, the literature has shown a lack of models to address these challenges. This master's thesis aims to fill this gap by exploring the impact of digitalization on the transfusion process through a qualitative and quantitative analysis of the risks associated with the interaction among technology, operators, and organizational structure.Methodology: The research process was developed in three main phases. First, a literature review was conducted to identify and classify relevant HOFs in the context of digital healthcare. Then, these findings were integrated into a risk analysis applied to e-health solutions in the transfusion process, resulting in the development of a theoretical model and the creation of a practical tool implemented in an Excel file. This tool was subsequently validated in collaboration with two hospitals and the developer of the software under analysis. Finally, the methodology was tested in a transfusion department of a hospital in Lombardy to calibrate the tool's parameters and verify its effectiveness.Results: The e-TRAST (digitalized Transfusion Risk Analysis from a Socio-Technical perspective) framework was developed by integrating Failure Modes, Effects, and Criticality Analysis (FMECA) with the Cognitive Reliability and Error Analysis Method (CREAM). This combination enables an in-depth analysis of failure modes within the digitalized transfusion process and their root causes. The tool’s underlying logic supports both safety and risk assessments that incorporate human, organizational, and technological factors, providing a holistic perspective on risk and facilitating the contextualization of e-health solutions within their operational environments.The Excel tool revealed that over 25% of failure modes present a higher likelihood of occurrence than previously estimated when human and organizational factors are considered. This tool proved to be effective in pinpointing areas for improvement—both for healthcare institutions, through enhanced training programs and stress management strategies, and for technology developers, by addressing system usability and reliability. In conclusion, the e-TRAST framework facilitates the safer and more efficient adoption of digital technologies within high-risk healthcare environments, ensuring patient safety and operational effectiveness.