This study investigates the potential of Self-Sovereign Identity (SSI) to empower individuals within Indonesia's health data ecosystem, particularly in the context of a Low- and Middle-Income Country (LMIC). The central concern is the loss of control that individuals face when their personal data becomes part of a broader health data ecosystem, utilized by various stakeholders like the government, healthcare facilities, and insurance companies. SSI, a decentralized and blockchain-enabled system, offers a solution by giving individuals control and ownership over their data, allowing them to decide how and to what extent their data is shared with third parties.

The research question focuses on how SSI functionalities should be designed to ensure the retention of personal data sovereignty (PDS) in an LMIC context. The study employs the Design Science Research (DSR) methodology, which includes the creation and evaluation of design artifacts to advance understanding in this domain. The research process involved developing SSI interface artifacts and testing them through a qualitative study with 15 Indonesian respondents, including individuals with socially stigmatized diseases like HIV/AIDS and TB. This population was chosen to ensure the study's inclusivity, given their heightened sensitivity to data privacy issues.

The study’s findings highlight the importance of data minimization and revocation functionalities in SSI systems. Data minimization allows users to share only the necessary information, while revocation gives them the ability to withdraw their consent for data sharing. These functionalities are crucial for fostering a sense of control, which is directly linked to a feeling of ownership over one's data. The study also revealed that a user’s digital literacy and affinity with data sharing significantly affect their perception of SSI functionalities. Users with a higher understanding of data implications tend to prefer more complex interfaces that encourage careful decision-making, whereas those with limited knowledge are more comfortable with simpler interfaces.

Additionally, the study underscores the importance of trust and contractual agreements as foundational elements in a user's willingness to participate in a data ecosystem. Without these, users may be hesitant to share their data, regardless of the control mechanisms in place.

This research contributes to the growing body of knowledge on SSI, particularly in the context of an LMIC like Indonesia. By taking a user-centric approach, the study explores the link between SSI functionalities and personal data sovereignty, providing insights that are currently underrepresented in existing literature. The inclusion of vulnerable populations further enriches the study’s findings, offering a comprehensive understanding of how SSI can enhance participation in the health data ecosystem while safeguarding personal data sovereignty.

Future research should aim to broaden the respondent pool to include more diverse socio-economic backgrounds, which would improve the generalizability of the findings. Additionally, further refinement of the SSI design artifact, informed by user feedback, is recommended to enhance its usability and effectiveness. Exploring the study's hypotheses through a quantitative approach could also provide deeper insights into the relationship between digital literacy, data sharing affinity, and personal data sovereignty.

This thesis examines the effects of safety notices on the utilization of knee implants in orthopedic practices. Utilizing a blend of correlation analysis, machine learning techniques, and interrupted time series analysis, this study evaluates the impact of safety notices on the market share of diverse knee implant models. The analysis leverages a dataset comprising safety notices, market share figures, and analytical model outputs to investigate both the direct and indirect influences of these notices on clinical decision-making processes.
Although safety notices are integral to regulatory compliance and patient safety under the Medical Device Regulation (MDR), which mandates continuous monitoring of device performance, findings indicate that these notices seldom significantly alter clinical practices or market shares. Notable exceptions include specific models such as Advance, Evolution, and Journey, which display variable impacts, suggesting the presence of other complex factors at play in clinical decision-making. These findings illustrate the complex dynamics of clinical responses to regulatory initiatives and underscore the need for more robust monitoring and evaluation strategies to determine the effectiveness of safety notices in post-market surveillance.
The thesis underscores the need to enhance post-market surveillance systems to more accurately assess the influence of safety notices on clinical practice, thereby addressing a crucial knowledge gap. By recommending directions for future research aimed at elucidating the subtle effects of safety notices, this work strives to maximize their utility and foster improved outcomes in patient care within the realm of medical devices. This research establishes a foundation for understanding the practical implications of safety notices in clinical environments, ensuring that regulatory measures are more closely aligned with clinical requirements, which will be useful for future research.