The widespread use of social networks has created new pathways for sharing and engaging with mental health information, particularly in contexts where access to care is limited and stigma remains high. Platforms like Instagram have become informal spaces for support, especially among young people. However, these same platforms also amplify misinformation, often through algorithmic systems that shape user perceptions and behavior in harmful ways.

This thesis investigates how to mitigate the risks of mental health misinformation on Instagram, using the Brazilian context as a case study. Integrating System-Theoretic Process Analysis (STPA) and Value Sensitive Design (VSD) to develop socio-technical interventions that are both system-aware and ethically grounded. The research unfolds in three phases: a conceptual phase to identify hazards and system dynamics; an empirical phase based on semi-structured interviews with Brazilian young adults; and a technical phase that synthesizes system risks and user values into actionable design recommendations.

The findings emphasize the importance of four core values: Knowledge, Autonomy, Safety and Integrity in shaping how users interpret and respond to mental health content. Participants described how Instagram’s algorithm reinforces emotionally charged echo chambers, increasing exposure to harmful misinformation while weakening trust in credible sources. Based on this, four interventions are proposed: (1) echo chamber disruption mechanisms, (2) content trigger warnings, (3) verified institutional accounts, and (4) user-controlled filters for validated content.

By framing misinformation as a socio-technical problem rooted in both platform architecture and user experience, this study offers a novel methodological contribution. It demonstrates how combining system-level safety analysis with value-centered design can support the development of interventions that are not only effective but also aligned with user priorities and sociocultural context.

This thesis explores how floods and pandemics - two low-probability, high-impact, threat-driven disasters - can be compared through a structured risk-based lens. Both hazards challenge societies due to their rarity and large-scale consequences, but also allow for intervention before impact due to their forecastable nature. Despite extensive disaster literature, cross-hazard comparisons remain limited. This study fills that gap by asking: What can be learned from a structured risk-based comparison of floods and pandemics?

Focusing on the Netherlands, the research adopts a semi-qualitative, multi-method approach structured around three sub-questions: comparing risk systems (SQ1), case timelines (SQ2), and intervention effects (SQ3). First, bowtie analysis revealed four components shaping disaster risk: risk mechanisms, intervention mechanisms, enabling processes, and risk dynamics. Second, timeline analysis showed that floods are more sudden and measurable, while pandemics are prolonged and uncertain, complicating early decision-making. Third, modeling demonstrated that prevention is most effective for both hazards, though interventions differ in complexity and cost.

Key findings suggest that while disaster dynamics vary, shared governance strategies - such as early warning, scenario planning, and defining acceptable risk - can strengthen preparedness. Cross-hazard learning, particularly between structured flood management and adaptive pandemic response, offers valuable lessons for enhancing disaster governance.

The Netherlands faces significant capacity challenges in healthcare due to staff shortages. Many healthcare positions remain unfilled, despite rising demand for medical services. This also impacts the Emergency Department (ED), as higher patient volumes lead to longer wait times and increased responsibilities for emergency physicians. The combination of these variables leads to an increase in personnel turnover, putting additional strain on capacity. These capacity difficulties may also be seen in Deventer Hospital's ED, highlighting the significance of effectively organising patient flows and addressing system dynamics.

Although Deventer Hospital has conducted analyses to improve capacity management, current approaches, both locally and in the broader literature, primarily focus on technical aspects, such as staffing planning within the ED. However, by focusing solely on technical factors, such analyses may fail to account for social factors that influence system performance, such as human behaviour, communication patterns, decision-making processes, and institutional constraints. To bridge this gap, this study adopts a socio-technical systems approach that incorporates both technical and social factors of capacity management in the ED.

The main question is:
How can Emergency Department capacity challenges be improved using a social-technical approach?

To answer this question, the current system at Deventer Hospital's ED was examined through a socio-technical systems framework. The IDEF0 model was used to map both the technical and social factors influencing capacity management. This model systematically represents workflow processes, resource dependencies, regulatory constraints, and the stakeholders involved. The system mapping was informed by multi-day observations, open interviews with ED physicians, document analysis, and a stakeholder analysis. The stakeholder analysis provided deeper insights into communication patterns, knowledge distribution, and power-interest relationships among the actors. Together, these methods resulted in a comprehensive and structured representation of the ED.

The system analysis revealed that ED capacity challenges involve both technical and social dynamics. These were categorized across three phases: inflow, throughput, and outflow. Specific issues included variability in triage processes, workforce shortages, delays in diagnostics, and asymmetric information exchange between departments. Furthermore, ED physicians noted that a proportion of patients could potentially have been treated elsewhere, affecting resource allocation and patient flow.

Based on these insights, potential interventions were developed to optimize patient redirection within the socio-technical landscape. A snapshot analysis estimated the proportion of patients who, according to ED physicians, could have been treated in alternative settings, such as by general practitioners or outpatient clinics. This analysis was complemented by interviews with ambulance personnel, GPs, and medical specialists, which provided deeper insight into barriers and opportunities for patient redistribution.

The findings indicate that while technical opportunities exist, particularly in redirecting patients to urgent outpatient clinics, success is dependent on effective capacity planning and accessibility in alternative care settings. Social factors play an equally critical role. Efficient patient diversion requires a robust communication framework among general practitioners, ambulance services, and specialists. In practice, however, such communication is not always optimal.

Additionally, a growing claims culture increasingly influences referral behavior. Concerns regarding legal liability and potential complaints compel healthcare providers to refer patients to the ED more frequently as a precaution, even when alternative care options could be more appropriate. This defensive referral behavior exacerbates ED workload and reflects a broader trend of risk aversion in healthcare decision-making.

To address these issues, both technical and social interventions are proposed. Technically, expanding urgent outpatient clinic capacity could offer potential, provided that accessibility and appointment scheduling are carefully managed. Socially, interventions such as structured feedback systems between EDs and referring providers, enhanced real-time communication channels, and targeted legal literacy training for healthcare professionals could reduce unnecessary referrals.

In conclusion, the socio-technical system analysis provided a more comprehensive understanding of ED capacity management by considering both technical and social dimensions. This approach revealed important dynamics that a purely technical analysis might have overlooked, such as communication gaps, coordination barriers, and organizational constraints. It led to the development of potential interventions that not only address logistical aspects of patient redirection but also promote social structural improvements within the healthcare system. By targeting both technical workflows and social coordination mechanisms, this socio-technical approach offers a more realistic pathway to optimizing Emergency Department capacity.

Hospitals place patients in overflow beds when specialty departments reach capacity, maintaining patient flow but potentially compromising patient safety. This study examines how hospitals address these risks in daily decision-making. Using a qualitative, single-center approach, data were collected through observations, hospital documentation, and 12 semi-structured interviews. Inductive thematic analysis identified three key challenges: (1) balancing operational efficiency with clinical suitability, (2) interdepartmental collaboration difficulties, and (3) safety risks for outlying patients.

Findings revealed that the Patient Flow Coordinator (PFC) leads overflow placements using structured tools, but nurses’ limited specialty knowledge contributes to delays and increased length of stay. Existing mitigation strategies include repatriation, decision-making support, and signaling quality concerns.

This study contributes to healthcare management by mapping overflow placement processes and identifying systemic challenges. Recommendations include fostering shared responsibility, enhancing interdepartmental knowledge-sharing, and formalizing decision-making. Future research should evaluate the proposed relationship between decision-making, interdepartmental collaboration, and patient safety risks.

With increasing pressure on healthcare systems, hospitals frequently face bed shortages, requiring patient admissions outside clinically appropriate wards—so-called overflow beds. While efforts are made to place patients in the most suitable available wards, concerns persist regarding the potential impact of overflow beds on patient safety. Despite these concerns, safety implications are not explicitly considered in clinical decision-making during capacity shortages due to a lack of clear evidence.
This study investigated the extent to which patient exposure to overflow beds influences mortality risk. Adopting a data-analysis and statistical prediction modelling approach, hospital capacity, patient characteristics, and safety data were analysed in three phases: (1) identifying clinically relevant exposure patterns, (2) quantifying and predicting the impact on mortality using predictive models, and (3) evaluating the clinical applicability of findings for decision-making.
These findings highlighted increased mortality risks based on three risk dimensions: general exposure, location, and duration in assessing overflow bed risks. The results revealed a significant association between overflow bed exposure and increased mortality risk. Patients placed in overflow beds had a relative 65% higher odds of mortality than those not exposed. In addition, specific risks were identified for mismatched ward placements, with increased mortality risks for patients placed in overflow bed locations din different types of wards than their intended clinically appropriate ward. Short exposure durations (<34 hours) were also linked to higher odds of mortality.
To translate these insights into clinical practice, risk-based guidelines were developed based on common patient parameters at hospital admission (age, comorbidities, and place of origin). Heat maps visually indicate which patients can be relatively safely placed in overflow beds and which should be avoided, enabling hospital staff to make more informed decisions.
These findings should raise awareness among hospitals and staff of the increased mortality risks when capacity constraints require admissions outside clinically appropriate wards. It is recommended that hospitals initiate discussions across the entire organisation - medical, nursing and support staff - about the identified safety risks, and integrate the implications of the research into future policies and guidelines. This will contribute to a more risk-informed, proactive and explicit consideration of safety in hospital capacity decisions, ultimately leading to a more efficient and, above all, safer approach to managing overflow beds in times of increasing healthcare pressures.

Universal Health Coverage (UHC) aims to ensure that all individuals have access to essential healthcare services without facing financial hardship. Achieving UHC requires not only the availability of healthcare services but also the delivery of high-quality care, supported by essential technologies such as medical devices. Medical devices enhance healthcare delivery by enabling timely and accurate medical interventions, yet ensuring that these devices contribute to healthcare outcomes requires more than making them available. In many low- and middle-income countries (LMICs), the functionality and integration of medical devices into healthcare delivery remain a persistent challenge. Devices that are not properly maintained, adapted to local contexts, or aligned with clinical needs often end up unused or broken. Therefore, procurement plays a crucial role in ensuring that medical devices are appropriately selected, acquired, and maintained to meet healthcare needs and remain functional over time.

This research explores how government-led procurement can be structured to support the sustained adoption of high-cost medical devices in LMICs, focusing on Malawi as a case study. A qualitative research design was adopted, using semi-structured interviews with key informants directly involved in the public procurement of medical devices in Malawi. These interviews provided insights into procurement practices, decision-making structures, and broader institutional dynamics. To guide the analysis, this research applies the Adaptability, Scalability, and Sustainability (ASaS) model, a decision-oriented framework designed to assess whether health interventions can be adapted, scaled, and sustained over time. The ASaS model is used as an evaluative tool to assess how well Malawi’s procurement practices align with key determinants of sustained adoption and to identify opportunities for improvement.

The findings show that public procurement of high-cost medical devices in Malawi is organised through a multi-layered system operating across national, institutional, and operational levels. Procurement processes are centrally governed to ensure regulatory oversight and financial accountability, with institutions such as the Internal Procurement and Disposal Committee (IPDC), the Public Procurement and Disposal of Assets Authority (PPDA), and the Ministry of Justice overseeing compliance with national priorities under the PPDA Act of 2017. These formal structures define clear steps for procurement, including needs assessments, technical specifications, supplier selection, tendering, contract negotiation, and quality assurance to ensure procured devices meet required standards. However, while procurement structures define formal decision-making processes, procurement practices encompass the broader systemic and institutional conditions that shape how these processes function in practice and influence procurement outcomes.

Procurement practices in Malawi face challenges that affect the sustained adoption of high-cost medical devices. Externally, fragmented procurement between donor-driven and government-led acquisitions leads to the introduction of devices without government oversight, limiting central tracking and complicating procurement and maintenance planning. Funding constraints further restrict the ability to acquire and sustain essential devices. Although regulatory frameworks promote transparency, they often result in a proliferation of device types that are difficult to manage over time. Internally, poor coordination between procurement and planning departments leads to delays and misalignment with facility readiness. In addition, weak monitoring and evaluation systems hinder follow-up on device functionality and prevent evidence-based decision-making. Finally, procurement outcomes are shaped by device-specific factors, including maintenance needs, spare parts availability, and alignment with clinical workflows, which are not consistently addressed in procurement processes, increasing the risk that devices will become underutilised or non-functional.

Based on these findings, the research concludes that supporting the sustained adoption of high-cost medical devices in Malawi requires shifting from cost-driven acquisition models to more strategic procurement processes that incorporate the Total Cost of Ownership (TCO). Procurement decisions should account for long-term costs such as maintenance, spare parts, operation, and supplier service commitments. Additionally, establishing a centralised national inventory and tracking system for medical devices would improve oversight, support more accurate needs assessments, and enhance future procurement planning. Moving toward evidence-based procurement will require the development of monitoring and evaluation systems to track device functionality and usage over time, ensuring that medical devices remain operational and integrated into healthcare delivery.

Beyond procurement processes, institutional design also influences procurement outcomes. A better balance is needed between centralised technical expertise and local facility input to improve the alignment of procurement decisions with clinical needs and usability. Integration of usability assessments at the need identification stage could help ensure that selected medical devices are both clinically essential and aligned with existing workflows. At the same time, navigating the trade-offs between transparency, competition, and standardisation is essential. While open competition remains important for fairness, moving toward a more standardised selection of device types could simplify maintenance, training, and spare parts sourcing, thereby supporting long-term usability and integration into clinical workflows.

In conclusion, this research underscores that the sustained adoption of high-cost medical devices in Malawi requires rethinking both procurement processes and the broader institutional frameworks in which they are embedded. Aligning procurement with healthcare system capacities requires moving beyond cost-driven acquisitions toward approaches that account for long-term usability, maintenance, and operation. Embedding these elements into procurement planning, alongside the development of monitoring and reporting mechanisms, would help ensure that procurement decisions are aligned with real needs and capacities within healthcare facilities. Equally important is addressing institutional design to ensure that procurement processes are supported by governance structures capable of integrating clinical, technical, and operational perspectives. By aligning procurement with the realities of healthcare system capacities and embedding long-term considerations, Malawi can move from acquiring medical devices to ensuring their sustained use. These insights are critical for policymakers and practitioners seeking to strengthen healthcare systems and promote sustainable outcomes from medical device investments.

Emerging and developing economies are currently growing at a significantly faster pace than their developed counterparts. While the real GDP of advanced economies is expected to grow by 1.7 and 1.8 percent in the years 2024 and 2025 respectively, the real GDP of emerging markets and middle income economies is expected to grow by 4.1 percent per annum. This rapid growth poses an opportunity for developed-market multinational corporations to realize market growth by expanding their business into these markets. However, operating in emerging and developing markets also brings novel challenges and constraints, to which entrants must adapt their strategies. For instance, these markets consist of a large low-income group that favors affordable and high quality products. A concept that addresses the constraints of serving low income groups in emerging and developing markets is frugal innovation, a form of resource constraint innovation. Frugal innovations are products that are affordable, focus on core functionalities, and have an optimized performance level, thus catering to the specific needs of Bottom of the Pyramid (BoP) consumers. This research adopts the perspective of Multinational Corporations (MNCs) and explores frugal innovation as a potential solution to the various challenges MNCs face in emerging and developing markets. This study answers the following research question: “How can frugal innovation complement multinational corporations’ strategies to address business and operational challenges faced in emerging and developing markets?” It thereby links strategies, challenges, and frugal innovation in a novel manner. To answer this question, frugal innovation strategies are identified in the literature and challenges and strategies of MNCs in emerging and developing markets are determined through a literature search and semi structured interviews with representatives of various MNCs. Through the literature review on frugal innovation, five frugal innovation strategies are identified: The first strategy MNCs can employ is a Frugal Innovation Orientation (FIO) strategy, thereby solely focusing on an economic value proposition. Furthermore, they can introduce a local R&D center and engage in customer co-creation. The products offered in emerging and developing markets should be cheap, focus on core functionalities and have an optimized performance level. Finally, the products should also match the quality of the brand. The most prevalent challenges faced by MNCs in emerging and developing markets, as identified through literature and interviews, include institutional voids, infrastructure deficiencies, low purchasing power, political instability, workforce challenges, trade regulations, consumer complexity, balancing standardization with adaptation, gaining product acceptance, and NGO push back. To navigate these challenges, MNCs employ various strategies, including localization, tailoring products and pricing to local markets, collaborating with companies and NGOs, identifying core customer values, understanding the local culture and market, focusing on market potential, adopting frugal innovation, and engaging in social initiatives. Upon comparing these challenges with the current strategies and the frugal innovation strategies, the following conclusion is drawn: The frugal innovation strategies potentially only solve the business challenges of consumer complexity, low purchasing power, and gaining product acceptance. However, these challenges are already being resolved by the current strategies of MNCs. Therefore, the frugal innovation strategies are not essential but can complement the current strategies. Some of the frugal and current strategies do overlap meaning that MNCs currently already use some of the identified frugal innovation strategies.

The healthcare sector is facing serious challenges. On the one hand, the population is ageing, resulting in a higher pressure on healthcare resources. On the other hand, less than half of the world’s global population is covered by essential healthcare services due to limiting resources. Frugal health innovations are developed to be affordable, accessible, and make effective use of limited resources. As such, frugal health innovations can help to decrease the resource-dependency in the healthcare sector, contributing to healthcare access to all. Yet, the adoption of frugal health innovations remains limited. Adding to this issue, the adoption is not studied from a theoretical perspective and empirical evidence on the reasons for (non-)adoption remains scarce. Understanding what affects the adoption from a theoretical perspective helps to identify underlying principles at hand, allowing to build a conceptual framework. Such a conceptual framework can guide frugal health innovation development for increased adoption probability and promote future theoretical studies on frugal health innovations. This research aims to understand what factors affect the adoption of frugal health innovations from a theoretical perspective, by asking the research question “What factors affect the adoption of frugal health innovations?”.

To guide the research, the first sub-research question “What theoretical framework is most appropriate to describe adoption of frugal health innovations?” was asked. Answering this question ensured a departing point for the theoretical understanding of frugal health innovation adoption. Secondary data from the literature was retrieved through a literature review, from which it followed that nine theoretical perspectives have been used to study the adoption of non-health-related frugal innovations. By comparing the theoretical perspectives against the context of frugal health innovations, it followed that the Unified Theory of Acceptance and Use of Technology 2 is the most appropriate theoretical perspective to study the adoption of frugal health innovations.

To further guide the research, the second sub-research question “What empirical evidence exists, that can give information on factors affecting the adoption of frugal health innovations?” was asked. Answering this sub-research question allowed to synthesize empirical evidence in the Unified Theory of Acceptance and Use of Technology 2 framework to arrive at a conceptual framework for the adoption of frugal health innovations. Secondary data from the literature was retrieved through a literature study, and the empirical evidence was put in the context of frugal health innovations. From this, it followed that the possibility to experiment with the innovation (Trialability), the innovation- fit with the customers’ lifestyle (Lifestyle Compatibility), the availability of required knowledge to use the innovation (Consumer Literacy), the trust toward the provider of the innovation (Trust), the technical performance of the innovation (Performance Expectancy), the ease-of-use of the innovation (Effort Expectancy), the degree of social pressure to use the innovation (Social Influence), the price of the innovation (Price Value), and the degree of resource- and infrastructural constraints impeding the use of the innovation (Facilitating Conditions) facilitate the intention to adopt frugal health innovations (Behavioural Intention). Interestingly, the synthesis revealed that Price Value, Facilitating Conditions, and Trust also act as a barrier in case they are not properly addressed by the frugal health innovation.

Ultimately, the conceptual framework was empirically validated in the context of frugal health innovations through semi-structured interviews with four frugal health innovation developers. Because developers were surveyed, in contrast to consumers by the studies from the literature review, the adoption, and not consumer-central behavioural intention to adopt, was studied. To increase the possibility of adoption, results suggest that trust between the developer and consumer should be established (Trust), the innovation should align with the preferences of the consumer (Lifestyle Compatibility), the innovation should be designed so that it is easy to use and install (Effort Expectancy), and the innovation should be priced appropriately to ensure affordability whilst maintaining a positive perceived price- quality relationship (Price Value). Further, results suggest that it is imperative to understand the context of the addressed health-related issues, as the performance of the frugal innovation must be superior to traditional health innovations if the latter shows poor performance or side effects, or can be inferior if they are used indicatively where the traditional innovation is used confirmatively (Performance Expectancy). Understanding the context is also of importance to determine whether the use of the frugal health innovation is not impeded by the lack of resources and/or infrastructure, or, appropriately addresses their absence, thereby providing a market opportunity (Facilitating Conditions). Additionally, results suggest that the severity of the health problem (Problem Severity) also affect the adoption, whilst only relevant in case frugal health innovations are sold to governmental organizations. All in all, this exploratory research provides a first conceptual framework to study the adoption of frugal health innovations and opens up the debate on what is required for their adoption. Developers are advised to tailor frugal health innovations according to the principles observed in this research study, as doing so likely enhances the probability of adoption. However, considering the lack of a consumer-perspective in this research study, a logical next step is to further gather empirical findings on frugal health innovation adoption using the developed conceptual framework, to ensure a more robust image of the factors affecting the adoption of frugal health innovations.

The COVID-19 pandemic highlighted vulnerabilities in global healthcare systems, emphasizing the need for innovation to enhance resilience, particularly in response to outbreaks and demographic changes like an ageing population. Many of these innovations originate from university research and are brought to market by health-tech spin-offs, creating significant societal value. In the Netherlands, academic entrepreneurial ecosystems play a crucial role in supporting these spin-offs, particularly in their early stages, through various facilitators. However, challenges unique to health-tech spin-offs, such as clinical regulations, often hinder their growth. Despite current efforts, facilitators lack comprehensive knowledge about the effectiveness of their support, leading to gaps that need addressing. Many publications exist about academic entrepreneurial frameworks however there remains a lack of knowledge about their applicability to Dutch academic entrepreneurial ecosystems. This study investigates how the three Dutch academic entrepreneurial ecosystems (Delft University of Technology, Leiden University Medical Centre and Erasmus Medical Centre) can design their academic entrepreneurial support systems to aid health-tech spin-offs effectively. Through a combination of literature analysis and interviews with facilitators and founders, the study identifies mismatches in support, including the need for tailored health-tech programs, clinical validation support, and efficient networking. It also explores the specialized support areas within Dutch ecosystems, such as TU Delft's focus on high-tech inventions, EMC's emphasis on medical devices, and LUMC's concentration on pharmaceutical spin-offs. The findings suggest that while each ecosystem has its strengths, there is a need for more targeted and effective support structures to meet the specific needs of health-tech spin-offs. The study offers practical implications for both facilitators and founders, providing a clearer understanding of how to optimize support within these ecosystems. Additionally, it contributes to the academic literature by offering insights into the unique challenges faced by health-tech spin-offs and the role of academic entrepreneurial ecosystems in addressing these challenges. Future research is recommended to further explore the effectiveness of tailored support solutions and the role of national policies in fostering the growth of health-tech spin-offs.

Background Issues:
Healthcare is essential for individuals and society, but faces challenges such as diseases, aging populations, financial burdens, and fair distribution of services. Regenerative medicine, which aims to replace or regenerate human cells, tissues, or organs, offers promising solutions but encounters difficulties in transitioning from research to clinical practice. This transition requires societal changes including political, regulatory, and public acceptance.

Regenerative Medicine in Japan:
Japan’s healthcare system is strained by an aging population and other health issues. To address this, Japan has implemented unique regulations over the past decade to promote regenerative medicine. These regulations allow hospitals to provide regenerative treatments without extensive scientific assessments and enable pharmaceutical companies to market products with conditional approval before full scientific validation. Although these measures aim to expedite access and industry growth, they also raise concerns about safety and standardization.

Research Question:
This research investigates how ethical considerations can be incorporated into the translation of regenerative medicine in Japan. Using an interdisciplinary approach, the study examines key processes and actors involved, ethical issues, and potential solutions through literature review, actor analysis, thematic analysis, conceptual synthesis, and an online questionnaire with supplementary interviews.

Results and Conclusion:
Key processes and influential actors in the translation of regenerative medicine in Japan were identified, including the Ministry of Health, Labour and Welfare (MHLW), the Ministry of Education, Culture, Sports, Science and Technology (MEXT), large hospitals, and universities/national research institutions. Current and potential ethical issues were explored, with suggested approaches derived from literature and comparative analysis with other countries.

Recommendations include:

MHLW should clearly define terms like “unproven,” “innovative,” “research,” and “treatment.”
Hospitals should refine their practices and guidelines, collaborating with MHLW and MEXT.
MHLW and MEXT should gather feedback from practitioners to update ethical guidelines.
Doctors and researchers should contribute to policy-making and practical guideline reflections.
Public discussion should be encouraged to gain societal acceptance and contribute to policy formation.

The research proposes a framework for incorporating ethical considerations into regenerative medicine in Japan, offering insights for policy refinement and further research in emerging technologies both in Japan and globally.

Neonatal care in the Netherlands is under significant strain due to severe bed capacity and staffing shortages, particularly in the southwestern region, where 36% of hospitals have closed neonatal beds. The current neonatal care system, structured into three escalating levels of specialization—neonatal medium care, high care, and Neonatal Intensive Care Units (NICUs)—struggles to meet demand, resulting in high occupancy rates and frequent patient transfers. This study developed a discrete-event simulation model to analyze and address bed capacity shortages within these staffing limitations. The model, based on regional perinatal birth data, evaluated the impact of various interventions on bed occupancy and transfer rates across different care levels.

Key findings revealed that reducing the length of stay, adjusting admission rates, and altering patient pathways could alleviate capacity pressures. While individual interventions offered modest improvements, a combined strategy integrating multiple approaches significantly reduced occupancy rates and patient transfers. This research underscores the need for a multifaceted approach to address neonatal care challenges and highlights the potential of simulation modeling as a tool for informed decision-making in healthcare resource management. The study’s insights offer a pathway toward sustainable neonatal care despite ongoing constraints.

Telemedicine has the potential to significantly improve healthcare delivery in low-resource settings (LRS), yet its adoption remains low despite its benefits. This study explores the organizational factors of telemedicine adoption in LRS using qualitative research methods and adapting the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. The research identifies key barriers and facilitators, and a modified framework is proposed to better address the adoption dynamics. The study provides valuable insights into how telemedicine adoption can be examined among healthcare professionals in LRS, highlighting the need for further validation of the proposed framework.

In recent years, there has been a significant increase in the number of depression cases. However, only 9% of depression patients in Indonesia receive appropriate treatment. The rapid advancement of technology highlights the potential for telemedicine to close this gap. Unfortunately, the adoption of telemedicine in Indonesia remains challenging, with a small amount of the population having used this technology.

Several factors impact the adoption of telemedicine among its users. The adoption of this technology, including by healthcare professionals, will depend on these factors. To understand these factors, the adoption of telemedicine for depression care among healthcare professionals in Indonesia is explored in this study.

The Unified Theory of Acceptance and Use of Technology (UTAUT) is employed as the theoretical foundation. Performance expectancy and effort expectancy are used to find the answer to the main research question. Performance expectancy refers to the degree to which one expects a system to help them raise their job performance, while effort expectancy refers to the degree to which a system is easy to use. Eleven interviewees were interviewed for this research, of whom eight are psychologists, two are psychiatrists, and one is an academic.

In terms of performance expectancy, there are nine key factors that could contribute to the adoption of telemedicine for depression care. In terms of effort expectancy, it was found that five key factors influence healthcare professionals’ perceived ease of use towards telemedicine. As a result, it was found through deeper analysis that education and technology are two additional contributors to the UTAUT framework in telemedicine for depression care. Additionally, the findings show that current regulations are still inadequate to provide comprehensive rules related to telemedicine practices in Indonesia.

This research has several limitations. It focuses exclusively on depression care in Indonesia as a country and not specific to certain locations. Bias can arise from the small number of interviewees in this research. Future research should consider the location, gender, age, and experience of interviewees to provide more comprehensive results. Another research can be employed to ensure the validity and generalization of the suggested framework in similar cases.

The implications of this research are intended for policymakers, academic institutions, and technology providers. To ensure the proper functioning of telemedicine, policymakers supported by academic institutions should incorporate telemedicine courses into the curriculum and establish formal regulations of telemedicine in the country. For technology providers, they must ensure that telemedicine functionalities meet the needs of healthcare professionals in order for them to perform their duties.

During the COVID-19 pandemic, many elective surgeries had to be rescheduled as resources suchas beds and ventilators were reallocated, causing significant delays in patient care. To avoid such disruptions in the future effective resource management and planning approaches for elective surgery are essential. Optimisation is a commonly used method to enhance elective operating theatre scheduling, it is a technique used for mathematical modeling. It can integrate various criteria to maximise benefits and minimise costs within specified constraints. However, optimisation alone often falls short in addressing the complexities and required flexibility of operating theatre scheduling. This is where simulation can build upon these limitations. Simulation techniques can model system behaviour by replicating real-world processes, introduce uncertainty, and evaluate responses to different policies, helping to identify bottlenecks and improve system efficiency. Sequencing optimisation and simulation can test theoretically sound solutions under real-world uncertainties and complexities. This leads to the following research question:

“How can Discrete Event Simulation evaluate optimisation-generated Master Surgery Schedules for operating theatres?”

The research question focuses on a Master Surgery Schedule, which coordinates different surgical specialities, sharing OTs and pre- and post-surgery resources. While this approach increases resource utilisation, it also adds complexity by needing to accommodate the varying requirements of each speciality. The research aims to evaluate different Master Surgery Schedule using Discrete Event Simulation to contribute to the optimisation model.

Overall, the use of the Discrete Event Simulation model provided detailed insights into the
performance of various schedules. Testing these schedules under different types of uncertainty
demonstrated their robustness, as the behaviour remained consistent across scenarios. By
comparing the schedules side by side, the simulation model effectively evaluated their
effectiveness, ensuring the intended purposes were served and identifying areas for improvement.

The research specifically considers Discrete Event Simulation as this method can queue patients for different resources and have them move throughout the system based on decision rules. It is also a standard applied method for modelling healthcare systems. Both Discrete Event Simulation and optimisation are standard methods for improving OT scheduling. Even sequencing the methods has been proven to contribute to OT scheduling. However, applying this approach to a Master Surgery Schedule is new and introduces additional complexity related to the shared OTs and pre- and postsurgery resources.

To explore this research question, a case study was conducted at Sophia Children’s Hospital in
Rotterdam. Previous research developed the Master Surgery Schedule using an optimization
model, resulting in four different schedules. These schedules either balanced ward leveling and operating theatre utilization equally or prioritized ward leveling. They also varied in computational requirements, as the model updated the bed availability either every 15 minutes or every hour. This research categorizes 18 different surgical departments into 50 groups based on their surgery duration and length of stay, assigning time slots to these groups in the schedules.

This research uses these groupings to fit different distributions for the input variables of length of stay and surgery duration. Five different types of distributions were tested for each group, and the best-fitting distribution was assigned. Additionally, previous research provides a schedule for ward capacity and establishes decision rules for patient management. In collaboration with the hospital, the probability of Intensive Care assignment and the various decision rules were validated.

The sensitivity analysis revealed a slight overestimation of surgery duration compared to the test data, but this did not significantly impact outcomes. The model is more vulnerable to ward capacity and length of stay, which were then selected for scenario analysis. The schedule prioritising ward levelling and checking availability every 15 minutes outperformed others, effectively addressing ward unavailability, the primary bottleneck. However, increasing capacity improves the number of successful surgeries but also leads to more cancellations due to operating theatre unavailability and increased overtime occurrences. This highlighted a trade-off between operating theatre utilisation and other Key Performance Indicators.

The sensitivity analysis revealed a slight overestimation of surgery duration compared to the test data, but this did not significantly impact the overall outcomes. The model was found to be more sensitive to ward capacity and length of stay, which were then selected for scenario analysis. Among the different schedules, the one prioritizing ward leveling and checking bed availability every 15 minutes outperformed the others, effectively addressing ward unavailability, which was identified as the primary bottleneck. However, while increasing ward capacity improved the number of successful surgeries, it also resulted in more cancellations due to operating theatre unavailability and increased overtime occurrences. This finding highlighted a trade-off between operating theatre utilization and other Key Performance Indicators.

In line with the literature, the research reveals that striving for increased operating theatre
utilisation puts excessive pressure on other resources. Ward unavailability is identified as the main reason for surgery cancellations, indicating that wards require even greater focus. An increase in ward capacity had the best outcomes during the scenario analysis, showing that this is the biggest bottleneck in the system.

The simulation model identified new parameters for the optimisation model and highlighted
weaknesses in the system to be improved upon. Future research should explore ward capacity in greater detail and develop better methods for sharing resources across different operating theatres and wards to reduce the differences in utilisation. Additionally, further research could investigate other causes of surgery cancellations and refine the definitions of surgery groups

Amidst ongoing climate change, communities worldwide face increasing frequency and severity of floods, which cause extensive destruction and pose significant health threats. Post-flood effects include drowning, injuries, and both communicable and non-communicable diseases, varying by context. This study addresses a critical knowledge gap by exploring the complex relationship between flood disasters, healthcare systems, and communicable diseases. It aims to understand how socio-economic, institutional, and geographical factors interact with health outcomes following floods.

The study highlights vulnerabilities in countries like Peru, Sri Lanka, and Pakistan, where past floods have significantly impacted communicable disease incidence. It evaluates healthcare system resilience by analyzing vulnerability and resilience factors that determine a country’s capacity to manage health impacts from floods. Vulnerability is influenced by socio-economic conditions, public health factors, and behaviors, while resilience is shaped by healthcare system quality, institutional effectiveness, and individual capacities.

Quantitative methods, including exploratory data analysis and causal-comparative design, form the core of this study. Natural flood events are used to investigate cause-and-effect relationships, supported by a conceptual framework developed through desk studies and concept mapping. Systematic data collection and analysis explore the relationship between flood events, healthcare systems, and communicable diseases. Principal component analysis identifies key indicators linking health characteristics with increased communicable disease incidences post-flood.

Synthesizing insights from data analysis, the study proposes an empirically validated framework to guide effective disaster response strategies. Understanding flood impacts and enhancing community resilience are crucial for developing targeted mitigation measures. By identifying vulnerabilities and resilience factors in healthcare and emphasizing individual empowerment, this research contributes to holistic disaster preparedness and response approaches.

Data-driven health research, specifically the development of AI models, is hampered by poor data availability and associated administrative burdens, caused complex and fragmented data protection regulation. To reap the benefits of using high quality health data, while safeguarding data protection of patients, the synthetic data generation is seen as a promising privacy-enhancing technology to avoid the need for personal data sharing. Although synthetic data is widely discussed, research primarily focuses on a technical development and evaluation of data protection, leaving substantive matters on the use of synthetic data within its institutional context open. By combining legal and technical knowledge, this thesis aimed to bridge this gap, by analysing how synthetic data generation could enable health data sharing for research in a privacy-enhancing manner. Specifically, a design science research approach is followed to combine the requirements from the institutional environment, focusing on a use case with a Dutch healthcare provider and research institute, with scientific knowledge on synthetic data generation and data protection evaluations. The research objective was to design a framework that structures the data protection-related factors that influence the extent to which synthetic health data enables secondary use of health data for research. The identified barriers and drivers of synthetic data generation focus on the health data sharing process, the interplay between the legal definition of anonymisation and technical data protection evaluations, as well as data protection principles. Synthetic data can enable secondary use of health data for research, but, measures should be implemented in the various phases of synthetic data sharing to safeguard patients’ data protection. As policy opportunity, this thesis argues for narrower definition of personal data to support privacy-enhancing technologies such as synthetic data generation.

Hospitals are part of the vital and vulnerable infrastructure in the Netherlands. Failure of such infrastructure may have severe consequences on a national scale. The Dutch flood risk management approach aims to prepare hospitals for floods through spatial adaptation. However, the current policy does not prescribe concrete guidelines for consistent decision-making and implementation of flood strategies to increase flood preparedness of hospitals. The engagement of stakeholders in this process is also arbitrary.

The main research question is: “How can flood preparedness of hospitals in the Netherlands be assessed and improved?” The main aim of this research is to quantitatively assess the flood preparedness of hospitals to enable comparison between flood strategies and to make recommendations on which stakeholders should be engaged for the implementation of flood strategies and how this can be achieved.

Six different flood preparedness indicators were selected that together describe flood preparedness of hospitals. Based on these indicators, the impact of several flood scenarios on the Reinier de Graaf Gasthuis (RdGG) and Erasmus Medical Centre (EMC) was quantitatively assessed. The costs per flood strategy are highest for “shelter in place with additional measures”, followed by both “shelter in place without additional measures” and “preventive evacuation”. “Accept” is least expensive. The number of fatalities per flood strategy for the RdGG (0,2 to 2,1 fatalities) is much lower than for the EMC (18,8 to 195,3 fatalities). Furthermore, it was determined which stakeholders should be engaged for the implementation of each flood strategy. Experts who have experience with hospital floods were interviewed to obtain their view on how these stakeholders could be engaged.

In conclusion, essential hospital functions can be categorised based on the flood preparedness indicators and flood strategies can be quantitatively compared. For the RdGG and EMC, "shelter in place with additional measures" yield the least amount of fatalities and is therefore the "best" flood strategy. The Executive Board of a hospital, hospital personnel, water boards, municipalities and safety regions should be engaged to realise the implementation of flood strategies. Experts with lived experience recommended to engage stakeholders through legislation or creating awareness.

It is recommended to calibrate the number of fatalities based on historical flood events and to analyse the vulnerability of the regional healthcare system to supplier failure during floods.

The third version of the Green Deal Sustainable Healthcare 3.0 (GD3) in the Dutch elderly care sector represents a dynamic and shared governance model that promotes widespread participation and implementation of sustainability practices. The GD3 provides a blueprint for elderly care organisations to pursue sustainability goals, but its success depends on collaborative efforts supported by various tools and frameworks. This research explores how joining the GD3 facilitates the achievement of sustainability goals in elderly care organisations. Successful implementation of the GD3 can have far-reaching effects, of which inspiring other sectors to adopt similar collaborative approaches. However, its effectiveness depends on the performance of the participating organisations and their use of empowering tools such as the Milieuthermometer Zorg (MTZ). Interaction and cooperation between the diverse group of actors is essential to achieve the desired results, as the GD3 operates through a shared form of governance involving both bottom-up and governmental actors. Active participation, implementation of sustainable actions and maintaining trust and cooperation are crucial for the effectiveness of the GD3. Repeated experience with climate agreements such as the GD3 helps to build trust, reciprocity and reputation among participating actors. All of this is being explored in the context of other challenges specific to care for the elderly, such as staff shortages and an ageing population. Ultimately, the GD3 represents a valuable initiative within the health sector that provides a script for sustainability efforts, while allowing organisations the flexibility to adapt and take artistic license in achieving the intended outcomes. The aim is to present a dazzling sustainability show within three years, signalling a transformed system. Given the urgency of sustainability and the challenges posed by an ageing population, embracing GD3's collaborative and adaptive approach is essential for the future of healthcare, particularly in the context of elderly care in the Netherlands.

In Dutch primary care, there is a dilemma that needs to be solved: caregivers using different digital platform in information system (DPIS) have difficulties in transferring necessary medical information. Although DPIS, as an emerging technology, assists in the decision making, coordination and control that occurs in the organizational environment. Its lack of openness leads to difficulties in exchanging information data. Therefore, this study focuses on the architectural requirements that can facilitate the openness of DPIS for primary care in the Netherlands. A design science approach was used to answer this question. The study first clarifies the current situation using document analysis and literature review, then defines the factors influencing openness and the requirements of stakeholders regarding openness and identifies architectural requirements. Finally, a conceptual artifact was developed and the requirements were validated in discussion with domain experts. The results of the study suggest that a clear distinction should be made between open to share or open to use when defining the openness of an architecture, and in addition, we should focus on the development of standardized data exchange regulations.

In recent years, the medical world has seen rapid digitalisation. Digitalisation of healthcare and the opportunities of remote monitoring can help to keep the healthcare system affordable and accessible. A promising application of remote monitoring is the use of consumer-grade wearables for clinical care. However, vulnerabilities leave consumer-grade wearables susceptible to cybersecurity and privacy risks. When the wearables gain clinical care functionality, increased risks are problematic for the success of the technology. This research examined this problem by analysing the role of users in the cybersecurity and privacy environment and the impact of human factors on the cybersecurity and privacy system of medical wearables. Vulnerabilities and associated risks were identified with the help of notions from human-centric cybersecurity. To establish a user-centred approach to tackle these risks, the user needs and limitations were examined by performing a quantitative survey research. Based on the results of the survey and the human-centric components of user, usage, and usability, guidelines for the user-centred approach were formulated. These guidelines were subsequently linked with the challenges and attacker-oriented and user-oriented risks to establish recommendations for medical wearable providers. Providers can use these to steer the design of the cybersecurity and privacy system and the structuring of the system environment. The research showed that by taking into account the needs and limitations of users, the cybersecurity and privacy system design can be more effective in tackling user-oriented risks. The research concludes that a user-centred approach to cybersecurity and privacy can contribute to the successful use of consumer-grade wearables for clinical care purposes.