Healthcare systems in the Netherlands and other Western countries are under increasing strain due to growing demand for care and a shrinking workforce. A critical challenge is understanding why nurses choose to remain in the profession, particularly in high-pressure settings such as hospital emergency departments. This thesis investigates how a systems science approach can contribute to understanding nurses’ workload and their intention to stay in the profession, using a case study of the Emergency Department at Erasmus MC.

Drawing on System Dynamics modeling and participatory Group Model Building with nurses, the study explores the complex relationships among perceived workload, job satisfaction, stress, and team dynamics. The research combines literature review, participatory modeling sessions, and simulation using Exploratory Modeling and Analysis to identify the conditions under which nurses are most likely to remain in the profession.

Findings show that perceived workload has a stronger influence on the intention to stay than objective measures such as patient-to-nurse ratios. A key insight is the concept of “shift balance,” which captures whether nurses experience more positive than negative shifts over time. This metric proved more meaningful than traditional workload indicators. The study also highlights the importance of eustress, a motivating form of stress, and the need to distinguish it from other stress types.

By applying systems science tools to a complex workforce issue, the thesis offers practical guidance for designing interventions that support nurses' long-term commitment to their profession. It has deepened the understanding of stress and workload dynamics around the nurses' intention to stay in the profession.

Pediatric Intensive Care Unit (PICU) capacity management plays a vital role in healthcare systems, especially during dynamic and high-demand situations. However, current planning approaches rely on static models and retrospective hospital data, which are limited in their ability to respond to sudden changes in demand. These models largely depend on internal patient flow and length of stay predictions, without considering external influences or real-time developments, leading to delayed responses and inefficient resource allocation. This research explores how new approaches to patient data analytics can improve PICU utilization planning and what kind of system architecture could enable this shift. A qualitative approach was employed, involving interviews with various PICU capacity management work-related professionals. The research process was structured using the Double Diamond model to guide the progression from problem exploration to solution development. Thematic analysis was used to identify key themes related to data use, legal and technical constraints, and opportunities for integrating new data sources such as wearable devices, remote monitoring systems, and data from other departments. This research was conducted in the context of PICU capacity management in the Netherlands. The findings show that while relevant data is being generated, it remains fragmented and unintegrated in current systems, limiting forecasting capabilities. Legal frameworks such as GDPR and the EU AI Act further complicate data exchange but also provide a basis for designing compliant systems. The study proposes a new system architecture that integrates diverse data sources while taking into account legal constraints, to enhance forecasting accuracy and operational decision-making. This research contributes to PICU capacity management by bringing together data analytics and automation while addressing legal constraints. It offers a scientific contribution by exploring how predictive modeling from various data sources can be integrated within a compliant system architecture and by addressing the challenge of fragmented data for effective PICU planning.

This master thesis studies the role of health insurers in stimulating the transition towards circular hospitals in the Netherlands, addressing a critical gap in current research. The Dutch healthcare sector contributes significantly to national carbon emissions, with hospitals being major contributors. As the government targets a fully circular economy by 2050, understanding how health insurers can facilitate this transition is vital.

Conducted within a master thesis internship at Zilveren Kruis, the largest Dutch health insurer, this research employs a complex systems perspective. The methodological framework consists of three phases, primarily using system diagrams and semi-structured interviews. The first phase involved a literature study and interviews with health insurers, leading to the development of the Insurer-driven Circular Hospitals model. The second phase included additional interviews with health insurers and hospitals to identify the effects of possible interventions and system barriers. The third phase focused on substantiating the responsibility roles of health insurers, based on the interviews.

Findings show that health insurers can use their financial, facilitating, and connecting roles to stimulate circularity in hospitals. Eight potential interventions were identified, with the most promising being: going into conversation with hospitals to provide suitable support, sharing good examples to enhance knowledge exchange, and offering financial support to counter financial barriers. Additional interventions include improving the measurability of hospital progress, including circularity criteria in procurement policy, collaborating with suppliers, collaborating with all health insurers, and involving patients.

The research highlights that achieving circular hospitals is a shared responsibility within the healthcare sector, necessitating collaborative efforts. The study contributes to the existing knowledge base by applying a systems approach to circular healthcare, validating known barriers such as financial constraints and procedural standards, and emphasizing the importance of awareness and collaboration. Future research should expand the participant base, explore system transformation approaches, quantify intervention impacts, and broaden the definition of circular hospitals to include recycling strategies.

In recent years, public health deterioration is a growing concern worldwide driven by factors such as lifestyle changes, environmental degradation, and unequal access to healthcare. In-creasing rates of chronic diseases, mental health disorders, and the global spread of infectious diseases have highlight the urgent attention to these problems. Consequently, the mounting pressure on global health infrastructures reinforces the need for innovative solutions, such as digital health technologies, to improve healthcare access and overall well-being. In the rapidly evolving landscape of digital healthcare, digital health startups are at the forefront of innovation, harnessing cutting-edge technologies like artificial intelligence, big data analytics, and mobile health applications to transform patient care, diagnosis, and treatment. Despite their in-creasing prominence, a significant knowledge gap remains in understanding how these digital health startups effectively create, capture, and deliver value, particularly within the intricate regulatory framework of the Dutch healthcare system.
This research directly addresses this gap by exploring the key elements of value creation, capture, and delivery specific to the digital health sector in The Netherlands to conceptually understand the core of the digital health startups. These elements—value creation, capture, and delivery-are fundamental components of any business model, as highlighted by researcher Alexander Osterwalder, as represent how a company creates value for customers, captures a part of this created value, and efficiently delivers its offerings, all of which are crucial for the success of digital health startups. Building on this, through a comprehensive analysis of existing business model frameworks, this study evaluates their applicability, points of alignment and misalignment with the current research’s aim, ultimately leading to the development of a conceptual value framework. This framework is crafted to provide a holistic and conceptual understanding to business modeling, equipping Dutch digital health startups with better under-standing, structured thinking and a birds-eye view of the processes necessary to successfully navigate the complexities involved in digital healthcare innovation. This research is only a preliminary step towards developing a tool, that can be practically used by the entrepreneurs for hands-on inputs and formulation of business strategies, through further research.
he findings of this research emphasize the critical importance of a well-structured business model that balances the demands of innovation, regulatory compliance, and patient safety. The practical implications of the framework include, offering a structured methodology that benefits entrepreneurs, mentors, and investors alike. This would especially be beneficial for first time entrepreneurs in the digital health field, guiding them through the complex processes with multiple stakeholders including the inherent complexities of the digital health field.
In terms of academic contributions, this conceptual value framework is first of a kind for the digital health startups, giving an overarching and holistic view of value creation, capture and delivery for Dutch digital health startups. As touched upon previously, this has also opened a new avenue to research further and build an easy to use tool for entrepreneurs to give them actionable insights. So in that view, conceptual value framework presented in this report is really just a starting point for the further nuanced research in the topic. Similar to how the existing tools, say Business Model Canvas is widely utilized to guide startups across various sectors, this research initiates the development of a specialized tool tailored specifically for digital health startups. The conceptual value framework proposed in this study serves as an essential first step toward creating such a tool. Given that digital health startups operate within a unique regulatory and environmental landscape, this holistic framework is designed to address the specific complexities of the digital health domain, providing a comprehensive tool that en-compasses its intricate requirements. In essence, the conceptual value framework presented in this study is just the beginning—a starting point for deeper, more nuanced exploration in this evolving field.
This research not only fills a crucial gap in the literature but also lays basis for further research that can serve as a detailed road map for digital health entrepreneurs, helping them to effectively align their business models with the unique challenges and opportunities presented by the Dutch healthcare system.

In treating patients with pancreatic cancer, multidisciplinary team (MDT) meetings have been established as the clinical standard for discussing patient cases using combined expertise from various specialisations. However, despite the combined expertise, 19%-33% of all pancreatic surgeries is observed to be prematurely abandoned due to locally advanced pancreatic cancer or metastatic disease. Furthermore, MDT meetings typically feature an open discussion format that can be subject to social influence factors affecting the overall objectivity of individual expert opinions. Subsequently, this research explores Artificial Swarm Intelligence (ASI) as a potential technology to overcome the aforementioned issues. Through an experiment, this research tests the use of ASI in a simulated MDT meeting and examines its effects on the accuracy of resectability assessment. Furthermore, a survey is conducted to assess the perceived impact of ASI on social loafing and social bias influences, as well as potential enablers and barriers for the potential implementation of ASI. Based on the experiment results, the use of ASI shows equal assessment accuracy compared to assessing tumor resectability through discussion as with regular MDT meetings. However, with regard to social influ- ence, participants assessed ASI to moderately drive reduction factors that reduce social loafing and social bias - suggesting indirect benefits to the objectivity of the decision process.

The rapid digitalisation of healthcare has underscored the importance of cybersecurity in hospitals. Yet, there is an untapped potential to consider cybersecurity from the start, during the procurement of medical devices. This thesis investigates the current procurement practices in Dutch hospitals, focusing on how cybersecurity considerations are integrated into these processes. Despite the critical role of cybersecurity in protecting patient safety and data integrity, there is a notable gap in the literature regarding its integration into medical device procurement. This research aims to fill this gap by providing a comprehensive analysis of procurement practices and offering insights for improvement.

The study is structured into five phases: an initial literature review to define the research problem and identify knowledge gaps, desk research to overview existing policies, regulations, and scientific literature, semi-structured interviews with stakeholders in three Dutch hospitals and one external stakeholder, a framework analysis of the interview data to identify key themes and dynamics, and synthesis of findings into a comparative case study with practical recommendations.

The findings reveal that the procurement process in Dutch hospitals is multifaceted, involving various stakeholders from within the hospital and outside, such as doctors, IT staff, procurement departments, and manufacturers. The procurement process across the three participating hospitals showed a remarkable resemblance, generally following a similar structured approach. However, it falls short in prioritising cybersecurity, often treating it as a baseline requirement. In addition, external influences, including manufacturers, medical conferences, and peer opinions, could impact procurement decisions. Manufacturers often engage directly with doctors and provide trial installations to promote their devices. However, cybersecurity is often not prioritised, with functional and financial requirements taking precedence.

This thesis makes significant contributions to the field by providing detailed empirical data on procurement practices and stakeholder dynamics, highlighting the role of cybersecurity plays in Dutch hospitals, and offering practical recommendations for enhancing cybersecurity integration. By addressing the gaps in existing literature, this research provides a foundation for future studies and practical improvements in healthcare procurement.

The findings underscore the need for hospitals to adopt more structured and standardised approaches to integrating cybersecurity into procurement decisions, ultimately enhancing the security and resilience of healthcare systems against evolving cyber threats. This research contributes to both the scientific community and healthcare practitioners, providing valuable insights and practical guidance for improving procurement practices and ensuring better patient safety and data protection.

Recently, the deficiency present in female-specific health has been emphasized.Knowledge and consequently treatments with regards to female-specific symptoms and chronic deceases have been lacking. Previous research has shown the opportunity of female health apps to decrease this discrepancy.
Female health apps simultaneously contribute to women’s health understanding and awareness, while also supplying data for necessary female-specific health research. However, this requires uptake and engagement among consumers. More importantly, it requires uptake among diverse women subgroups of the population. Otherwise, the apps likely contribute to increased health disparities present between different socio-demographic groups and biased female health research.
Therefore, research uncovering the influence of app factors on female health app uptake, while accounting for the diversity in the female population is necessary. The specific female health apps under scrutiny in this research are fertility & menstrual tracking apps (MTA), due to their relative popularity, diverse potential consumer group and importance in women’s lives. Consequently, the following research question is answered in this research to contribute to closing the knowledge gap of MTA preference among diverse women: ’To what extent do various factors influence fertility & menstrual tracking app uptake by women from diverse backgrounds?’

Cardiovascular diseases (CVDs) are a leading cause of death globally, causing 38% of all premature deaths. Providing care for the patients who survive is considered a priority for healthcare managers. In the Netherlands, 1.7 million people currently are diagnosed with cardiovascular diseases. After experiencing and surviving a CVD event, patients require support to get their lives back on track. However, over the next years, the number of patients is expected to increase to 2.6 million people, creating a burden on the healthcare system. Moreover, the costs of healthcare have been increasing over the last few years, decreasing the accessible and affordable for the patients to receive care. Intervention is needed to keep the quality of life of patients high. However, most interventions focus on the prevention of CVDs, with no attention to patients that already diagnosed with cardiovascular diseases. This research presents a model for the support of patients with cardiovascular diseases within the Netherlands. It is done in conjunction with Harteraad, a non-profit Dutch patient organisation that represents the interests of the 1.7 million patients. The model aims to explore the effect of interventions on the lives of patients while keeping the investment cost-efficient. To successfully answer the research question, four steps were taken. First, a literature study was conducted to find potential candidate interventions that Harteraad can implement. The results from the literature study suggest that the priority lies in interventions on physical activity, mental health and medication adherence. In the second step, a causal loop diagram (CLD) was built that maps the interventions to outcomes. For this research, the main outcome variable is the social returns on investment (SROI). SROI measures value creation on a social, environmental and economic level. Secondary outcomes include deaths, hospitalisations, and quality of life. All three of which are used to calculate the SROI. The CLD shows that the interventions affect the outcomes by improving patient behaviour. Whether that is in more exercise, seeking mental support or medical adherence. In the third step, a System Dynamics model was developed to simulate the economic effect of different interventions. Population data were retrieved from the Hartstichting, whereas data sources on input values were found in academic literature. The latter being a source of uncertainty, as healthcare systems across countries cannot be directly compared. So in the fourth step, uncertainties were incorporated into the SD model and tested systematically. The results for the simulation show that the SROI is positive for six interventions. As such, the recommendation is to invest in either of those interventions. More specifically, for physical activity, the efficient interventions are “Active-at-Home”, “Video Gaming”, and “Group-Based Training”. For mental health, the efficient interventions are “Care Coordination”, “Cognitive Behavioural Therapy”, and “Telemedicine”. Lastly, for “CombiConsult”, the recommendation is to offer additional mental support as well to create social return. Although the model is able to give insights into potential interventions, more research is required. The model is only a simplified representation of the real world. Data was either lacking or outdated, creating nuance in the model results. As such, the model cannot be used to give the optimal solution. These nuances thus need to be addressed in future research. Despite the limitations of the model, the research provides societal and scientific contributions. The research shows that system dynamics modelling is a suitable method to model the support of patients. Moreover, the model is able to determine if interventions are cost-efficient while increasing social benefits to the patient. This research furthermore adds a contribution by performing a systematic uncertainty analysis and so on, offering aid in robust decision-making. Lastly, the model is suitable to be used in different countries under different healthcare systems. As such, this research contributes to the research on patient support.

Medical equipment supplied to low- and middle-income countries (LMICs) are often substandard and inappropriate to the contextual needs. The majority of equipment entering these countries are donated or financed by external agencies. Procurement of equipment also happens through public tendering. However, the assessment and management of the equipment entering these countries are found to be inappropriate and ineffective. This has resulted in equipment that remains unused, malfunctions, or fails to meet its expected lifespan. This ultimately causes harmful consequences to the patient groups in LMIC. It is high time that this situation needs to be addressed and implement measures to provide quality, safe, affordable, accessible, and appropriate health technologies to people in these low-resource settings. One approach to create transparency around the notion of appropriate health technologies for LMICs is by creating a set of measurable criteria, tested in the form of a label. A global team of BioMedical engineers undertook an initiative to implement such a label, namely, ‘Appropriate Medical Equipment’ or ‘AME Label’. This research aims to examine the feasibility and constraints associated with implementing such an initiative from the perspective of medical equipment manufacturers.

The study investigated four main topics to answer the research question: ‘How can a new product label support medical equipment manufacturers to sustainably enter the healthcare market of low- and middle-income countries?’. These are the value of product labels in the market, regulatory challenges faced by manufacturers in the MedTech industry, challenges for manufacturers in entering LMICs, and perception of manufacturers on the concept of AME label. A combination of desk research and qualitative interview was used to deduce the conclusion. Initially, a case study was conducted involving a medical equipment manufacturer based in the Netherlands, whose operations primarily targeted LMICs. The data was collected through one-to-one online semi-structured interviews with managers within this organization. The preliminary findings formed were later validated through survey and interviews conducted with a globally diverse sample size including industry and academic experts.

The results of the study indicated that the adoption of AME label has the potential to benefit manufacturers with enhanced brand value, increased visibility, improved credibility, and greater product transparency in their target markets. These factors can in turn build confidence and trust among LMIC stakeholders on AME-labeled products, opening doors for sustained business opportunities for manufacturers in these countries. By optimizing the product design towards the contextual requirements and including competitive product features, manufacturers could use the AME label as a differentiating factor in their sales. Subsequently, manufacturers could attain higher commercial value for their products and improved operating efficiency in the healthcare market of LMICs. At the same time, it is found that the introduction of the AME label could increase the complexity of the regulatory system. Manufacturers of all sizes face challenges while undergoing any regulatory process, adhering to regulatory norms, or undertaking any product label. This is unavoidable for manufacturers while supplying medical equipment across boundaries. Therefore, the inclination of manufacturers to adopt AME label depends on how effectively it streamlines the supply process, cuts administrative costs, reduces documentation work, and expedites the distribution of equipment to target countries.

Considering the novelty of the label, there are some concerns that could hinder the full-fledged adoption of the AME label by manufacturers. These concerns primarily revolve around the reliability and trustworthiness of the label. To overcome these concerns, the AME team should take into account the following aspects when implementing the label. They should carefully plan and execute steps to ensure that the label is recognized and accepted by authorized bodies like the UN, WHO, etc. It is equally important that measures need to be taken in the direction where the label is validated by all relevant stakeholders in LMICs. It is also essential to establish a clear positioning of the AME label within the regulatory system by highlighting the unique testing methods and distinctive tangible advantages it offers to the manufacturers compared to existing labels. By addressing these concerns, the widespread adoption of the AME label by medical equipment manufacturers could be achieved, leading to the availability of appropriate equipment in LMIC hospitals, and ultimately benefiting the patient groups within.

Healthcare is an essential part of our lives, promoting and preserving the health of individuals and society. The industry has been evolving at a high pace over the last few decades, driven by technology and growing care demands. This progress is currently having an opposite effect on the overarching objective of serving healthy living due to the increasing environmental footprint and social toll of the industry. Today, healthcare accounts for nearly 4.4% of global CO2 net emissions worldwide, while in the Netherlands, the sector accounts for about 7% of the national footprint. In particular, Radiology represents a clinical area of great concern, being a major contributor to the healthcare carbon footprint due to its high energy consumption and hazardous waste generation. Furthermore, Radiology professionals face heavy workloads due to rising demands for imaging exams, driven by patient expectations on the one hand, and the convenience of leading doctors, as well as existing differences in protocols across hospitals, on the other hand. These complex Environmental, Social, and Governance (ESG) challenges must be approached in an integrated way, to effectively enable the embedding of sustainable practices at the core of healthcare, accelerating in this way the transition towards a circular economy across the industry. This research aims to provide broad and deep insights into the Radiology ecosystem in the Netherlands, ESG definition guidance, and an end-to-end ESG strategic design toolkit that aims to simplify, measure, and integrate ESG efforts across healthcare. An integrated department-, hospital-, national-, and global approach is being proposed to streamline efforts towards 2030 ESG goals and beyond.

A systemic design approach is proposed for this study, combining mixed methodologies of qualitative, quantitative, and co-creation efforts with cross-disciplinary experts from six university hospitals, as well as the national Radiology association in the Netherlands. The steps towards framing, prioritizing, and embedding ESG into the Radiology workflow are consistently captured as research findings, concluding contextual insights on the ESG impact across the different levels of the system. These are represented as an ESG pyramid in this study. Identifying key ESG healthcare challenges and influential entities in the system offers a foundation for strategic dialogues on ESG goals definition. Additionally, an ESG healthcare ecosystem map has been developed to further understand the dynamics among key system stakeholders, on three main dimensions: financial, clinical compliance, and ESG. The perspective of embedding ESG in Radiology, within the Netherlands, is taken as a representative industry case study. Consolidation of clinical workflow data, operational insights, and current ESG context resulted in a cross-hospital view of Radiology ESG hotspots, dependencies, and opportunities. Interventions on ESG hotspots are then addressed and positioned, at corresponding decision power levels, within the larger system. Furthermore, a solution for integrated ESG value-impact measurement and continuous monitoring is proposed. Such a simplified and transparent way of working has the potential to increase awareness, drive collaboration, significantly reduce ESG spending and identify new circular value opportunities.

The outcomes of this research indicate that embedding ESG hotspots into the Radiology workflow should be approached in a holistic and systemic way. The ESG strategic design toolkit can facilitate relevant dialogues on the value and impact of ESG interventions across levels in the healthcare ecosystem, enabling hospitals and departments to effectively define ESG goals and programs. This simplifies complexity and provides consistency across the broader system hierarchy.

The intellectual disability population increased from 65.545 people in 2011 to 116.200 people in 2020. In other words, the population almost doubled in less than ten years' time. Interventions are required to be able to make sure everyone receives the needed care. Therefore, the causes for the growth should be further examined before any decision on intervention can be taken. This thesis contributed to understanding the factors influencing the increase in the intellectual disability population and evaluating the behaviour of the sector. To improve the understanding, a System Dynamics model was designed analysing the influence of self-reliance on the intellectual disability population.

The question of why there is an increase in the intellectual disability population has been attempted to be answered within this study. After evaluating multiple factors as a cause for the growth in the intellectual disability population, self-reliance was selected as being an important factor. In the conceptual model, three reinforcing feedback loops were found, indicating that when there is no intervention, the self-reliance of the intellectual disability population continuously decreases, resulting in more people applying for care from the Wlz. In the qualitative model, this proposition could not be rejected, indicating the importance of the role of self-reliance on the growth of the intellectual disability population. Especially for the population with an IQ score between 70 and 85, more attention should be paid to the increase or maintaining of self-reliance. In that way, the intellectual disability sector is always able to care for the ones who cannot live without.

Social enterprises play a significant role in achieving the Sustainable Development Goals (SDGs). Measuring the social impact of social enterprises presents several challenges, including the complexity of social issues, the need for standardized metrics, and the limited resources available. Obtaining funding is crucial for social enterprises to fulfill their mission. When applying for funding, they often have to report on the social impact they generate, as it is an essential part of the value they create. Another difficulty is that social impact is experienced differently by various actors. The research, therefore, adopts an exploratory approach to understand how funders and social enterprises perceive the impact assessment, particularly for those contributing to SDG 3. Thus, the central question of this research is 'How are funders and social enterprises aligned in measuring social impact on SDG3?'.
This research was conducted in partnership with Unifix Care. Unifix Care is a social enterprise whose mission is to improve access to safe surgical care in Sub-Saharan Africa. The findings presented were derived from a review of the literature, interview rounds, and a survey. The first round of interviews were exploratory interviews with general impact funders. The second round consisted of interviews with social enterprises contributing to SDG and funders funding these social enterprises. The survey aimed to validate statements based on literature and interviews and to give an idea of the data funders and social enterprises use some impact indicators.
A finding of this research is that the change in how the Theory of Change is used, from an internal tool to an external accountability mechanism, indicates a misalignment between funders and social enterprises. While funders may demand accountability, social enterprises initially used it for internal improvement. This shift suggests a divergence in how both parties perceive and utilize this tool for measuring social impact. Social enterprises' power imbalance and dependency on funders can lead to a misalignment in measuring social impact. Contributing to this is the fact that aligning the mission of social enterprises with the strategic goals of funders is considered very important.
A subsequent finding is that there could be a reporting difference between easier-to-measure KPIs from the Theory of Change (input, activity, output) and harder-to-measure KPIs more aligned with the overall goal (outcome and impact). The survey results indicated a mild divergence in opinions between funders and social enterprises on the priority of measuring input, activity, and output indicators versus outcome and impact indicators. Social enterprises were somewhat in favor, whereas funders were somewhat opposed. In terms of quantifying outcome and impact indicators, a simple, state-of-the-art calculation was generally adequate for most social enterprises, in contrast to the preferences of funders. These findings could result in the miscalculation of social impact generated by social enterprises. For this, it is necessary to bring back the Theory of Change as an integrated framework.
Another finding is that both social enterprises and funders focus more on a social enterprise's positive rather than negative impacts. Given that every social enterprise likely has some adverse effects, these should be acknowledged to ensure a comprehensive assessment of the overall positive social impact. Additionally, it is found that the inconsistency in defining 'impact investors' and the varied interpretation of 'impact first' approaches reflect a lack of uniformity in how social impact is perceived and measured. This variability can lead to challenges in aligning the measurement approaches of funders and social enterprises.
The main limitations of this study are related to the small survey sample size, which only provides an indication. More research is needed to draw definitive conclusions. Another limitation is the selection and categorization of indicators in the survey; an attempt was made to do this as generically as possible. However, future research would benefit from validating this selection and categorization by multiple experts.
The following recommendations aim to foster effective collaborations between funders and social enterprises, enhancing transparency and accountability in social impact measurement. A publicly accessible database should be created to share the social impact results of social enterprises. This will allow for establishing normal distributions and facilitate the assessment of the likelihood of success of similar interventions. Therefore, a portion of funding should be dedicated to monitoring the long-term impact of social enterprises. This enhances transparency and allows for a deeper understanding of the effectiveness of various investments in achieving social impact. Funders should also publicize the Theories of Change of the social enterprises in their portfolio. This transparency helps understand how the impact is achieved and mitigates the risk of 'impact washing.' The initiative for these recommendations, particularly the database and publication of Theories of Change, should come from the government or the actors funding the funders. They have the influence to drive more impact-focused decisions and support impact-driven social enterprises. Future studies should incorporate comparative cognitive mapping and game theory to understand better the preferences and incentives of funders and social enterprises. Additionally, using Agent-Based Modelling or System Dynamics with the EMA workbench could yield insights into the effectiveness of specific policies in a complex, uncertain environment.

Substance use disorders, particularly alcohol use disorder (AUD), are a major global health challenge, significantly impacting morbidity and mortality rates. In the Netherlands, around 20% of the population is affected by excessive alcohol consumption, with a notable treatment gap and disproportionate effects on the elderly. Despite increased research into AUD treatments, patient numbers remain stable, straining healthcare systems. Moreover, the Dutch government anticipates that addressing the needs of both diagnosed and undiagnosed patients, the workforce should be increased in the general healthcare sector from the current level of 16.67% to 25% of the total Dutch workforce by 2040. Furthermore, existing regulations and policies appear inadequate in effectively managing these demands.

This study aims to explore the socio-organisational drivers and policy effects on the Dutch mental health care system, focusing on AUD, to maintain sustainable quality care. It examines organizational drivers, expert perspectives, policy influence on system dynamics, and the relationship between capacity shortages and care quality. The research employs a mixed-method approach, including a literature review, exploratory interviews, a Participatory System Dynamics Modeling (PSDM) workshop, and a comparative analysis of data from 12 mental health services (MHS).

Key findings include the significance of internal factors like patient satisfaction and therapeutic alliance, and the crucial role of over and undertreatment considerations during treatment processes. External factors like self-coping, and individualization and blurring of alcohol in shops also influence both treatment effectiveness and alcohol consumption. Current policy regulations inadvertently contribute to capacity shortages and treatment gaps. System Dynamics (SD) modelling reveals that increased regulatory pressures and quality care demands lead to capacity being consumed by administrative tasks and budget gaps. This relates to a 'fixes that fail' archetype, combined with social dynamics like an ageing population and increased alcohol consumption, exacerbates the 'growth and underinvestment' archetype in the Dutch mental healthcare system.

The study highlights the unintended consequences of current policies, such as disjointed preventive measures and reduced practitioner autonomy. It also emphasizes the complexity of healthcare systems as revealed by the challenge of identifying cause-and-effect due to multiple aggregational levels, the diverse perspectives on the system both by literature and experts, the varied healthcare contexts and the multi-disciplinary and collaborative nature of (mental) healthcare. Key limitations include not fully addressing safety in health quality and challenges in integrating quantitative methods.

This thesis underscores the importance of a holistic approach in healthcare, considering both social and organizational aspects. It suggests that current policies may lead to over-regulation or insufficient prevention awareness, impacting both society and MHS organisations. Adopting a holistic system approach can enhance further understanding of policy impacts crucial for preventing a growing treatment-capacity gap and ensuring a sustainable mental health care system for society’s vulnerable members.

In Low and Middle-Income Countries (LMICs), a significant challenge lies in the misalignment between available medical equipment and the specific needs of these regions. For example the needs of being adapted to low resource settings. A lot of medical equipment is not adapted to be operated in low-resource settings. This situation has prompted a growing interest in seeking comprehensive solutions that ensure clinical safety, adaptability to local needs, and affordability with the available resources. Previous strategies have had limited success, as they primarily focused on isolated aspects such as providing extra training or ensuring spare parts and leaving medical equipment unused or non-functional. Presently, a global team of experts is actively exploring the potential of an innovative solution – the "Appropriate Medical Equipment" (AME) label. The idea of this team of experts is to develop such a label so that those who are purchasing equipment know that the equipment is appropriate for the LMICs settings. Because, often, equipment is donated or funded by external organizations with procurement processes that prove inappropriate and ineffective. The unused and non-functional medical equipment contributes to critical issues, adversely impacting the functionality, usability, and lifespan of medical equipment, thus impeding its vital role within the healthcare system. Therefore, this research will delve into the requirements and characteristics necessary for developing this new product label, considering the perspectives of experts related to LMICs.\\

The research addressed four sub-research questions that collectively provided answers to the main research question: \textbf{\textit{"What characteristics of an Appropriate Medical Equipment label would facilitate the intended use of medical equipment in low- and middle-income countries?"}} To answer the main research question, a design approach was employed, proving to be a valuable problem-solving method for this multifaceted problem. The design approach encompassed four phases: exploration, ideation, prototyping, and prototype review. In the exploration phase, four key steps were undertaken. Firstly, a literature review was conducted to investigate the current usage and experiences related to labels and certificates for medical equipment as well as labels in general, with a focus on experiences pertaining to medical equipment labels and certificates. Secondly, scientific literature was used to identify system factors influencing the life cycle of medical equipment. Insights from this literature were translated into IDEF frameworks, which formed the foundation for subsequent interviews. These IDEF frameworks served as structured way of showing information and were used as boundary objects throughout the research and interviews. Thirdly, interviews were conducted with experts, validating the information obtained from the literature and enhancing the IDEF framework. The fourth step was consolidating the insights to formulate a problem statement. This problem statement encapsulated key stakeholders' needs, requirements, desires, and dilemmas. Following the accumulation of knowledge from the exploration phase, the ideation phase began. During the ideation phase the design space matrices were developed for each of the categories. This design space matrix showed the decision making process between categories and means. The third phase, prototyping, involved synthesizing the knowledge gathered from the previous phases to create a prototype. Lastly, in the review prototype phase, the prototype was discussed with experts who provided feedback and opinions. Following the prototype review, consideration was given to future steps, determining the best approach for addressing this complex problem.

The study concludes that to facilitate the intended use of medical equipment in LMICs, a product label should incorporate essential characteristics, identified through a comprehensive review of literature and expert interviews. These characteristics encompass safety, design orientation, training, finance, maintenance, spare parts, service, usability, transparency, and end-of-life considerations. By prioritizing and integrating these features, the label has the potential to indirectly improve the overall life cycle of medical equipment in LMICs. The requirements for such a product label are identified through expert interviews, encompassing training, technical aspects, and safety considerations.

Beyond individual characteristics of the label itself, this study also explored the success of label implementation for medical equipment in LMICs. Several concerns require attention for a successful label implementation. The concern covered in this research is the potential misalignment of values and agendas among stakeholders can hinder commitment to a new product label and its prototype. To address this, incentives should be tailored to meet the specific needs of each stakeholder. Research indicates a preference for the bottom-up approach in label development due to its effectiveness in managing complexity and enhancing project success rates. Starting with end-user testing and progressing upward to demonstrate the label's value and encourage adherence to its standards can motivate manufacturers. By integrating the label's unique characteristics with advocacy efforts and a bottom-up approach, it has the potential to facilitate the intended use of medical equipment in low- and middle-income countries, enhancing the crucial role of medical equipment in healthcare systems in these regions.

The findings in this thesis hold significant importance for individuals seeking solutions to reduce the high rates of unused or non-functional medical equipment in LMICs. This thesis explores the distinctive characteristics of a label and how these characteristics can address the challenges present in the medical equipment life cycle. By gaining a clear understanding of these issues, organizations and experts can leverage these insights when developing solutions to reduce high percentages of unused and non-functional medical equipment, such as the product label. Lastly, the thesis introduces an initial prototype for a product label for medical equipment in LMICs. This prototype is a start for future study and can be used as a starting point for the actual development of the product label.

In 2020, the world was hit by a global pandemic through COVID-19, causing millions of deaths worldwide. The last two years proved that a health-related crisis like COVID-19 strains us as a society and the capacities of health systems worldwide. Severe infections of COVID-19 require higher capacities of hospital beds, ICUs with ventilators and Personal Protective Equipment. For health systems, the question arises of how to secure enough PPE and ventilators before and during a health-related crisis like COVID-19.
This research explores how health systems can create responsive and prepared supply strategies to meet the rising demand for critical medical supplies during health-related crises. Concerning the availability of critical medical supplies, preparedness entails stockpiling as a supply strategy. Furthermore, preparedness entails actions decision-makers in health systems can take to increase the effectiveness of responsive supply strategies. Responsiveness refers to supply strategies used at the beginning of a health-related crisis in the short term. Responsive supply strategies include ramping up domestic production, supporting innovations, loaning medical supplies, and purchasing medical supplies from the world market or through direct tender.
In this research, a System Dynamics model was developed to explore how health systems can create resilient and responsive supply strategies, a System Dynamics model was developed, focusing on the English health system as an example for the Global North. Given the deep uncertainties surrounding the supply chain of critical medical supplies, Exploratory Modelling and Analysis was conducted to identify candidate policies and explore their performance given the uncertainties. Specifically, uncertainties affecting the success of purchasing supplies through direct tender and from the world market had the most impact on the availability of PPE and ventilators.
The results of the analysis and the findings in the literature provide the following recommendations to decision-makers in health systems to create prepared and responsive supply strategies that ensure the availability of critical medical supplies during health-related crises. Decision-makers can implement (i) stockpiles exhibiting higher inventory levels than recommended, and no delays concerning the operation within the warehouse or the delivery of the medical supplies. Furthermore, it is suggested to (ii) implement diverse supplier frameworks and crisis frameworks, (iii) diversify supplier, (iv) implement stocks of raw material for domestic production. It is useful for decision-makers to apply several responsive supply strategies simultaneously. Furthermore, health systems can further investigate additional supply strategies.
In this research, it is assumed that collaboration is not relevant nor of interest for the English health system. Hence, it would be interesting to explore the effect that sharing critical medical supplies between national health systems could have on the shortage of PPE and ventilators in the future.

Technologies for Low- and Middle-Income Countries (LMICs) need to take
into account local cost, usability and maintenance challenges, and ‘modular’
device designs can be one way of overcoming these challenges. However,
despite research into the design advantages of these devices, the adoption
challenges have not yet been investigated.
This research aims to make the adoption of modular laparoscopic instruments possible in LMICs, starting in India with four types of local hospitals. It aims to find the various actors and factors, including stakeholders that play a role in making this technology successfully adopted in India. The study involves desktop research to analyse LMIC markets with respect to surgical instruments, followed by qualitative research to identify barriers and facilitators to the adoption of these instruments in the Indian context. For this, we will conduct interviews and observations with experts and practitioners developing and using laparoscopic instruments in Indian hospitals. All findings will result in a case study that combines all findings and concludes with a framework that covers all aspects related to the successful adoption of modular steerable laparoscopic instruments with
interchangeable end-effectors

Background & Objective: The unprecedented value and long­term uncertainties of gene therapies have challenged established health technology assessment (HTA) methods. Real-world data (RWD) and real-world evidence (RWE) may mitigate the encountered uncertainties. However, empirical evidence appears to be lacking in the literature. This research aimed to provide this evidence and identify implications for EU-wide gene therapy joint clinical assessments.

Methods: An initial literature review laid the theoretical foundation for the research. A retrospective comparative analysis delivered empirical evidence on RWD/RWE usage in gene therapy HTAs. Preliminary findings were probed in three use cases and verified in semi­structured interviews.

Results: Nineteen HTA reports published by the HTA bodies G­BA (Germany) and NICE (England) were identified for the ten in­scope gene therapies.
Whereas NICE had an average inclusion of 14 sources per HTA report (with an acceptance rate of 56%), G­BA had 8 (with 32% acceptance rate).
While RWD/RWE supporting evidence on an external comparator had the lowest acceptance rate, RWD/RWE on intervention effectiveness had the highest acceptance rate. Insufficient information to substantiate the choice of RWD/RWE and inappropriate RWE study design was the most common exclusion rationales for RWD/RWE.

Conclusions: The presented empirical evidence adds to the current knowledge base in two ways; it provides empirical evidence on HTAs of gene therapies (1) and RWD/RWE usage in gene therapy HTAs (2). This work provides insights into how RWD/RWE usage differs between HTA bodies and explicates relevant considerations for gene therapy manufacturers when using RWD/RWE in future HTA submissions. It also proposes that alignment on evidentiary requirements and assessment elements will optimise the transferability of future joint clinical assessment outcomes to national HTA bodies. Knowledge transfer and knowledge sharing initiatives will play a pivotal role in achieving such a consensus.

Currently, medical technologies in Sub-Saharan Africa (SSA) are not yet sufficient to provide robust healthcare systems. This is not due to it being unavailable, but due to a large portion of present technologies being non-functional. This non-functionality also causes a lack of adoption of medical technologies. Through a T-shaped case study (e.g. a multiple case study with one case worked out in-depth), current barriers in adoption are uncovered. These are then integrated into an actionable framework that can be used by organizations implementing medical technologies in SSA to uncover barriers applicable to them, as well as proposed mitigating strategies to overcome these barriers. Themes included affecting adoption in this thesis are: maintenance, training, organizational and behavioral change. Barriers discovered can be divided into three categories. The first being resource-barriers, covering time, money, human and materials. Secondly, institutional barriers, covering policy, trust and the need for breaking habits. The last barrier category covers communication between client and organization. The framework offers the possibility to find applicable barriers based upon characteristics of an implementation situation. The implementation situation herein is medical equipment (ME) being implemented by an organization (O) into a client organization (CO). Using the knowledge on barriers in an early stage provides opportunity for the organization to overcome these barriers by informed analysis of mitigating strategies that they could implement.

The gap between planning and budgeting is a problem for improving health systems. In decentralisation health care services, authority, resources, and responsibilities are moved from central actors (i.e. national government) to peripheral actors (i.e. municipalities). Adding the risk of creating silos within sub-national governments, creating the need for collaboration in some form. Data analytical forecasting, like prognosis tools, may facilitate planning for health care service implementation. When operating on the interface between actors, as a boundary object, they may mitigate the risk of fragmentation and isolation associated to decentralisation, by enabling collaboration.

In the case of decentralised Assisted Living in the Netherlands ("Beschermd Wonen") citizens dealing with psycho-social problems, receive guidance to participate in society. Newly responsible sub-regions have limited facilities and funds for their own citizens.

Newly responsible sub-regions having limited facilities and funds, may face incurring costs and inaccessible care when citizens seek to other areas due to uncoordinated implementation and elimination of facilities. To plan these, a prognosis tool was designed and developed for the three sub-regions.

A literature review was conducted on decentralisation of health care services globally. The prognosis tool’s technical design and development, and observations during, were studied. Analysed Interviews with actors involved in the prognosis tool, assessed if and how collaborating was enabled.

Lack of research on the implementation of decentralisation for health services, the use of prognosis tools for this purpose, the risk fragmentation resulting from independent processes and lack of system focus and the need for collaboration were highlighted in the literature, justifying building and testing a tool.

The design of the tool was therefore intentional: colour codes stimulated usability, the three sub-regions sub-files were stored in one place promoting transparency, and standardisation was stimulated by representing all sub-regions’ demands and resources into a general fitting categorisation and identical calculations from input to results for all sub-regions.

The tool and outcome is usable for agreements with care suppliers (procurement) or housing and enables organisation through agreements between sub-regions.

The meta-analysis of the interviews revealed that from the prognosis tool’s design and development, shared understanding emerged through shared language and extensive problem demarcation.
An independent expert mediated the needs of sub-regions, staying close to the task. This combined with the factual outcome led to insight and clarity in the content of subregions’ own and other’s task.

Inducing trust and confidence in the relation and in achieving own and shared goals. Leading to tranquility and comfort, setting the atmosphere for collaboration. By clarifying the uncertainties and interdependencies, where or why collaboration is needed (the identified risk) has stimulated collaborative action.

This prognosis tool has enabled collaboration for decentralised health services by addressing both socio-technical aspects. The latter integrate the effected sub-systems, ensuring the outcome can be used for organising future steps (such as procurement). The former, extensive problem demarcation and shared language emerged a shared understanding of the system. In combination with the factual outcome (prognosis), insight and clarity was created into the actual need and to enable trust and comfort, enabling collaboration.