MEDICAL
DOMAINS
To test and validate the UNIFIED Framework in real-world settings, the project applies its methodology across five medical domains and six complementary use cases. These use cases represent diverse clinical areas, patient populations, and healthcare contexts, allowing the project to explore how patient-centred evidence can be generated and integrated into healthcare decision-making.
Each use case combines patient preference information, clinical outcome assessments, and digital health technology measures to better understand what outcomes matter most to patients and how these can be captured in clinical research and care. By applying the framework across different diseases and healthcare systems, UNIFIED can evaluate its applicability, comparability, and scalability across multiple clinical contexts.
Every use case is supported by a dedicated public–private leadership team. This includes a Clinical Lead, who ensures clinical relevance and study feasibility; an Industry Lead, who supports efficiency and alignment with real-world development and regulatory needs; an Academic Methodology Lead, who provides expertise in analysing and integrating patient-centred data; and a Disease-Specific Patient Organisation Lead, who ensures that the approach remains grounded in patient perspectives.
Together, these teams work collaboratively to design and implement the studies, ensuring that the results are scientifically robust, clinically meaningful, and aligned with the needs of patients, healthcare providers, regulators, and policymakers.
1 - Paediatric Radiation Oncology
This medical domain includes two complementary use cases: paediatric oncology patients undergoing curative radiotherapy and their parents or caregivers, and long-term survivors of childhood cancer. By covering both active treatment and survivorship, this use case aims to provide a comprehensive understanding of patient and family needs across different stages of the care journey.
The first use case focuses on patients undergoing radiotherapy. It examines patients’ preferences for psychoeducational interventions designed to reduce anxiety and the need for sedation during treatment. Clinical Outcome Assessments (COA) and Digital Health Technology Measures (DHTM) will also be used to assess anxiety, depressed mood, and distress. These insights will help identify approaches that can improve treatment success while reducing long-term health and economic impacts.
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The second use case focuses on long-term survivors of paediatric radiation oncology. Surviving childhood cancer, particularly after radiotherapy, can carry a risk of developing health problems later in life. Therefore, survivors of childhood cancer in the Princess Máxima Center receive a survivorship care plan, which includes a cancer treatment summary and screenings tests that are recommended based on this summary and on survivorship guidelines. In this use case patient preferences regarding the survivorship care plan will be examined. By combining insights on chronic effects and patient preferences, this work will help support more personalised survivorship care.
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Together, these two use cases capture the full spectrum of challenges faced by children with cancer and survivors, helping to advance more holistic, effective, and sustainable patient-centred care.
2 - Lung Cancer
This use case is starting in Italy, with the hope of extending to Spain, Germany, and Austria. It leverages both prospective and historical patient data available to the UNIFIED consortium. The cross-border approach allows researchers to explore how differences in regional healthcare systems—such as variations in access to care—affect treatment pathways and patient-centred outcomes.
Lung cancer patients often face complex and highly variable care needs, as well as significant side effects from treatment. By analysing data across different healthcare settings, this use case will help identify how care can be better tailored to patients’ individual needs.
Ultimately, the goal is to support more personalised and timely care for lung cancer patients, improving both survival and quality of life.
3 - Parkinson's Disease
Parkinson’s disease is one of the most complex neurodegenerative conditions, with symptoms that can vary greatly between individuals and over time. To better understand these fluctuations, this use case relies on digital health technologies (DHTs) to track real-time changes in symptoms and capture patient-centred outcomes through patient preference information (PPI) and clinical outcome assessments (COAs).
Because reliable biomarkers for Parkinson’s disease are still limited, DHTs offer valuable tools for the objective detection and monitoring of symptom changes and disease progression. These technologies can capture real-world data on both motor and non-motor symptoms as they occur in daily life.
In addition, DHTs can support patients in monitoring their symptoms and sharing meaningful information with caregivers and healthcare professionals. This can help improve communication, support more personalised care, and provide a better understanding of how Parkinson’s disease affects everyday life.
4 - Obesity
This use case addresses a condition with rapidly increasing prevalence and significant health and economic impact worldwide. People living with obesity often face stigma and barriers to care, making patient engagement particularly important.
Digital health technologies (DHTs), including interactive tools, offer new opportunities to capture patient preference information (PPI) and clinical outcome assessments (COAs) in this field. These approaches can help better understand patients’ experiences, treatment preferences, and outcomes. At the same time, research in this area must reflect the wide socio-economic diversity of people affected by obesity, including those from underserved communities.
Many individuals undergoing treatment for obesity struggle to achieve substantial weight loss. However, even a 5–10% reduction in body weight can lead to meaningful improvements in metabolic health. By identifying effective patient-monitoring tools and integrating them into care, this use case aims to strengthen patient motivation, improve adherence to treatment recommendations, and support better long-term disease management. These tools may also help enable earlier detection of complications and support more personalised care for people living with obesity.
5 - Juvenile Idiopathic Arthritis
This use case is focused on juvenile idiopathic arthritis (JIA) which is a complex, lifelong condition with variable outcomes and treatment burden. The study will measure the preferences of parents and patients of both paediatric age (under 18) and young adults. The JIA team will examine preferences for clinical endpoints that matter most to patients and parents. The study will also explore effective approaches for collecting these clinical outcome assessments (COAs) in clinical trials, with a focus on what digital health technologies (DHTs) are preferred. Improving what data is collected and how these data is gathered in clinical studies can help increase the quality of patient-centred evidence and improve data collection completion rates.
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A unique aspect of the use case is that it includes responses from both patients and parents – enabling a dual perspective on these preferences for COAs to be measured in trials, and the DHTs to collect them. These dual perspectives are critical to understanding treatment success given the increasing autonomy of youth with lifelong chronic conditions during the transition period from paediatric to adult care and shifting roles in shared decisions.
This use case aims to support future clinical trials that better reflect what matters to patients and parents, and are easier to participate in.