Working towards a national End Stage Kidney Disease Data System for Ireland

End Stage Kidney Disease and current data in Ireland

End Stage Kidney Disease (ESKD) is defined as having such a degree of kidney disease that the person is now on long-term Renal Replacement Therapy, either with a functioning Kidney Transplant or utilising one of the modalities of long-term dialysis therapies¹⁰. ESKD is a condition of significant cost and complexity for health services, in particular due to the need for these dialysis and transplant services¹¹. Because of this, the use of ESKD registries has been recognised internationally as being important for optimising patient care, resource allocation and planning for healthcare infrastructure¹². More than 70 such registries exist internationally, although their functionality, scope and complexity differ¹³.

In Ireland, the Kidney Disease Clinical Patient Management System (KDCPMS) is the main national electronic health record system, which provides data to support multidisciplinary care for patients with ESKD. KDCPMS also provides a core framework that can support registry functionality and data from KDCPMS has supported the publication of annual reports by the National Renal Office¹⁴ which have been used for service planning and is shared with the European Renal Association Registry. Another key existing resource in Ireland is the kidney transplant registry in Beaumont Hospital which has produced several academic outputs related to kidney transplant outcomes^15–17.

While these platforms/registries have significant value, they do not possess the governance, resources and scope to provide all the functions of a modern ESKD data system. In light of this and given the increasing prevalence of ESKD in Ireland (affecting over 5,400 individuals in 2024 and increasing by 3% per annum)¹⁸, there is growing interest in developing such an ESKD data system to optimise patient care and improve resource allocation¹⁹.

The National End Stage Kidney Disease Data System project

The goal of the National End Stage Kidney Disease (NESKD) Data System project is to support the development of an ESKD data system for Ireland. This data system should facilitate communication and interoperability with other similar systems, which are in the process of being created for other chronic diseases. This is particularly important in ESKD, given the extent of overlap with other chronic diseases such as hypertension and diabetes mellitus²⁰.

In planning such a data system, careful design, planning and execution is required to ensure it is sufficiently agile, longitudinal and multi-modal to meet the needs of its users now and into the future²¹. To achieve this, several considerations have been outlined in the literature²², the early stages being identification and consultation with a broad range of stakeholders.

The stakeholders identified as being critical to establishing an ESKD data system include clinicians involved in the care of those with ESKD, researchers, public health physicians, policymakers, advocacy groups, technical staff and ESKD patients themselves²³. Aspects requiring exploration with these stakeholders include the specific variables for collection on the registry, methods of data collection and entry, technical and research considerations and data governance and co-design of outputs²⁴.

The NESKD Data System project consulted widely with several stakeholders to better understand the needs and requirements for an ESKD data system in Ireland. This paper outlines the approach that we followed to facilitate this exercise. The Design Thinking process aimed at generating points of agreement culminated in two multi-stakeholder design workshops and a final multi-stakeholder summit. The focus of this was to identify the current needs of an ESKD data system in Ireland as well as develop consensus on the next steps in developing such a data system. The key objectives were:

Multi-Stakeholder design workshops

To develop a comprehensive and user-centred NESKD Data System in Ireland, we employed a Design Thinking approach, integrating this process into two multi-stakeholder design workshops, hosted by the University of Galway Ideas Lab in August 2024. This methodology was chosen to ensure active engagement with all relevant stakeholders, facilitating feedback and collaborative ideation to design a data system that meets the diverse needs of its users.

Use of Design Thinking

In order to guide a structured consultation process to agree these aspects, recognised and structured methods can be used. One such process is “Design Thinking”, whereby stakeholders are consulted on an iterative basis to ideate, design and prototype a new product or system²⁵. The use of this concept is well established in the business world, as well as the healthcare context²⁶. Design Thinking involves a process of detailed planning, which aims to provide a comprehensive understanding of a problem and of its potential solutions^16,17. Initial stages of the Design Thinking process involve “needfinding” to understand the existing context and identify the specific needs and barriers of the different stakeholders. This stage then translates into an ideation phase, where potential solutions (in this case aspects of an ESKD data system) can be generated. These solutions are then prototyped and discussed leading to further refinement and testing²⁵.

Design Thinking emphasises empathy, prototyping, and iterative testing to solve complex problems^16,17. This use of Design Thinking in the context of developing health systems such as the NESKD Data System aligns effectively with the application of constructivist theory, particularly the ideas pioneered by Jean Piaget. Constructivist theory posits that individuals construct knowledge actively, influenced by their experiences and interactions with the environment²⁷. In Design Thinking, the iterative engagement of our stakeholders mirrors this principle by fostering environments where participants actively build solutions through experiential feedback loops²⁵.

Structure of workshops

The workshops aimed to utilise the Design Thinking approach described above to initiate discussions around the development of the NESKD data system. Participants included nephrologists, nurses, data specialists, healthcare planners, researchers, and patient representatives.

To provide context, several presentations were delivered, offering insights into the current state of ESKD management and data systems both within Ireland and internationally. An overview highlighted the challenges in kidney disease management in Ireland and the need for a national data system to improve patient outcomes and resource allocation. Insights from the experience of the UK Renal Registry were shared, illustrating the benefits of having a comprehensive renal data system. An explanation of how the existing Kidney Disease Clinical Patient Management System (KDCPMS) supports renal service delivery in Ireland was provided, and a technical overview addressed the existing infrastructure and possibilities for integrating current systems into the new NESKD Data System.

The core of the workshops were collaborative discussions guided by the central question: "What does the National End Stage Kidney Disease Data System look like?" Participants explored this question from four perspectives:

The Patient: Considering what data and information would be helpful for patients in understanding and managing their care journey, including access to personal health records and aggregated data.

The Clinician: Identifying the types of data that clinicians need to enhance patient treatment, monitor outcomes, and improve service delivery.

The Healthcare Planner: Determining the data required for effective service planning, resource allocation, and long-term decision-making, emphasising the need for comprehensive, accurate, and timely information.

The Researcher: Exploring what data would facilitate research studies, support clinical trials, and contribute to the advancement of knowledge in kidney disease in Ireland.

Multi-Stakeholder design summit

To validate and expand upon the insights gained from the Design Thinking Process, a one-day multi-stakeholder summit was organised, featuring national and international speakers. The event was structured around three main sessions covering different topics, with a final session dedicated to developing consensus on the way forward. The summit was open to key stakeholder groups, including patients, clinicians, researchers, healthcare planners, and technical experts. Efforts were made to ensure diversity among delegates through targeted communications and by providing financial support to cover travel expenses for people living with kidney disease.

Figure 1 outlines how the above Design Thinking process coupled with the multi-stakeholder summit contributes to the development of guiding principles of the development of the ESKD data system.

Figure 1. Description of how this research contributes to broader objectives.

Design thinking workshop results

The workshops took place online on 13/08/2024 and 20/08/2024, with 24 and 18 participants present respectively. Table 1 breaks down their self-reported professional backgrounds.

Session 1 involved a focus on the patient and clinician perspective for the needs of an ESKD data system. Following the small group discussions, several common aspects/themes were generated. These aspects were then presented to attendees on an anonymous survey with participants ranking them in order of importance. The highest ranked outputs of said survey are detailed in Table 2.

Session 2 explored the healthcare planner and researcher perspectives. Again, participants were surveyed on the elements of an ESKD data system relevant to these perspectives. The most popular of these are detailed in Table 3.

Overall, this process of Design Thinking yielded valuable insights:

Results from the summit

The multi-stakeholder summit was attended by 62 participants, representing a diverse range of stakeholder groups, including nephrologists, nephrology nurses, data specialists, researchers, patient representatives, and international experts in kidney disease data systems (Table 1). The summit was structured around three main sessions, each focusing on different aspects critical to the development of the NESKD Data System (Appendix 3).

The first session provided an overview of the epidemiological work on kidney disease that has been conducted in Ireland, as well as experiences with renal registries in Scotland, Northern Ireland, and the United States. This session highlighted the benefits and challenges associated with existing kidney disease data systems and underscored the need for a comprehensive data system in Ireland.

The second session focused on the technical aspects of setting up a data system, including discussions on data quality, data management, governance, and database design. Participants discussed the complexities of integrating disparate data sources, ensuring data accuracy, and establishing robust governance frameworks to protect patient data and comply with legal requirements.

The third session addressed patient perspectives and ethical aspects of data collection and use. Patient representatives shared their experiences and emphasised the importance of patient involvement in the design and implementation of the data system. Ethical considerations regarding data privacy, consent, and the use of patient data for research and healthcare planning were also discussed.

During the final session of the summit, agreement was reached on the formation of three working groups to advance the development of the NESKD Data System. The first working group was tasked with addressing technical aspects, focusing on data quality, data management, data analysis, and outputs. The second working group was assigned to tackle governance issues, recognising the critical role of the Health Support System (HSS) framework and the need to align with national policies. The third working group was established to formalise a sustainable model for effective patient and public involvement (PPI) in the data system, ensuring that patient voices remain central in the ongoing development and implementation process.

This collaborative approach, bringing together diverse expertise and perspectives, was instrumental in fostering a shared vision for the NESKD Data System.

The needs of patients

In both the workshops and the summit, patients highlighted access to their own health information as a key concern. This included access to patients’ laboratory results (including recent trends), explicit information regarding their diagnosis, up to date list of medications as well as information on their status on the transplant list (where relevant). Overall, this desire for greater transparency of health information for patients is echoed in the literature, with access for individual health information being cited as a key desire of patients in the development of other registries or data systems^28,29. Furthermore, increased patient access to their health information, especially in those with a chronic disease is associated with increased adherence to medications, as well as improvements in blood pressure and glycaemic control^28,30,31. Systematic reviews have also identified an association between patient access to their electronic health records and increased patient satisfaction and more positive perceptions of the physician-patient relationship^28,32.

Challenges from a patient perspective regarding access to data system information do exist and were highlighted both in the Design Thinking process and in the literature. Confidentiality and security are cited as key issues^28,33. Additionally, issues regarding equity of access to such information has been raised in the literature, with uptake of registration for access to similar health data systems being higher among those of higher education and non-minority ethnicity^32,34.

The key role of patient participation in all elements of the design process for the ESKD data system was highlighted at the summit. This aligns with the key role of patient and public involvement (PPI) in research. Ensuring that development of the ESKD data system understands and appreciates facilitators and barriers pertaining to patients and members of the public and is a core aspect of the Health Research Board’s (HRB) strategy for 2021–2025^35,36. Public/patient involvement in steering groups is often a feature of efforts to integrate PPI³⁷, and while such parties were involved the Design Thinking process, the agreement was that tangible action was required to ensure PPI was integrated in all aspects of the development and implementation of the ESKD data system. Consequently, ensuring ongoing integration of PPI in this process is a key focus of one of the working groups established at the summit.

The needs of clinicians

Clinicians viewed access to accurate health information as a high priority, as was the need for the ESKD data system to utilise standardised formats and generate standardised metrics. Furthermore, it was highlighted that integration with existing systems was key in avoiding increased administrative burden and to improve usability

Health data systems’ integration with existing systems has been frequently studied in the literature and noted to be both a strength but also a barrier to their development/implementation^8,38. Successful integration of such data systems is associated with ease of access to a patient’s health information for clinicians, reduced healthcare costs and reduced administrative time^8,39. Furthermore, this effect is particularly pronounced for patients who may attend multiple centres (as may frequently be the case for ESKD patients) using the same data system, reducing duplication/overuse of medical testing and resources⁴⁰. However, integration with existing systems has been cited as a barrier to implementation also⁸. Failure of a new health data system to integrate efficiently with existing systems reduces usability for clinicians via increased number of logins, difficulties with permissions/access to different levels of clinician and overall disruption to workflow^41,42. Consequently, integration can be viewed as both a potential facilitator and barrier to implementation of health a data system.

Integration would need to be balanced with the need for standardisation across multiple sites. Currently, all hospitals offering dialysis utilise KDCPMS and it is hoped that such a system may offer a launchpad/stepping stone to developing the data system¹⁴. However, beyond KDCPMS, Irish hospitals utilise a range of different data systems, which limits linkage across sites and has been highlighted in the literature as being a particular challenge to instigating such data systems in an Irish context⁴³. Such standardisation and integration concerns echo the needs expressed by healthcare planners and are consequently a focus of the technical working group established at the summit.

The needs of the healthcare planner

Concerns regarding technical aspects, governance and data quality of the ESKD data system were key focuses of all parties. For the healthcare planner particularly, successful implementation of these aspects of the data system would result in data of sufficient quality to guide resource allocation and policy development. Specifically, Key Performance Indicators (KPIs) were highlighted as being of particular importance, especially in monitoring patients’ interactions with different healthcare providers (including allied healthcare professionals). The use of KPIs in this area, has been highlighted as being a driver of improvement in the quality and level of allied healthcare provision⁴⁴, however, careful selection and design of KPIs will be required to ensure they are operable and generate sufficiently meaningful/useful data to inform healthcare planning and resource allocation⁴⁵.

The Design Thinking process highlighted the need for the collection of good-quality data to inform national comparisons for service planning. KPIs, coupled with standard quality indicators could permit the generation of meaningful comparisons across sites. Furthermore, such data could provide geographic mapping of current ESKD services, providing key information on both the demographical distribution of ESKD across Ireland as well as the availability and provision of ESKD services across different areas. Such geographical data systems have been highlighted in the literature as being particularly important in an ESKD context, given the need to plan complex dialysis and transplant services⁴⁶.

The needs of researchers

Researchers highlighted the need for high quality data as well as the availability of health data for the purpose of research. Health data system/registry data have long been used by researchers, and these concerns regarding data quality and access have been described from the outset of such systems⁴⁷. Such a data system provides an opportunity for researchers to access large volumes of data which is often prospectively collected. This has the potential to reduce researcher workload and expense whilst potentially increasing sample size and geographical spread⁴⁸. However, this distance from the researcher at the point of data collection provides barriers. Such data systems rarely incorporate a researcher’s specific scientific question into their design and may lack sufficient data to answer said question^48,49. Furthermore, this separation between researcher and primary data collection, generates potential issues with the quality, with information bias and a lack of collection of confounding variables being of particular concern to researchers^48,50. Therefore, broad considerations regarding data quality, standardisation of data collections and where possible, collection of common confounding variables are issues to consider in the development of the ESKD data system.

Ensuring that researchers will have access to the ESKD data system’s data was also raised as a key issue. This echoes the needs for clear governance structures expressed by all stakeholders. Ensuring that structures are in place to facilitate access to data for research in as seamless and timely a manner as possible whilst also ensuring data security and compliance with both legislation and guiding frameworks will be an ongoing priority of the ESKD data system’s development. Consequently, technical and governance aspects of the data system was identified as another key concern of the working groups at the summit.

Technical and governance considerations

All the above needs are predicated on a data system that is technically sound, operates with the appropriate governance structures in place and provides high-quality and accurate information.

Stakeholders identified the importance of technical considerations and highlighted the need for such concerns to be integrated into all stages of planning. Such considerations for health data systems are a frequent focus in the literature and are often cited as potential barriers to successful implementation of a data system. Lack of standards across sites, poor interface design and lack of integration with existing systems are particularly highlighted in a systematic review by Tummers et al.⁵¹. The successful implementation of such a data system in Ireland, may be complicated by the current landscape, whereby there is a current lack of electronic health records and patient reported data outside KDCPMS posing a challenge to integration with existing systems and standardisation across sites⁴³.

Governance considerations were also key issues raised, with the need for such a data system to be compliant with national policies and legislation being highlighted. Ensuring that the data system aligns with the Health Support System framework (a key aspect of the HSE’s national service plan) of improving patient care, generating service metrics, improving service planning and generating new research will be a key overarching focus of the data system⁵². However, robust information governance needs to be interwoven at all stages of development to ensure that data is collected, stored, analysed and presented in a way that is both compliant with legislation/policy and cognisant of the sensitive nature of the information⁵³. Consequently, a working group with a focus on governance of the ESKD data system was established at the summit.

Enhancing user-centeredness

In using the Design Thinking process, the workshops endeavoured to emphasise understanding of the end-user’s lived experiences, thereby ensuring that the solutions generated are grounded in actual patient and clinician needs⁵⁴. By starting with empathy and iterative feedback, design thinking can facilitate a system that patients find empowering, and clinicians find practical^26,55. Ultimately, this fed into the development of the working groups borne from the multi-stakeholder summit, namely, on integrating PPI into the design process.

Encouraging cross-disciplinary collaboration

A diverse group of stakeholders were involved in both the Design Thinking workshops and multi-stakeholder summit. The collaborative and inclusive nature of design thinking fosters meaningful engagement among diverse stakeholders—clinicians, patients, researchers, healthcare planners, and technical experts. This collective sense-making ensures the resulting data system reflects the multifaceted reality of ESKD care^26,56. Such interdisciplinary collaboration can lead to more holistic insights and help reconcile differing priorities and perspectives.

Increasing stakeholder buy-in and ownership

By involving stakeholders from the outset, the design process aimed to build trust, transparency, and shared ownership of the final system. This is particularly important for the ESKDDS, where there is significant dependency on the buy-in from the clinical community routinely entering data and the network of system administrators managing the systems at a local level. When participants see their contributions reflected in the outcome, they are more likely to advocate for and sustain the system’s use over time. This sense of co-production can be crucial for long-term system maintenance, policy support, and scalability^55,57.

Facilitating deeper understanding of complex systems

Healthcare data systems are inherently complex, bridging clinical practice, technical infrastructure, and policy environments. Design thinking encourages holistic problem exploration and reframes challenges in ways that illuminate underlying systemic issues. This results in more informed decision-making and can yield a data system that is sensitive to real-world constraints, ultimately leading to more effective, data-driven quality improvement initiatives^25,56.

However, despite the strengths of the approaches adopted it is also necessary to acknowledge the limitations of this approach;

Limited representation and sample bias

A fundamental concern is the risk that the participants involved in the workshops—regardless of whether they are clinicians, patients, or planners—may not be fully representative of the broader stakeholder population. Design thinking sessions often rely on convenience sampling and the self-selection of participants who are interested and available to attend. Consequently, the insights generated may overemphasise the views of more engaged or vocal stakeholders while under-representing less empowered or marginalised groups. This can skew the solutions and lead to a data system that does not comprehensively cater to the needs of all end-users^57,58. Notably, certain key groups while present, were likely underrepresented in the workshops, namely: patients, nurses involved in the care of those with ESKD and technical staff.

Lack of generalisability and rigour

The workshop’s use of Design Thinking does pose issues regarding the generalisability of the findings beyond the individuals attending it. Design thinking, by its nature, is context-specific and iterative. Although it can yield rich qualitative insights and generate innovative ideas, it does not inherently guarantee that these ideas will be transferable beyond the specific setting or group of participants. The process tends to focus on generating localised solutions rather than systematically testing hypotheses or validating findings across multiple contexts. There will be a need for parallel processes as other chronic diseases develop data systems under the Chronic Care Model.

Potential domination by certain voices

While design thinking aims to level the playing field, in practice, power dynamics may still influence the dialogue. Clinicians or researchers with higher professional status may unintentionally dominate conversations, steering discussions and overshadowing patient perspectives. This risks limiting the depth of patient engagement and detracts from the supposed equity that design thinking seeks to create⁵⁹. Moreover, differing communication styles, confidence levels, and familiarity with the design thinking process can result in uneven contributions, diluting the richness and balance of insights.