International multi-stakeholder collaboration to support implementation of cancer care efficiency metrics: A qualitative study to develop the All. Can Action Guide

International multi-stakeholder collaboration to support implementation of cancer care efficiency metrics: A qualitative study to develop the All. 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Can Action Guide Ana Sofia V. Carvalho, Óscar Brito Fernandes, Damir Ivanković, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6429529/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background : Cancer care efficiency contributes to overall healthcare systems performance. However, many healthcare systems experience challenges in measuring it effectively. All.Can, a multi-stakeholder organisation working to improve cancer care efficiency, has identified eight cancer metrics as a starting point for standardising efficiency measurement, focusing on timeliness of care, coordination of care, and patient-centeredness. This study aims to identify barriers and enablers to implementing these metrics globally and to describe the co-development of a guide to support stakeholders in embedding these metrics into healthcare workflows. Methods : This qualitative study used a co-development approach in collaboration with the All.Can community. Semi-structured interviews were conducted to identify barriers, enablers and good practices in implementing cancer care efficiency metrics. Data were analysed using a combination of deductive and inductive coding, guided in part by the Implementation in Context (ICON) framework. A qualitative content analysis was conducted to explore the perceived actionability of contextual factors, which informed the development of an Action Guide grounded in health systems research principles. The guide was reviewed by potential end-users and launchedin September 2024. Results : Forty informants from 21 countries have participated in semi-structured interviews. Regulatory influences were most frequently cited as relevant factors for implementing timeliness-of-care metrics. Barriers included fragmented or missing regulations on cancer data collection and limited database interoperability, while enablers involved national strategies and standardised care pathways. For coordination-of-care metrics, regulatory issues were again central, notably the lack of regulation defining roles such as oncology nurses and care coordinators. Political influences emerged prominently for patient-reported metrics, including lack of funding and absence of systematic data collection strategies. Advocacy was often seen as a key enabler. These informed the development of an Action Guide, intended to support the implementation of cancer care metrics. Conclusions : This study identified contextual barriers and enablers for implementing cancer efficiency metrics and described the co-development of the All.Can Action Guide as a practical tool for policymakers, care providers and advocates. Through mapping priority areas for action, this study may strengthen data-driven decision-making, enhance timeliness and coordination of care, and ultimately improve patient outcomes and experiences worldwide. Cancer Efficiency Implementation Cancer policy Cancer care coordination Health Care Quality Access and Evaluation [MeSH] Quality of Health Care [MeSH] Barriers Enablers Quality Indicators Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Cancer is a leading cause of mortality and morbidity globally (1), with far-reaching societal implications (2). Cancer prevalence has been rising in the past years and is expected to continue increasing (2; 3), due to factors such as longer life expectancy (4) and more effective treatments. Thus, per capita health expenditure on cancer care is expected to increase by 67% across Organisation for Economic Co-operation and Development (OECD) countries between 2030 and 2050 (2). Workforce shortages pose a key challenge to the delivery of timely, effective and equitable care (3). Furthermore, cancer is an extremely heterogenous disease, with a wide range of treatment options and care pathways (5), emphasizing the importance of multidisciplinary care. These factors highlight the need for an efficient use of resources to ensure the sustained quality of cancer care, ultimately improving care experiences and outcomes for people with a history of cancer. Efficiency is considered a cross-cutting dimension of health system performance, being key to health systems’ adaptation to the growing healthcare demands within limited resources (6). While some efforts to measure efficiency in cancer care internationally have been made previously (7), the lack of systematic and standardised measurement across countries hinders international benchmarking and efforts to improve efficiency (3). International collaboration is essential for developing solutions to address this issue. All.Can International (All.Can) is a not-for-profit, global multi-stakeholder organisation, working to improve the efficiency of cancer care. It operates through ten individual and 34 organisational members, as well as National All.Can teams, known as ‘National Initiatives’, across 21 countries. These include 12 countries in Europe, two in North America, two in South America, four in Asia and one in Oceania. All.Can is a unique example of an organisation dedicated to improving cancer care efficiency through multi-stakeholder cooperation. In collaboration with the University of Southampton, All.Can has previously identified a set of eight cancer efficiency metrics as a foundational starting point for standardising measurement across global cancer care pathways (8). These metrics focus on measurement of three core dimensions of efficiency: timeliness of care, coordination of care, and patient-centeredness. However, knowing 'what' to measure is only the first step; embedding these metrics across health systems to inform decision-making remains a significant challenge. A critical question is 'how' to effectively implement these metrics, particularly through a cascading approach from clinical setting to managerial and policy-level decisions. Actionable guidance is needed to support implementation, with a focus on understanding both the enabling and hindering conditions from a system perspective. Furthermore, the variety of actors and their roles in cancer care and policy across health system levels, alongside the variety of governance models across countries, demands an engaged, multi-profile, multi-level and collaborative international approach. This study aims to identify barriers and enablers to implementing cancer efficiency metrics globally, at national and organisational levels, as perceived by multi-level stakeholders. To achieve this, the study describes the co-development of an actionable international implementation guide — the All.Can ‘Action Guide for Efficient Cancer Care’. Designed for policy-makers, patient advocates, hospital managers, and healthcare professionals, the Guide is organised around three clusters of efficiency metrics (timeliness of care, coordination of care, and patient-centeredness) and aims to support these actors address real-world challenges and facilitators. With a focus on actionability, the Guide provides structured guidance and evidence-based recommendations to support stakeholders in embedding these metrics into routine practice. Methods Study design We conducted an exploratory qualitative design (9). The study comprised two phases of data collection through semi-structured interviews: the first phase aimed to identify barriers, enablers and good practices for the use of cancer metrics at national and regional levels, while the second phase intended to characterise the implementation of good practices (Figure 1). Drawing on this data and applying a health systems research theory-based approach (10), we have outlined the structure of the Action Guide. The first iteration of the Action Guide was evaluated by potential end-users. During the design, development and validation phases, the research team engaged regularly with the All.Can community, employing a co-development approach to create an actionable implementation guide. The research team included five experts in health systems performance measurement and management and a doctoral student in the same field. EP is CEO of All.Can International (Additional file 1 includes the detailed team composition). Reporting complies with the consolidated criteria for reporting qualitative studies (COREQ) (11) (Additional file 2). Data collection Target informants were national experts from All.Can from the three decision-making levels of healthcare systems - clinical, organisational and policy levels. All.Can comprises 34 organisational and ten individual members across the world, who promote its mission and work. Additionally, All.Can is active in 21 countries through National Initiatives that tailor its goals to local contexts. Representatives of all National Initiatives and one individual member were invited to participate in semi-structured interviews, by email. The background, aim and interview questions were sent in advance of each interview. The interview guide was structured in three sections, corresponding to the three metric clusters (Additional file 3). Based on their perception and knowledge, informants were also asked to provide examples of good practices from their country and identify potential informants. These interviews were conducted over a four-month period (July-October 2023) in pairs by the research team (DI, OBF, EB, ASVC, DK), for a duration of one hour, in English, via Microsoft Teams (version 25007.607.3371.8436). Interviews were recorded and transcribed verbatim with the agreement of the informants. Requests to reply in writing were accommodated. Field notes were prepared after the interviews by one interviewer and reviewed by the second. Five case studies were selected for in-depth characterisation, considering their potential for implementation in different contexts, scalability, and how evenly they were distributed across the metric clusters. The language, platform, duration, research team, recording and transcription processes were the same as in the first phase. Data analysis A qualitative content analysis (12) was conducted to characterise the magnitude of importance of specific attributes of context, as perceived by participants (Figure 2). This method was chosen to allow for some interpretation regarding the actionability of stakeholders’ implementation efforts. The ICON framework (13) informed the deductive coding to identify and structure the full spectrum of perceived contextual barriers and enablers. This framework outlines domains of determinants that are considered to influence implementation outcomes, acting as barriers and enablers, focusing particularly on the identification of features of context. Data analysis was conducted with Microsoft Excel. The data analysis followed a structured approach combining inductive and deductive coding, guided by the ICON framework. First, open inductive coding was conducted to extract barriers and enablers from the transcripts. These were added into pre-structured spreadsheets — one for each metric cluster (Additional file 4)—representing the decontextualisation phase. Next, the original transcripts were reviewed again by ASVC to ensure completeness and accuracy of the extracted content ( recontextualisation ). In the following step, similar barriers and enablers were grouped into inductive categories ( first step of categorisation ). These categories were then deductively matched to the external-level attributes of the ICON framework ( second step of categorisation ), enabling a theory-informed structuring of the data. For example, a quote such as “political momentum to focus on health data” was first coded inductively as “political will” and subsequently linked deductively to the ICON attribute “political influences”. Finally, we quantified the number of barriers and enablers assigned to each ICON attribute to assess their relative prominence ( first step of compilation ). Given that not all informants commented on every issue, we did not apply further ranking or weighting to the attributes (12). To enhance the actionability of the findings for international stakeholders at different health system levels, themes and sub-themes of action were identified, considered as ‘preconditions for implementation’ ( second step of compilation ). These themes were identified by the lead researcher (ASVC) from the interview notes and team debriefs, and underwent slight changes after revision by the research team, often related to clarity of wording. To each theme/sub-theme, actionable recommendations were developed. Coding was conducted by one researcher (ASVC, OBF, DI or EB) and reviewed by another, throughout. Inclusive development and validation process of the Action Guide The Action Guide was created anticipating the implementation of metrics per cluster in different countries, at national and organisational level. To increase the actionability of the Guide for various users and uses, it was agreed to provide step-by-step guidance in a non-linear document, which offers the possibility to navigate the Guide with no predetermined order, according to each user’s needs and with links to additional resources. As such, different entry points to the Guide were considered, inter-linked with clickable links to allow users to navigate from one to another to find useful resources for their needs. To do so, we made an inventory of theoretical frameworks of implementation science and we considered a classical framework of health systems research, developed by John Øvretveit (10), as an actionable way of organising our data. This framework considers three questions to assess ‘why’, ‘what’ and ‘how’ to evaluate in the context of health systems research. To evaluate the Guide’s actionability , five of the informants from the second phase of data collection were purposefully selected and invited for three semi-structured interviews. These experts were potential end-users not directly involved in the development of the Guide, and experienced in implementing an innovative practice in their context. Interviews explored the usefulness, clarity and completeness of the Guide. The preliminary version of the Guide, the aims and interview questions were sent in advance of each interview (Additional File 5). The Action Guide was developed with various moments of consultation over time with the All.Can community (Figure 1). Participants in stakeholder consultation included potential end-users, such as patient representatives, oncology healthcare professionals, academics, national health agency officials and industry representatives. This development process allowed to finetune the data analysis, to validate the results, and to receive feedback on successive drafts of the Guide. The Action Guide was launched in September 2024, where plans for international use and potential pilot projects were discussed. The results of this study are presented by addressing both aims of the study together, per cluster of efficiency metrics: timeliness of care, coordination of care and patient-centeredness. For each cluster, we first present an overview of the quantification of individual barriers and enablers to the implementation of metrics by visually showcasing their distribution across the ICON attributes. Categories of barriers and enablers are then detailed in-text. Subsequently, the themes and sub-themes of preconditions for implementation are presented in one table per cluster, together with illustrative quotes from the interviews. Results Characteristics of informants A total of 31 informants from 21 countries participated in the first phase of data collection (Additional file 6). From the 22 invitations sent, 18 semi-structured interviews were conducted and three participants opted for written responses. Representatives from one country have declined to participate, due to insufficient knowledge on the subject. Several interviews included multiple informants, with six interviews involving two participants and two involving three. The informants represented diverse professional backgrounds, including oncology healthcare professionals, patient representatives, researchers, national health agency officials, and industry representatives. Given that some informants held multiple affiliations, they provided insights from different levels of the health system (Additional File 6 provides a detailed breakdown). In the second phase, nine informants contributed with insights on five selected good practice case studies. These discussions focused on implementation processes, encountered challenges, and strategies that facilitated success. The following sub-sections present the findings organised per cluster of metrics. Case studies were considered an essential component to enhance the Action Guide’s actionability to support end-users, by providing in-depth descriptions of phenomena in real-life contexts (14). Data from these case studies can be found in Additional file 7. Barriers, enablers and guidance to implement timeliness-of-care metrics Regulatory influences were identified as being the most prominent attribute of barriers and enablers regarding timeliness-of-care metrics: a total of 50 (63%) barriers and enablers related to these metrics were mentioned as pertaining to regulatory aspects of implementation, followed by 16 (20%) concerning political influences, 13 (16%) related to intercommunity / interorganizational / intersectoral relationships and 1 (1%) related to community influences. (Figure 3) (Additional file 8 presents the breakdown of barriers and enablers mapped to the ICON framework). With respect to regulatory influences, perceived barriers were related to the lack of a national approach regarding cancer data and different regulations supporting data collection between regions, provinces or territories. Various aspects related to the maturity of data ecosystems were perceived as barriers, such as the absence or underdevelopment of electronic health records, the lack of interoperability of databases, and lack of a nation-wide unique patient. Data collection not being available for monitoring purposes at National level was another perceived barrier. Enablers included the implementation and update of national strategic planning documents, the regulation of standardised care pathways, and legislation supporting cancer data collection, namely the centralization of data collection. Regarding political influences, the lack of political will and the time investment required to develop cancer registries were perceived as barriers, while collaboration at decision- making and external political pressure were considered enablers. The themes of preconditions for implementation of timeliness-of-care metrics identified were: ‘legal frameworks and strategy, policy context and funding’, ‘data governance’, and ‘data use and performance monitoring’ (Table 1) (Additional file 9 presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme). Table 1 – Themes and sub-themes of preconditions for implementation of timeliness-of-care metrics TIMELINESS-OF-CARE METRICS Themes of preconditions for implementation Sub-themes Illustrative quotes Legal frameworks and strategy, policy context, funding National cancer control plan, its development and regular update “[this organization is mandated by the federal government] So they're the ones who hold the national cancers but create and encourage the implementation of the National Cancer strategy, for example. And they've also just released a National Cancer data strategy. So [they] work a lot with the cancer agencies directly to encourage alignment with that national strategy.” (Canada) National health data ecosystem, including a national approach to cancer data collection and funding to develop the health data infrastructure “By legislation, pathology services have to give that information to the cancer registries and any patient receiving radiation oncology that again is legislated. That information has to be given to the cancer registry data. It's fairly good. And as I say, it's being enhanced at the moment by a number of federally funded projects to increase the information on recurrence and metastasis as well, which will be excellent” (Australia) Data governance Interoperability among databases, considering promoting the maturity of electronic health records and the implementation of patient unique identifiers “There is the “pension number”, but healthcare is not allowed to use it for data linkages.”; “Each hospital has a different system, but it is almost impossible to link them” (Australia) Data use and performance monitoring Mechanisms of feedback and learning, including investing in the availability of near real-time performance data, notably focusing on inequalities in access and quality of cancer care “Treatment data is collected only at hospital-level (related to diagnosis and treatment) and is only available and used for reimbursement purposes, then only available to the health insurers and is not accessible for measurement efforts” (Sweden) Barriers, enablers and guidance to implement coordination-of-care metrics Regulatory influences were identified as being the most prominent attribute of barriers and enablers for implementation of coordination-of-care metrics: a total of 39 (75%) barriers and enablers mentioned were in relation to these aspects of implementation, followed by less than ten barriers and enablers in relation to each of the others attributes of context (Figure 4). (Additional file 8 presents the breakdown of barriers and enablers mapped to the ICON framework). Concerning regulatory influences, the absence of regulations defining the roles of multidisciplinary teams, oncology nurses and care coordinators, and defining the centralisation of cancer care in specialised centres were referred as challenges to implementation, together with the lack of regulation pertaining to task shifting and task sharing. With respect to political influences, workforce shortages and the lack of national of prioritisation of cancer nurses regulation were mentioned as barriers, while political will was perceived as enabler. In relation to community influences, the existence of active National Associations of Oncology Nurses and the providence of care coordinators by Non-Governmental Organisations and patient advocacy groups were perceived as enablers. The following preconditions themes for implementation of coordination-of-care metrics were identified in relation to the perceived barriers and enablers: ‘workforce capacity’, ‘oncology nurses and cancer patient navigators’, ‘task sharing and substitution’, ‘multidisciplinary tumour boards’, and ‘comprehensive cancer centres’. (Table 2) (Additional file 9 presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme). Table 2 - Themes and sub-themes of preconditions for implementation of coordination-of-care metrics COORDINATION-OF-CARE METRICS Themes of preconditions for implementation Sub-themes Illustrative quotes Workforce capacity Monitoring and addressing workforce shortages in the cancer care ecosystem, ensuring it remains a national priority “But in there is health and human resources, right? I mean, I think us like everybody else's experiencing a lot of crises and people leaving because of burnout from the pandemic and from the fact that working is already difficult because of the fragmentation, lack of information […] There's more focus [and investment] is being put through […] the human resource piece. […]So there are priorities that have been named, that are being shared federally, provincially and territorially that relate to Health Human resources” (Canada) Oncology nurses and cancer patient navigators Regulation of the professional role of oncology nurses and cancer care navigators across the care pathway, ensuring similar mandates at subnational levels “both the General Nursing Council and Patient Organisations urge the institutionalization of the role of nurse case managers at all levels of care to address the cancer patient process in a comprehensive manner, with the aim of increasing the quality of care (…) and minimising the time between procedures. (…) This figure of case manager in the oncology field is being included (…) in pioneering hospitals” (Spain) Task sharing and substitution Regulation concerning task sharing and substitution, ensuring harmonisation at subnational levels “[task shifting] It does [happen], yes. again it's very variable. you know, [our country] has probably got a stronger doctor input into most areas of care than many countries.” (Australia) Multidisciplinary tumour boards Regulation of multidisciplinary tumour boards to ensure meeting quality standards, ensuring harmonisation at subnational levels “Multidisciplinary teams are not legally mandated nor regulated. [they] exist in most of the private sector, however this is not the case in the public sector. The patients have to move between hospitals to do different treatments […]. Hospitals are connected in a way, to send patients for specific treatments from one hospital to another. But there is no “team”. Also, teams have no psychologists or dieticians, for instance.” (Greece) Comprehensive cancer centres Centralisation of cancer care in specialised centres and monitoring patient access to ensure equal access to specialised care “In fact, tumour boards are in the legislation for more 20 years but is it not obliged. Some private oncology hospitals organise their own tumour boards. […] [Our country has] around 400 sites where patients are treated. You can imagine how difficult it is: oncologists are in small hospitals and they have to decide […]. We do not have a centralised approach […]” (Australia) Barriers, enablers and guidance to implement patient-centeredness metrics Political influences were predominantly reported as influencing the implementation of patient-reported-metrics: a total of 21 (46%) barriers and enablers were mentioned as being in relation to political aspects of implementation, followed by 10 (22%) barriers and enablers mentioned as related to community influences and the same number related to regulatory influences (Figure 5). (Additional file 8 presents the breakdown of individual barriers and enablers mapped to the ICON framework). Regarding political influences, insufficient political will, funding and the absence of a national approach to systematic data collection were identified as a barriers. With respect to community influences, low levels of health literacy and societal advocacy groups with no connection to the health care system were perceived as barriers. Advocacy efforts by patient groups, NGOs and organizations’ will to include patient perspectives were perceived as enablers. With respect to regulatory influences, the lack of embedding of these metrics in existing cancer registries or databases and lack of enforcement and feedback mechanisms were perceived as barriers. The use of standardised tools was perceived as an enabler. Linking up the use of metrics to other functions and scaling up successfully run pilot projects were considered enablers for implementation related to interorganisational relationships. Perceived barriers and enablers were identified in relation to the following preconditions: ‘legal frameworks and strategy, policy context and funding’ and ‘data governance, use, and reporting’. (Table 3) (Additional file 9 presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme). Table 3 - Themes and sub-themes of preconditions for implementation of patient-centeredness metrics PATIENT-CENTEREDNESS METRICS Themes of preconditions for implementation Sub-themes Illustrative quotes Legal frameworks and strategy, policy context, funding to patient-reported data collection Political will and funding “I think within the [health system] there is also the aim to try and put patient experience on an equal footing for clinical and quality outputs and safety, and so there's a real drive (…). So kind of developing national systematic ways of collecting data, allowing comparisons and driving improvement[…]” (Case study England’s National Cancer Patient Experience Survey) National approach “The cancer plan speaks very strongly about the need to collect patient reported outcomes and experience measures, but they're not collected systematically anywhere.” (Australia) Use of standardised tools “ […] there was no instrument in [this country] for PREMs in cancer care. […]This is why we looked into what was done in other countries. I think that the main thing here was there was a gap in the standardised instrument […] to inform policies” (Case study Swiss Cancer Patient Experiences) Involvement of patient groups and non-governmental organisations “I think [our team] really understands the importance of involving the patient in key decisions about the survey. […] like the questions we should ask, how should we contact people, what the materials look like? […] I think that's really important […] that the patient should be involved at every step.” […] “I think another key enabler is the advisory group and the cancer charities that we have on the advisory group […]. I think it adds to the legitimacy of the survey. If you've got large cancer charities that are clearly supportive of the survey […], I think it gives patients more confidence in the survey and the importance of taking part. So when we come on to some of the challenges, the cancer charities have been really huge big advocates for the survey. […] having the cancer charities there that have got a really strong voice and a really kind of political power in this space, it's been really, really helpful” (Case study England’s National Cancer Patient Experience Survey) Data governance, use, and reporting Embedding of patient-reported metrics in cancer registries or databases “As external researchers, we do not have access to patient data. […]and there's no registry of all the patients that go through […]care. […]. So, really, access to patient information is the key barrier here. […] Therefore, there are two main issues, identification of disease patients and identification of confirmed diagnosis. These are the two main challenges in these kind of [patient-reported measures] surveys.” (Case study Swiss Cancer Patient Experiences) Enforcement and feedback mechanisms “the patient experience surveys […]are developed […] to provide that national monitoring of progress against policy regulation[…]. But also key is that we're able to give the [organisations] who participate in the survey information to allow them to carry out quality improvement.” […] “And you see data from these national surveys feature heavily in the Care Quality Commission, who are our regulator and inspector for Health and Social Care. And when they go and inspect organizations, they're looking at data from patient experience surveys […], so that they can make judgments on how organizations are performing.” (Case study England’s National Cancer Patient Experience Survey) Structure of the Action Guide The Action Guide was developed with three entry points: ‘Why’ – addressing the relevance of efficiency in cancer care, ‘What’ – characterising the three metrics clusters and related health system components, and ‘How’ – a roadmap to implementation (Figure 6). The ‘How’ section includes five steps: 1) it guides users to define context-specific priorities, drawing on the literature on cancer care efficiency; 2) it provides a preparedness checklist for metrics implementation, elaborated based on the categories of barriers and enablers identified; 3) it presents key contextual factors, based on the magnitude of relevance attributed to each ICON attribute at system level and detailing specific categories of barriers and enablers; 4) the Guide lists potential key actors to be involved in implementation efforts, compiled from the stakeholders mentioned in the interviews; 5) it provides key recommendations for metrics implementation per cluster, which are action points derived from the themes of preconditions identified. The good practices case studies are characterised at the end of the Guide and referred in each related cluster with hyperlinks. Related literature resources are provided throughout the Guide. Launch of the Action Guide and dissemination activities The launch of the Action Guide took place at an in-person meeting with the All.Can community in September 2024, in Geneva. The general public could attend virtually and interact via the chat and live polls. A summary of the Guide’s structure and guidance were presented in a plenary session, followed by a panel discussion. Live polls during this event showed the relevance, high level of interest and the intention to implement the Guide’s recommendations by this community. The Guide is available at All.Can International’s website (link). Following the launch event, various dissemination activities were carried out, enhancing the visibility of the Guide to a broader community (e.g. a conference abstract showcasing preliminary results was presented at the European Cancer Organisation’s Summit in November 2024 (15). Discussion Cancer poses a significant challenge to health systems and to society as a whole. At health system level, current efforts emphasize measuring inputs and outcomes of cancer care, while lacking a systematic approach to measure the efficiency of cancer care (16; 3). However, international patient-reported data indicate that waiting times, poor care coordination and insufficient patient-centred care are critical concerns for individuals with chronic conditions (17). Employing a qualitative content analysis, this study mapped barriers and enablers to implementing cancer care efficiency metrics across health systems from the perspective of international multi-level stakeholders from 21 countries. Barriers and enablers were mapped to the attributes of the context from the Implementation in Context (ICON) Framework, per cluster of cancer care efficiency metrics: timeliness of care, coordination of care, and patient-centeredness. Furthermore, this study described the development of an Action Guide to support implementation of cancer efficiency metrics globally through a participatory process, identifying actionable themes with recommendations for action for multi-level stakeholders, underscoring the strong role of political, regulatory and advocacy factors at system level. Addressing barriers related to the regulation of standardised care pathways measuring timeliness targets and maturity of data ecosystems, while leveraging enablers such as the regulation of oncology nurses specialists, care navigators, and a standardised approach to patient-reported data collection, can foster the efficiency of cancer care globally. In relation to the timeliness-of-care metrics, regulatory aspects considered relevant to implementation were related to the development and regular update of national cancer control plans. Cancer plans contribute to prioritise cancer-specific actions at the health system level and are considered foundational to foster cancer control (18). The 2019 WHO global survey (19) showed that, despite 92% of the 177 responding countries having cancer plans or strategies, 80% were operational, showing room for improvement. As our study showed, international collaboration may foster cross-country learning and exchange to define key priorities and advance cancer plans. Furthermore, our findings underscore the importance of developing national health data ecosystems, notably fostering the maturity of electronic health records and interoperability of databases to support the implementation of time-related cancer metrics. These insights also align with global momentum around digital health transformation, highlighting the need to invest in interoperable health information systems that can support real-time monitoring and data-driven cancer care improvements. This is corroborated in a recent OECD report CITATION OEC25 \l 2070 (16) showing that most EU countries struggle with effectively monitoring waiting times in the cancer care pathway. Our study further signals that the regulation of standardised care pathways, particularly including time targets, may prove a relevant enabler to foster timeliness of care. Previous studies have showed the potential for standardised cancer care pathways in improving cancer outcomes CITATION Rot12 \l 2070 \m van20 (20; 21) . Regarding the coordination-of-care metrics, a strong emphasis on regulatory influences was also noticeable to strengthen the measurement and improve care coordination. Specifically, the regulation of advanced roles for nurses, care navigators, multidisciplinary teams, alongside concentrating cancer care. Previous research has underscored the potential to oncology nurses to deliver more integrated care (22) (23) and European countries have recently been implementing additional roles for nurses to tackle increased health needs and oncologists shortages (24). A previous OECD report also underscored the role of legislation and regulation to remove barriers hindering the implementation of new advance practice nurses' roles (25). Furthermore, cancer care often requires two or more professionals to perform a task at any stage of the pathway (26), therefore professionals’ cooperation is paramount. In line with our findings, worldwide cancer associations have been pushing for standardised formats for MDT meetings to foster coordination and shared-decision making (27). Additionally, concentrating cancer care is currently a priority in many countries and various initiatives have been leveraging national efforts to foster their implementation across Europe (16). With respect to the implementation of patient-reported metrics, political will, funding and a national approach to systematic data collection were perceived as having a stronger role to implementation. While most countries lack the implementation of national and standardised methods to collect patient-reported data (16), political momentum is growing internationally to increase efforts for collecting patient-reported-data to monitor and improve care (17). A systematic review addressing determinants to implement PROMs/PREMs has also identified the need to integrate them into existing workflow routines to ensure their use, to engage with health system’s leaders, and to involve all relevant stakeholders (28). Furthermore, our results signal the key role of advocacy efforts and the involvement of patient groups in the implementation of standardised approaches to patient-reported data collection. In addition, the absence of systematic data collection and uneven implementation of standardised metrics may exacerbate health disparities, particularly for underserved populations. Equity considerations should therefore underpin efforts to implement cancer care efficiency metrics, ensuring that improvements in timeliness, coordination, and patient-centeredness benefit all population groups equitably. Strengths and limitations The international and participatory nature of this project, including multi-level stakeholders, allowed to account for various perspectives, which enabled to enrich and validate the research findings. Additionally, it fostered a sense of ownership, thereby contributing to a more successful adoption of the Guide’s recommendations. The implementation theory-based approach ensured a systematic and comprehensive mapping of factors influencing implementation of cancer efficiency metrics, while the quantification of the attributes of the ICON framework allowed to signal key areas to prioritise. Balancing the framework-informed method with an open-inductive coding to identify themes of preconditions enabled us to capture actionable points to which stakeholders may relate to drive change. This Guide was developed with input from only one international cancer community and the barriers and enablers reported are based on the perception and knowledge of the participants. Nonetheless, in the validation phase we received feedback from potential end-users not directly involved in the development process, which has contributed to improve the generalisability of the findings. While the research team maintained a facilitative role in the co-development process, we recognise that our background in health systems research and our collaboration with All.Can may have influenced how certain issues were framed. Implications for practice and policy By employing an inclusive development approach and applying a theoretical implementation science approach, this study offers practical insights into how global exchange and collaboration can promote cross-country learning for the effective uptake of cancer efficiency metrics. The interaction between academic and practical approaches led to the refinement of both the content and format of our findings. For instance, during discussions on the first iteration of the Guide, the All.Can community requested to modify the name initially proposed by All.Can - ‘playbook’ -, considering the sensitive nature of the issue. Thus, ‘Action Guide’ was considered a more neutral and suitable title. This process emphasises the importance of striking a balance between theory and practice to effectively incorporate end-users’ perspectives and needs into a widely accepted final product. The inclusive development process conducted in close collaboration with an international community has also showed that there is a relevant added value in having an international multi-stakeholder organisation engaging with an academic institution to develop a guiding framework for implementation. This co-development process has proven effective and has already yielded tangible results, namely the organisation of pilot projects in various All.Can member countries, showing the interest of the cancer community in the guidance and resources the Action Guide offers. The involvement of All.Can as co-authors of this work underscores the rationale behind this approach and further highlights the benefits of collaboration in ensuring the actionability and applicability of this work. As health systems face increasing pressures from rising cancer incidence and constrained resources, embedding efficiency metrics can also contribute to broader sustainability goals—ensuring that care improvements are delivered in a way that is both economically and operationally viable over time. The flexible, modular structure of the Action Guide also supports its scalability and adaptability to different health system contexts, including varying resource settings. Future research could evaluate the uptake and use of the Action Guide, exploring the extent to which the final product reached its potential. Additionally, while this research intends to provide evidence to cancer-related policy-making, some of the findings may potentially be extrapolated to other clinical areas. Notably, the challenges of monitoring timeliness of care and patient-centredness are transversal to health care delivery. Conclusion This study identifies the perceived contextual barriers and enablers for implementing cancer efficiency metrics from the perspective of informants from an international multi-stakeholder cancer community, focusing on timeliness of care, coordination of care, and patient-centeredness. Moreover, this study describes the participatory development of an Action Guide designed to enhance the actionability of these metrics globally. This research contributes to the field by identifying actionable themes that multi-level stakeholders in the cancer field can prioritise to advance the implementation of these metrics within their specific contexts. The co-development of this Action Guide, owned and disseminated by an international multi-stakeholder cancer organisation, is a step forward to foster cross-country learning and ensure that research knowledge is effectively used to inform future cancer policies globally, ultimately aiming to enhance system performance, patient experiences and outcomes. Abbreviations ASVC: Ana Sofia V. Carvalho DK: Dionne Kringos EB: Erica Barbazza EP: Eduardo Pisani NK: Niek Klazinga OECD: Organisation for Economic Co-operation and Development OBF: Óscar Brito Fernandes Declarations Ethics approval and consent to participate This study was approved by the non-WMO Committee of the Medical Ethics Review Committee of Amsterdam University Medical Centers: committee’s reference number 2023.0939. This committee is authorised by the board of directors of Amsterdam UMC and supervised by the Medical Ethics Review committee. Participants in the study provided written informed consent during the recruitment phase and expressed their consent verbally at the start of the interviews. Interview data has been anonymised and confidentiality was assured by referring to informants by country name. Consent for publication Not applicable. Availability of data and materials The datasets generated and analysed during the current study are available in the Zenodo repository, 10.5281/zenodo.15184172. Competing interests EP is the CEO of All.Can International. The other authors declare that they have no competing interests. Funding This study was funded by All.Can International. Authors' contributions ASVC, OBF, DI, EB, EP, NK and DK contributed to conceptualise the study. ASVC, OBF, DI, EB, and DK performed the data collection. ASVC performed the data analysis, which was revised by OBF, DI and EB. ASVC drafted the article. OBF, DI, EB, EP, NK and DK provided feedback and have contributed to revising the manuscript. All authors approved the final version of the manuscript. Acknowledgments The authors wish to thank the interviewees for the time and insights they provided during the interviews. The authors also wish to thank members of the broader All.Can community for their engagement in the project and for their constructive feedback. References Institute for Health Metrics and Evaluation. IHME, data tools and practices, GBD Compare 2021 [Internet]. 2025 [cited 2025 Feb 26]. Available from: https://vizhub.healthdata.org/gbd-compare/. OECD. Tackling the impact of cancer on health, the economy and society. Paris: OECD Publishing; 2024. OECD. Beating cancer inequalities in the EU: Spotlight on cancer prevention and early detection. Paris: OECD Publishing; 2024. Steel N, Bauer-Staeb CM, Ford JA, Abbafati C, Abdalla MA, Abdelkader A, et al. Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021. 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Multidisciplinary team approach in cancer care: A review of the latest advancements featured at ESMO 2021. EMJ Oncol. 2022;10(Suppl 6):2–11. Glenwright BG, Simmich J, Cottrell M, O’Leary SP, Sullivan C, Pole JD, Russell T. Facilitators and barriers to implementing electronic patient-reported outcome and experience measures in a health care setting: a systematic review. J Patient Rep Outcomes. 2023 Feb 14;7(1):13. WHO Regional Office for Europe. Taking the pulse of quality of care and patient safety in the WHO European Region: multidimensional analysis and future prospects. Copenhagen: WHO Regional Office for Europe; 2024. Licence: CC BY-NC-SA 3.0. ESMO. WHO–ESMO collaboration sets accessible cancer care, prevention and education as priority areas of intervention [Internet]. Dailyreporter.esmo.org; 2025 [cited 2025 Feb 3]. Available from: https://dailyreporter.esmo.org/news/who-esmo-collaboration-sets-accessible-cancer-care-prevention-and-education-as-priority-areas-of-intervention European Health Data Space [Internet]. European Commission; 2025. Available from: https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space_en European Health Data Space [Internet]. Health.ec.europa.eu. Available from: https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space_en McDowell BD, Klemp J, Blaes A, Cohee AA, Trentham-Dietz A, Kamaraju S, et al. The association between cancer care coordination and quality of life is stronger for breast cancer patients with lower health literacy: A Greater Plains Collaborative study. Support Care Cancer. 2020 Feb;28:887-95. Under Pressure: Safeguarding the Health of Europe's Oncology Workforce [Internet]. Europeancancer.org. Available from: https://www.europeancancer.org/resources/publications/under-pressure-safeguarding-the-health-of-europes-oncology-workforce.html Morabito A, Mercadante E, Muto P, Manzo A, Palumbo G, Sforza V, et al. Improving the quality of patient care in lung cancer: key factors for successful multidisciplinary team working. Explor Target Antitumor Ther. 2024;5(2):260. EUnetCC - The European Comprehensive Cancer Center Network [Internet]. German Cancer Society; 2025 [cited 2025 Mar 3]. Available from: https://ecc-cert.org/health-service-research/eunetccc/ Additional Declarations Competing interest reported. EP is the CEO of All.Can International. The other authors declare that they have no competing interests. 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EP is the CEO of All.Can International. The other authors declare that they have no competing interests.","formattedTitle":"\u003cp\u003eInternational multi-stakeholder collaboration to support implementation of cancer care efficiency metrics: A qualitative study to develop the All. Can Action Guide\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eCancer is a leading cause of mortality and morbidity globally (1), with far-reaching societal implications (2). Cancer prevalence has been rising in the past years and is expected to continue increasing (2; 3), due to factors such as longer life expectancy (4) and more effective treatments. Thus, per capita health expenditure on cancer care is expected to increase by 67% across Organisation for Economic Co-operation and Development (OECD) countries between 2030 and 2050 (2). Workforce shortages pose a key challenge to the delivery of timely, effective and equitable care (3). Furthermore, cancer is an extremely heterogenous disease, with a wide range of treatment options and care pathways (5), emphasizing the importance of multidisciplinary care.\u0026nbsp;These factors highlight the need for an efficient use of resources to ensure the sustained quality of cancer care,\u0026nbsp;ultimately improving care experiences and outcomes for people with a history of cancer.\u003c/p\u003e\n\u003cp\u003eEfficiency is considered a cross-cutting dimension of health system performance, being key to health systems\u0026rsquo; adaptation to the growing healthcare demands within limited resources (6). While some efforts to measure efficiency in cancer care internationally have been made previously (7),\u0026nbsp;the lack of systematic and standardised measurement across countries hinders international benchmarking and efforts to improve efficiency (3). International collaboration is essential for developing solutions to address this issue. All.Can International (All.Can) is a not-for-profit, global multi-stakeholder organisation, working to improve the efficiency of cancer care. It operates through ten individual and 34 organisational members, as well as National All.Can teams, known as \u0026lsquo;National Initiatives\u0026rsquo;, across 21 countries. These include 12 countries in Europe, two in North America, two in South America, four in Asia and one in Oceania. All.Can is a\u0026nbsp;unique example of an organisation dedicated\u0026nbsp;to improving cancer care efficiency through\u0026nbsp;multi-stakeholder cooperation.\u003c/p\u003e\n\u003cp\u003eIn collaboration with the University of Southampton, All.Can\u003cem\u003e\u0026nbsp;\u003c/em\u003ehas previously identified a set of eight cancer efficiency metrics as a foundational starting point for standardising measurement across global cancer care pathways (8). These metrics focus on measurement of three core dimensions of efficiency: timeliness of care, coordination of care, and patient-centeredness.\u0026nbsp;However, knowing \u0026apos;what\u0026apos; to measure is only the first step; embedding these metrics across health systems to inform decision-making remains a significant challenge. A critical question is \u0026apos;how\u0026apos; to effectively implement these metrics, particularly through a cascading approach from clinical setting to managerial and policy-level decisions. Actionable guidance is needed to support implementation, with a focus on understanding both the enabling and hindering conditions from a system perspective. Furthermore, the variety of actors and their roles in cancer care and policy across health system levels, alongside the variety of governance models across countries, demands an engaged, multi-profile, multi-level and collaborative international approach.\u003c/p\u003e\n\u003cp\u003eThis study aims to identify barriers and enablers to implementing cancer efficiency metrics globally, at national and organisational levels, as perceived by multi-level stakeholders. To achieve this, the study describes the co-development of an actionable international implementation guide \u0026mdash; the All.Can \u0026lsquo;Action Guide for Efficient Cancer Care\u0026rsquo;. Designed for policy-makers, patient advocates, hospital managers, and healthcare professionals, the Guide is organised around three clusters of efficiency metrics (timeliness of care, coordination of care, and patient-centeredness) and aims to support these actors address real-world challenges and facilitators. With a focus on actionability, the Guide provides structured guidance and evidence-based recommendations to support stakeholders in embedding these metrics into routine practice.\u003c/p\u003e\n"},{"header":"Methods","content":"\u003ch2\u003eStudy design\u003c/h2\u003e\n\u003cp\u003eWe conducted an exploratory qualitative design (9). The study comprised two phases of data collection through semi-structured interviews: the first phase aimed to identify barriers, enablers and good practices for the use of cancer metrics at national and regional levels, while the second phase intended to characterise the implementation of good practices (Figure 1). Drawing on this data and applying a health systems research theory-based approach (10), we have outlined the structure of the Action Guide. The first iteration of the Action Guide was evaluated by potential end-users. During the design, development and validation phases, the research team engaged regularly with the All.Can community, employing a co-development approach to create an actionable implementation guide.\u003c/p\u003e\n\u003cp\u003eThe research team included five experts in health systems performance measurement and management and a doctoral student in the same field. EP is CEO of All.Can International (Additional file 1 includes the detailed team composition). Reporting complies with the consolidated criteria for reporting qualitative studies (COREQ) (11) (Additional file 2).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData collection\u003c/h2\u003e\n\u003cp\u003eTarget informants were national experts from All.Can from the three decision-making levels of healthcare systems - clinical, organisational and policy levels. All.Can comprises 34 organisational and ten individual members across the world, who promote its mission and work. Additionally, All.Can is active in 21 countries through National Initiatives that tailor its goals to local contexts. Representatives of all National Initiatives and one individual member were invited to participate in semi-structured interviews, by email. The background, aim and interview questions were sent in advance of each interview. The interview guide was structured in three sections, corresponding to the three metric clusters (Additional file 3). Based on their perception and knowledge, informants were also asked to provide examples of good practices from their country and identify potential informants.\u003c/p\u003e\n\u003cp\u003eThese interviews were conducted over a four-month period (July-October 2023) in pairs by the research team (DI, OBF, EB, ASVC, DK), for a duration of one hour, in English, via Microsoft Teams (version 25007.607.3371.8436). Interviews were recorded and transcribed verbatim with the agreement of the informants. Requests to reply in writing were accommodated. Field notes were prepared after the interviews by one interviewer and reviewed by the second. Five case studies were selected for in-depth characterisation, considering their potential for implementation in different contexts, scalability, and how evenly they were distributed across the metric clusters. The language, platform, duration, research team, recording and transcription processes were the same as in the first phase.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Data analysis\u003c/p\u003e\n\u003cp\u003eA qualitative content analysis (12) was conducted to characterise the magnitude of importance of specific attributes of context, as perceived by participants (Figure 2). This method was chosen to allow for some interpretation regarding the actionability of stakeholders\u0026rsquo; implementation efforts. The ICON framework (13) informed the deductive coding to identify and structure the full spectrum of perceived contextual barriers and enablers. This framework outlines domains of determinants that are considered to influence implementation outcomes, acting as barriers and enablers, focusing particularly on the identification of features of context. Data analysis was conducted with Microsoft Excel.\u003c/p\u003e\n\u003cp\u003eThe data analysis followed a structured approach combining inductive and deductive coding, guided by the ICON framework. First, open inductive coding was conducted to extract barriers and enablers from the transcripts. These were added into pre-structured spreadsheets \u0026mdash; one for each metric cluster (Additional file 4)\u0026mdash;representing the \u003cem\u003edecontextualisation\u003c/em\u003e phase. Next, the original transcripts were reviewed again by ASVC to ensure completeness and accuracy of the extracted content (\u003cem\u003erecontextualisation\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eIn the following step, similar barriers and enablers were grouped into inductive categories (\u003cem\u003efirst step of categorisation\u003c/em\u003e). These categories were then deductively matched to the external-level attributes of the ICON framework (\u003cem\u003esecond step of categorisation\u003c/em\u003e), enabling a theory-informed structuring of the data. For example, a quote such as \u0026ldquo;political momentum to focus on health data\u0026rdquo; was first coded inductively as \u0026ldquo;political will\u0026rdquo; and subsequently linked deductively to the ICON attribute \u0026ldquo;political influences\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eFinally, we quantified the number of barriers and enablers assigned to each ICON attribute to assess their relative prominence (\u003cem\u003efirst step of compilation\u003c/em\u003e). Given that not all informants commented on every issue, we did not apply further ranking or weighting to the attributes (12). To enhance the actionability of the findings for international stakeholders at different health system levels, themes and sub-themes of action were identified, considered as \u0026lsquo;preconditions for implementation\u0026rsquo; (\u003cem\u003esecond step of compilation\u003c/em\u003e). These themes were identified by the lead researcher (ASVC) from the interview notes and team debriefs, and underwent slight changes after revision by the research team, often related to clarity of wording. To each theme/sub-theme, actionable recommendations were developed. Coding was conducted by one researcher (ASVC, OBF, DI or EB) and reviewed by another, throughout.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eInclusive development and validation process of the Action Guide\u003c/h2\u003e\n\u003cp\u003eThe Action Guide was created anticipating the implementation of metrics per cluster in different countries, at national and organisational level. To increase the actionability of the Guide for various users and uses, it was agreed to provide step-by-step guidance in a non-linear document, which offers the possibility to navigate the Guide with no predetermined order, according to each user\u0026rsquo;s needs and with links to additional resources. As such, different entry points to the Guide were considered, inter-linked with clickable links to allow users to navigate from one to another to find useful resources for their needs. To do so, we made an inventory of theoretical frameworks of implementation science and we considered a classical framework of health systems research, developed by John \u0026Oslash;vretveit (10), as an actionable way of organising our data. This framework considers three questions to assess \u0026lsquo;why\u0026rsquo;, \u0026lsquo;what\u0026rsquo; and \u0026lsquo;how\u0026rsquo; to evaluate in the context of health systems research.\u003c/p\u003e\n\u003cp\u003eTo evaluate the Guide\u0026rsquo;s actionability , five of the informants from the second phase of data collection were purposefully selected and invited for three semi-structured interviews. These experts were potential end-users not directly involved in the development of the Guide, and experienced in implementing an innovative practice in their context. Interviews explored the usefulness, clarity and completeness of the Guide.\u0026nbsp;The preliminary version of the Guide, the aims and interview questions were sent in advance of each interview (Additional File 5).\u003c/p\u003e\n\u003cp\u003eThe Action Guide was developed with various moments of consultation over time with the All.Can community (Figure 1). Participants in stakeholder consultation included potential end-users, such as patient representatives, oncology healthcare professionals, academics, national health agency officials and industry representatives. This development process allowed to finetune the data analysis, to validate the results, and to receive feedback on successive drafts of the Guide. The Action Guide was launched in September 2024, where plans for international use and potential pilot projects were discussed.\u003c/p\u003e\n\u003cp\u003eThe results of this study are presented by addressing both aims of the study together, per cluster of efficiency metrics: timeliness of care, coordination of care and patient-centeredness. For each cluster, we first present an overview of the quantification of individual barriers and enablers to the implementation of metrics by visually showcasing their distribution across the ICON attributes. Categories of barriers and enablers are then detailed in-text. Subsequently, the themes and sub-themes of preconditions for implementation are presented in one table per cluster, together with illustrative quotes from the interviews.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eCharacteristics of informants\u003c/h2\u003e\n\u003cp\u003eA total of 31 informants from 21 countries participated in the first phase of data collection (Additional file 6). From the 22 invitations sent, 18 semi-structured interviews were conducted and three participants opted for written responses. Representatives from one country have declined to participate, due to insufficient knowledge on the subject. Several interviews included multiple informants, with six interviews involving two participants and two involving three. The informants represented diverse professional backgrounds, including oncology healthcare professionals, patient representatives, researchers, national health agency officials, and industry representatives. Given that some informants held multiple affiliations, they provided insights from different levels of the health system (Additional File 6 provides a detailed breakdown). In the second phase, nine informants contributed with insights on five selected good practice case studies. These discussions focused on implementation processes, encountered challenges, and strategies that facilitated success.\u003c/p\u003e\n\u003cp\u003eThe following sub-sections present the findings organised per cluster of metrics. Case studies were considered an essential component to enhance the Action Guide’s actionability to support end-users, by providing in-depth descriptions of phenomena in real-life contexts (14). Data from these case studies can be found in Additional file 7.\u003c/p\u003e\n\u003ch2\u003eBarriers, enablers and guidance to implement timeliness-of-care metrics\u003c/h2\u003e\n\u003cp\u003eRegulatory influences were identified as being the most prominent attribute of barriers and enablers regarding timeliness-of-care metrics: a total of 50 (63%) barriers and enablers related to these metrics were mentioned as pertaining to regulatory aspects of implementation, followed by 16 (20%) concerning political influences, 13 (16%) related to intercommunity / interorganizational / intersectoral relationships and 1 (1%) related to community influences. (Figure 3) (Additional file 8 presents the breakdown of barriers and enablers mapped to the ICON framework).\u003c/p\u003e\n\u003cp\u003eWith respect to regulatory influences, perceived\u0026nbsp;barriers were related to\u0026nbsp;the lack of a national approach regarding cancer data and different regulations supporting data collection between regions, provinces or territories. Various aspects related to the maturity of data ecosystems were perceived as barriers, such as the absence or underdevelopment of electronic health records, the lack of interoperability of databases, and lack of a nation-wide unique patient. Data collection not being available for monitoring purposes at National level was another perceived barrier. Enablers included the implementation and update of national strategic planning documents, the regulation of standardised care pathways, and legislation supporting cancer data collection, namely\u0026nbsp;the centralization of data collection.\u003c/p\u003e\n\u003cp\u003eRegarding political influences, the lack of political will and the time investment required to develop cancer registries were perceived as barriers, while collaboration at decision- making and external political pressure were considered enablers.\u003c/p\u003e\n\u003cp\u003eThe themes of preconditions for implementation of timeliness-of-care metrics identified were: ‘legal frameworks and strategy, policy context and funding’, ‘data governance’, and ‘data use and performance monitoring’ (Table 1) (Additional file\u0026nbsp;9\u0026nbsp;presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme).\u003c/p\u003e\n\u003cp\u003eTable 1 – Themes and sub-themes of preconditions for implementation of timeliness-of-care metrics\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTIMELINESS-OF-CARE METRICS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eThemes of preconditions for implementation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSub-themes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIllustrative quotes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLegal frameworks and strategy, policy context, funding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNational cancer control plan, its development and regular update\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“[this organization is mandated by the federal government] So they're the ones who hold the national cancers but create and encourage the implementation of the National Cancer strategy, for example. And they've also just released a National Cancer data strategy. So [they] work a lot with the cancer agencies directly to encourage alignment with that national strategy.” (Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNational health data ecosystem, including a national approach to cancer data collection and funding to develop the health data infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“By legislation, pathology services have to give that information to the cancer registries and any patient receiving radiation oncology that again is legislated. That information has to be given to the cancer registry data. It's fairly good. And as I say, it's being enhanced at the moment by a number of federally funded projects to increase the information on recurrence and metastasis as well, which will be excellent” (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eData governance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInteroperability among databases, considering promoting the maturity of electronic health records and the implementation of patient unique identifiers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“There is the “pension number”, but healthcare is not allowed to use it for data linkages.”; “Each hospital has a different system, but it is almost impossible to link them” (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eData use and performance monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMechanisms of feedback and learning, including investing in the availability of near real-time performance data, notably focusing on inequalities in access and quality of cancer care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“Treatment data is collected only at hospital-level (related to diagnosis and treatment) and is only available and used for reimbursement purposes, then only available to the health insurers and is not accessible for measurement efforts” (Sweden)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003eBarriers, enablers and guidance to implement coordination-of-care metrics\u003c/h2\u003e\n\u003cp\u003eRegulatory influences were identified as being the most prominent attribute of barriers and enablers for implementation of coordination-of-care metrics: a total of 39 (75%) barriers and enablers mentioned were in relation to these aspects of implementation, followed by less than ten barriers and enablers in relation to each of the others attributes of context (Figure 4). (Additional file 8 presents the breakdown of barriers and enablers mapped to the ICON framework).\u003c/p\u003e\n\u003cp\u003eConcerning regulatory influences, the absence of regulations defining the roles of multidisciplinary teams, oncology nurses and care coordinators, and defining the centralisation of cancer care in specialised centres were referred as challenges to implementation, together with the lack of regulation pertaining to task shifting and task sharing. With respect to political influences, workforce shortages and the lack of national of prioritisation of cancer nurses regulation were mentioned as barriers, while political will was perceived as enabler. In relation to community influences, the existence of active National Associations of Oncology Nurses and the providence of care coordinators by Non-Governmental Organisations and patient advocacy groups were perceived as enablers.\u003c/p\u003e\n\u003cp\u003eThe following preconditions themes\u0026nbsp;for\u0026nbsp;implementation of coordination-of-care metrics were identified in relation to the perceived\u0026nbsp;barriers and enablers: ‘workforce capacity’, ‘oncology nurses and cancer patient navigators’, ‘task sharing and substitution’, ‘multidisciplinary tumour boards’, and ‘comprehensive cancer centres’. (Table 2) (Additional file 9 presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme).\u003c/p\u003e\n\u003cp\u003eTable 2 - Themes and sub-themes of preconditions for implementation of coordination-of-care metrics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOORDINATION-OF-CARE METRICS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eThemes of preconditions for implementation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSub-themes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIllustrative quotes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWorkforce capacity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMonitoring and addressing workforce shortages in the cancer care ecosystem, ensuring it remains a national priority\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“But in there is health and human resources, right? I mean, I think us like everybody else's experiencing a lot of crises and people leaving because of burnout from the pandemic and from the fact that working is already difficult because of the fragmentation, lack of information […] There's more focus [and investment] is being put through […] the human resource piece. […]So there are priorities that have been named, that are being shared federally, provincially and territorially that relate to Health Human resources”\u0026nbsp;(Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOncology nurses and cancer patient navigators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegulation of the professional role of oncology nurses and cancer care navigators across the care pathway, ensuring similar mandates at subnational levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“both the General Nursing Council and Patient Organisations urge the institutionalization of the role of nurse case managers at all levels of care to address the cancer patient process in a comprehensive manner, with the aim of increasing the quality of care (…) and minimising the time between procedures. (…) This figure of case manager in the oncology field is being included (…) in pioneering hospitals” (Spain)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTask sharing and substitution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegulation concerning task sharing and substitution, ensuring harmonisation at subnational levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“[task shifting] It does [happen], yes. again it's very variable. you know, [our country] has probably got a stronger doctor input into most areas of care than many countries.” (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultidisciplinary tumour boards\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegulation of multidisciplinary tumour boards to ensure meeting quality standards, ensuring harmonisation at subnational levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“Multidisciplinary teams are not legally mandated nor regulated. [they] exist in most of the private sector, however this is not the case in the public sector. The patients have to move between hospitals to do different treatments […]. Hospitals are connected in a way, to send patients for specific treatments from one hospital to another. But there is no “team”. Also, teams have no psychologists or dieticians, for instance.” (Greece)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComprehensive cancer centres\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCentralisation of cancer care in specialised centres and monitoring patient access to ensure equal access to specialised care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“In fact, tumour boards are in the legislation for more 20 years but is it not obliged. Some private oncology hospitals organise their own tumour boards. […] [Our country has] around 400 sites where patients are treated. You can imagine how difficult it is: oncologists are in small hospitals and they have to decide […]. We do not have a centralised approach […]” (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eBarriers, enablers and guidance to implement patient-centeredness metrics\u003c/h2\u003e\n\u003cp\u003ePolitical influences were predominantly reported as influencing the implementation of patient-reported-metrics: a total of 21 (46%) barriers and enablers were mentioned as being in relation to political aspects of implementation, followed by 10 (22%) barriers and enablers mentioned as related to community influences and the same number related to regulatory influences (Figure 5). (Additional file 8 presents the breakdown of individual barriers and enablers mapped to the ICON framework).\u003c/p\u003e\n\u003cp\u003eRegarding political influences, insufficient political will, funding and the absence of a national approach to systematic data collection were identified as a barriers. With respect to community influences, low levels of health literacy and societal advocacy groups with no connection to the health care system were perceived as barriers. Advocacy efforts by patient groups, NGOs and organizations’ will to include patient perspectives were perceived as enablers.\u003c/p\u003e\n\u003cp\u003eWith respect to regulatory influences, the lack of embedding of these metrics in existing cancer registries or databases and lack of enforcement and feedback mechanisms were perceived as barriers. The use of standardised tools was perceived as an enabler.\u003c/p\u003e\n\u003cp\u003eLinking up the use of metrics to other functions and scaling up successfully run pilot projects were considered enablers for implementation related to interorganisational relationships.\u003c/p\u003e\n\u003cp\u003ePerceived barriers and enablers were identified in relation to the following preconditions: ‘legal frameworks and strategy, policy context and funding’ and ‘data governance, use, and reporting’. (Table 3) (Additional file 9 presents the table of recommendations published in the Action Guide in relation to each theme/sub-theme).\u003c/p\u003e\n\u003cp\u003eTable 3 - Themes and sub-themes of preconditions for implementation of patient-centeredness metrics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePATIENT-CENTEREDNESS METRICS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eThemes of preconditions for implementation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSub-themes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIllustrative quotes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLegal frameworks and strategy, policy context, funding\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eto patient-reported data collection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePolitical will and funding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“I think within the [health system] there is also the aim to try and put patient experience on an equal footing for clinical and quality outputs and safety, and so there's a real drive (…). So kind of developing national systematic ways of collecting data, allowing comparisons and driving improvement[…]”\u0026nbsp;(Case study England’s National Cancer Patient Experience Survey)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNational approach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“The cancer plan speaks very strongly about the need to collect patient reported outcomes and experience measures, but they're not collected systematically anywhere.” (Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUse of standardised tools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“ […] there was no instrument in [this country] for PREMs in cancer care. […]This is why we looked into what was done in other countries. I think that the main thing here was there was a gap in the standardised instrument […] \u0026nbsp;to inform policies” (Case study Swiss Cancer Patient Experiences)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInvolvement of patient groups and non-governmental organisations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“I think [our team] really understands the importance of involving the patient in key decisions about the survey. […] like the questions we should ask, how should we contact people, what the materials look like? […] I think that's really important […] that the patient should be involved at every step.” […] “I think another key enabler is the advisory group and the cancer charities that we have on the advisory group […]. I think it adds to the legitimacy of the survey. If you've got large cancer charities that are clearly supportive of the survey […], I think it gives patients more confidence in the survey and the importance of taking part. So when we come on to some of the challenges, the cancer charities have been really huge big advocates for the survey. […] having the cancer charities there that have got a really strong voice and a really kind of political power in this space, it's been really, really helpful”\u0026nbsp;(Case study England’s National Cancer Patient Experience Survey)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eData governance, use, and reporting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEmbedding of patient-reported metrics in cancer registries or databases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“As external researchers, we do not have access to patient data. […]and there's no registry of all the patients that go through […]care. […]. So, really, access to patient information is the key barrier here. […] Therefore, there are two main issues, identification of disease patients and identification of confirmed diagnosis. These are the two main challenges in these kind of [patient-reported measures] surveys.” (Case study Swiss Cancer Patient Experiences)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnforcement and feedback mechanisms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e“the patient experience surveys […]are developed […] to provide that national monitoring of progress against policy regulation[…]. But also key is that we're able to give the [organisations] who participate in the survey information to allow them to carry out quality improvement.” […] “And you see data from these national surveys feature heavily in the Care Quality Commission, who are our regulator and inspector for Health and Social Care. And when they go and inspect organizations, they're looking at data from patient experience surveys […], so that they can make judgments on how organizations are performing.” (Case study England’s National Cancer Patient Experience Survey)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eStructure of the Action Guide\u003c/h2\u003e\n\u003cp\u003eThe Action Guide was developed with three entry points: ‘Why’ – addressing the relevance of efficiency in cancer care, ‘What’ – characterising the three metrics clusters and related health system components, and ‘How’ – a roadmap to implementation (Figure 6). The ‘How’ section includes five steps: 1) it guides users to define context-specific priorities, drawing on the literature on cancer care efficiency; 2) it provides a preparedness checklist for metrics implementation, elaborated based on the categories of barriers and enablers identified; 3) it presents key contextual factors, based on the magnitude of relevance attributed to each ICON attribute at system level and detailing specific categories of barriers and enablers; 4) the Guide lists potential key actors to be involved in implementation efforts, compiled from the stakeholders mentioned in the interviews; 5) it provides key recommendations for metrics implementation per cluster, which are action points derived from the themes of preconditions identified. The good practices case studies are characterised at the end of the Guide and referred in each related cluster with hyperlinks. Related literature resources are provided throughout the Guide.\u003c/p\u003e\n\u003ch2\u003eLaunch of the Action Guide and dissemination activities\u003c/h2\u003e\n\u003cp\u003eThe launch of the Action Guide took place at an in-person meeting with the All.Can community in September 2024, in Geneva. The general public could attend virtually and interact via the chat and live polls. A summary of the Guide’s structure and guidance were presented in a plenary session, followed by a panel discussion. Live polls during this event showed the relevance, high level of interest and the intention to implement the Guide’s recommendations by this community. The Guide is available at All.Can International’s website (link). Following the launch event, various dissemination activities were carried out, enhancing the visibility of the Guide to a broader community (e.g. a conference abstract showcasing preliminary results was presented at the European Cancer Organisation’s Summit in November 2024 (15).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancer poses a significant challenge to health systems and to society as a whole. At health system level, current efforts emphasize measuring inputs and outcomes of cancer care, while lacking a systematic approach to measure the efficiency of cancer care (16; 3). However, international patient-reported data indicate that waiting times, poor care coordination and insufficient patient-centred care are critical concerns for individuals with chronic conditions (17). Employing a qualitative content analysis, this study mapped barriers and enablers to implementing cancer care efficiency metrics across health systems from the perspective of international multi-level stakeholders from 21 countries. Barriers and enablers were mapped to the attributes of the context from the Implementation in Context (ICON) Framework, per cluster of cancer care efficiency metrics: timeliness of care, coordination of care, and patient-centeredness. Furthermore, this study described the development of an Action Guide to support implementation of cancer efficiency metrics globally through a participatory process, identifying actionable themes with recommendations for action for multi-level stakeholders, underscoring the strong role of political, regulatory and advocacy factors at system level. Addressing barriers related to the regulation of standardised care pathways measuring timeliness targets and maturity of data ecosystems, while leveraging enablers such as the regulation of oncology nurses specialists, care navigators, and a standardised approach to patient-reported data collection, can foster the efficiency of cancer care globally.\u003c/p\u003e\n\u003cp\u003eIn relation to the timeliness-of-care metrics, regulatory aspects considered relevant to implementation were related to the development and regular update of national cancer control plans. Cancer plans contribute to prioritise cancer-specific actions at the health system level and are considered foundational to foster cancer control (18). The 2019 WHO global survey (19) showed that, despite 92% of the 177 responding countries having cancer plans or strategies, 80% were operational, showing room for improvement. As our study showed, international collaboration may foster cross-country learning and exchange to define key priorities and advance cancer plans.\u003c/p\u003e\n\u003cp\u003eFurthermore, our findings underscore the importance of developing national health data ecosystems, notably fostering the maturity of electronic health records and interoperability of databases to support the implementation of time-related cancer metrics. These insights also align with global momentum around digital health transformation, highlighting the need to invest in interoperable health information systems that can support real-time monitoring and data-driven cancer care improvements. This is corroborated in a recent OECD report \u003c!--[if supportFields]\u003e\u003cspan style='mso-bidi-font-family: Arial;mso-bidi-theme-font:minor-bidi'\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u0026nbsp;CITATION OEC25 \\l 2070 \u003c/span\u003e\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e(16)\u003c!--[if supportFields]\u003e\u003cspan style='mso-bidi-font-family:Arial;mso-bidi-theme-font:minor-bidi'\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c/span\u003e\u003c![endif]--\u003e showing that most EU countries struggle with effectively monitoring waiting times in the cancer care pathway. Our study further signals that the regulation of standardised care pathways, particularly including time targets, may prove a relevant enabler to foster timeliness of care. Previous studies have showed the potential for standardised cancer care pathways in improving cancer outcomes \u003c!--[if supportFields]\u003e\u003cspan style='mso-bidi-font-family: Arial;mso-bidi-theme-font:minor-bidi'\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003e\u0026nbsp;CITATION Rot12 \\l 2070\u0026nbsp;\u0026nbsp;\\m van20\u003c/span\u003e\u003cspan style='mso-element: field-separator'\u003e\u003c/span\u003e\u003c![endif]--\u003e(20; 21)\u003c!--[if supportFields]\u003e\u003cspan style='mso-bidi-font-family:Arial;mso-bidi-theme-font:minor-bidi'\u003e\u003cspan style='mso-element:field-end'\u003e\u003c/span\u003e\u003c/span\u003e\u003c![endif]--\u003e.\u003c/p\u003e\n\u003cp\u003eRegarding the coordination-of-care metrics, a strong emphasis on regulatory influences was also noticeable to strengthen the measurement and improve care coordination. Specifically, the regulation of advanced roles for nurses, care navigators, multidisciplinary teams, alongside concentrating cancer care. Previous research has underscored the potential to oncology nurses to deliver more integrated care (22)\u0026nbsp;(23) and European countries have recently been implementing additional roles for nurses to tackle increased health needs and oncologists shortages (24). A previous OECD report also underscored the role of legislation and regulation to remove barriers hindering the implementation of new advance practice nurses\u0026apos; roles (25). Furthermore, cancer care often requires two or more professionals to perform a task at any stage of the pathway (26), therefore professionals\u0026rsquo; cooperation is paramount. In line with our findings, worldwide cancer associations have been pushing for standardised formats for MDT meetings to foster coordination and shared-decision making (27). Additionally, concentrating cancer care is currently a priority in many countries and various initiatives have been leveraging national efforts to foster their implementation across Europe (16).\u003c/p\u003e\n\u003cp\u003eWith respect to the implementation of patient-reported metrics, political will, funding and a national approach to systematic data collection were perceived as having a stronger role to implementation. While most countries lack the implementation of national and standardised methods to collect patient-reported data (16), political momentum is growing internationally to increase efforts for collecting patient-reported-data to monitor and improve care (17). A systematic review addressing determinants to implement PROMs/PREMs has also identified the need to integrate them into existing workflow routines to ensure their use, to engage with health system\u0026rsquo;s leaders, and to involve all relevant stakeholders (28). Furthermore, our results signal the key role of advocacy efforts and the involvement of patient groups in the implementation of standardised approaches to patient-reported data collection.\u003c/p\u003e\n\u003cp\u003eIn addition, the absence of systematic data collection and uneven implementation of standardised metrics may exacerbate health disparities, particularly for underserved populations. Equity considerations should therefore underpin efforts to implement cancer care efficiency metrics, ensuring that improvements in timeliness, coordination, and patient-centeredness benefit all population groups equitably.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe international and participatory nature of this project, including multi-level stakeholders, allowed to account for various perspectives, which enabled to enrich and validate the research findings. Additionally, it fostered a sense of ownership, thereby contributing to a more successful adoption of the Guide\u0026rsquo;s recommendations. The implementation theory-based approach ensured a systematic and comprehensive mapping of factors influencing implementation of cancer efficiency metrics, while the quantification of the attributes of the ICON framework allowed to signal key areas to prioritise. Balancing the framework-informed method with an open-inductive coding to identify themes of preconditions enabled us to capture actionable points to which stakeholders may relate to drive change.\u003c/p\u003e\n\u003cp\u003eThis Guide was developed with input from only one international cancer community and the barriers and enablers reported are based on the perception and knowledge of the participants. Nonetheless, in the validation phase we received feedback from potential end-users not directly involved in the development process, which has contributed to improve the generalisability of the findings. While the research team maintained a facilitative role in the co-development process, we recognise that our background in health systems research and our collaboration with All.Can may have influenced how certain issues were framed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for practice and policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy employing an inclusive development approach and applying a theoretical implementation science approach, this study offers practical insights into how global exchange and collaboration can promote cross-country learning for the effective uptake of cancer efficiency metrics. The interaction between academic and practical approaches led to the refinement of both the content and format of our findings. For instance, during discussions on the first iteration of the Guide, the All.Can community requested to modify the name initially proposed by All.Can - \u0026lsquo;playbook\u0026rsquo; -, considering the sensitive nature of the issue. Thus, \u0026lsquo;Action Guide\u0026rsquo; was considered a more neutral and suitable title. This process emphasises the importance of striking a balance between theory and practice to effectively incorporate end-users\u0026rsquo; perspectives and needs into a widely accepted final product.\u003c/p\u003e\n\u003cp\u003eThe inclusive development process conducted in close collaboration with an international community has also showed that there is a relevant added value in having an international multi-stakeholder organisation engaging with an academic institution to develop a guiding framework for implementation. This co-development process has proven effective and has already yielded tangible results, namely the organisation of pilot projects in various All.Can member countries, showing the interest of the cancer community in the guidance and resources the Action Guide offers. The involvement of All.Can as co-authors of this work underscores the rationale behind this approach and further highlights the benefits of collaboration in ensuring the actionability and applicability of this work.\u003c/p\u003e\n\u003cp\u003eAs health systems face increasing pressures from rising cancer incidence and constrained resources, embedding efficiency metrics can also contribute to broader sustainability goals\u0026mdash;ensuring that care improvements are delivered in a way that is both economically and operationally viable over time. The flexible, modular structure of the Action Guide also supports its scalability and adaptability to different health system contexts, including varying resource settings.\u003c/p\u003e\n\u003cp\u003eFuture research could evaluate the uptake and use of the Action Guide, exploring the extent to which the final product reached its potential. Additionally, while this research intends to provide evidence to cancer-related policy-making, some of the findings may potentially be extrapolated to other clinical areas. Notably, the challenges of monitoring timeliness of care and patient-centredness are transversal to health care delivery.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identifies the perceived contextual barriers and enablers for implementing cancer efficiency metrics from the perspective of informants from an international multi-stakeholder cancer community, focusing on timeliness of care, coordination of care, and patient-centeredness. Moreover, this study describes the participatory development of an Action Guide designed to enhance the actionability of these metrics globally. This research contributes to the field by identifying actionable themes that multi-level stakeholders in the cancer field can prioritise to advance the implementation of these metrics within their specific contexts.\u003c/p\u003e\n\u003cp\u003eThe co-development of this Action Guide, owned and disseminated by an international multi-stakeholder cancer organisation, is a step forward to foster cross-country learning and ensure that research knowledge is effectively used to inform future cancer policies globally, ultimately aiming to enhance system performance, patient experiences and outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASVC: Ana Sofia V. Carvalho\u003c/p\u003e\n\u003cp\u003eDK: Dionne Kringos\u003c/p\u003e\n\u003cp\u003eEB: Erica Barbazza\u003c/p\u003e\n\u003cp\u003eEP: Eduardo Pisani\u003c/p\u003e\n\u003cp\u003eNK: Niek Klazinga\u003c/p\u003e\n\u003cp\u003eOECD: Organisation for Economic Co-operation and Development\u003c/p\u003e\n\u003cp\u003eOBF: \u0026Oacute;scar Brito Fernandes\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the non-WMO Committee of the Medical Ethics Review Committee of Amsterdam University Medical Centers: committee\u0026rsquo;s reference number 2023.0939. This committee is authorised by the board of directors of Amsterdam UMC and supervised by the Medical Ethics Review committee.\u0026nbsp;Participants in the study provided written informed consent during the recruitment phase and expressed their consent verbally at the start of the interviews. Interview data has been anonymised and confidentiality was assured by referring to informants by country name.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available in the Zenodo repository, 10.5281/zenodo.15184172.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eEP is the CEO of All.Can International. The other authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was funded by All.Can International.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eASVC, OBF, DI, EB, EP, NK and DK contributed to conceptualise the study. ASVC, OBF, DI, EB, and DK performed the data collection. ASVC performed the data analysis, which was revised by OBF, DI and EB. ASVC drafted the article. OBF, DI, EB, EP, NK and DK provided feedback and have contributed to revising the manuscript. All authors approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe authors wish to thank the interviewees for the time and insights they provided during the interviews. The authors also wish to thank members of the broader All.Can community for their engagement in the project and for their constructive feedback.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eInstitute for Health Metrics and Evaluation. IHME, data tools and practices, GBD Compare 2021 [Internet]. 2025 [cited 2025 Feb 26]. Available from: https://vizhub.healthdata.org/gbd-compare/.\u003c/li\u003e\n\u003cli\u003eOECD. Tackling the impact of cancer on health, the economy and society. Paris: OECD Publishing; 2024.\u003c/li\u003e\n\u003cli\u003eOECD. Beating cancer inequalities in the EU: Spotlight on cancer prevention and early detection. Paris: OECD Publishing; 2024.\u003c/li\u003e\n\u003cli\u003eSteel N, Bauer-Staeb CM, Ford JA, Abbafati C, Abdalla MA, Abdelkader A, et al. Changing life expectancy in European countries 1990\u0026ndash;2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021. Lancet Public Health. 2025 Mar 1;10:e172\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eKrzyszczyk P, Acevedo A, Davidoff EJ, Timmins LM, Marrero-Berrios I, Patel M, et al. The growing role of precision and personalized medicine for cancer treatment. Technol (Singap World Sci). 2018 Sep-Dec;6(3-4):79\u0026ndash;100.\u003c/li\u003e\n\u003cli\u003eOECD. Rethinking health system performance assessment: a renewed framework. Paris: OECD Publishing; 2024.\u003c/li\u003e\n\u003cli\u003eOECD. Cancer care: assuring quality to improve survival. 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Available from: https://doi.org/10.1787/20ef03e1-en\u003c/li\u003e\n\u003cli\u003eOECD. Does healthcare deliver?: Results from the Patient-Reported Indicator Surveys (PaRIS) [Internet]. Paris: OECD Publishing; 2025. Available from: https://doi.org/10.1787/c8af05a5-en\u003c/li\u003e\n\u003cli\u003eRomero Y, Tittenbrun Z, Trapani D, et al. The changing global landscape of national cancer control plans. Lancet Oncol. 2025;26(1):e46\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Assessing national capacity for the prevention and control of noncommunicable diseases: report of the 2019 global survey. Geneva: World Health Organization; 2020.\u003c/li\u003e\n\u003cli\u003eRotter T, Kinsman L, James E, et al. The effects of clinical pathways on professional practice, patient outcomes, length of stay, and hospital costs: Cochrane systematic review and meta-analysis. Eval Health Prof. 2012;35(1):3\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003evan Hoeve JC, Vernooij RWM, Fiander M, et al. Effects of oncological care pathways in primary and secondary care on patient, professional and health systems outcomes: a systematic review and meta-analysis. Syst Rev. 2020;9(1):246.\u003c/li\u003e\n\u003cli\u003eYoung AM, Charalambous A, Owen RI, Njodzeka B, Oldenmenger WH, Alqudimat MR, So WK. Essential oncology nursing care along the cancer continuum. Lancet Oncol. 2020 Dec 1;21(12):e555\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eMishelmovich N, Arber A, Odelius A. Breaking significant news: The experience of clinical nurse specialists in cancer and palliative care. Eur J Oncol Nurs. 2016 Apr 1;21:153\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eDelamaire M, Lafortune G. Nurses in advanced roles: A description and evaluation of experiences in 12 developed countries. Paris: OECD Health Working Papers No. 54, OECD Publishing; 2010.\u003c/li\u003e\n\u003cli\u003eChollette V, Beasley DD, Abdiwahab E, Taplin S. Health information systems approach to managing task interdependence in cancer care teams. J Oncol Pract. 2017 Mar 1;13(1):154\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eScott B. Multidisciplinary team approach in cancer care: A review of the latest advancements featured at ESMO 2021. EMJ Oncol. 2022;10(Suppl 6):2\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eGlenwright BG, Simmich J, Cottrell M, O\u0026rsquo;Leary SP, Sullivan C, Pole JD, Russell T. Facilitators and barriers to implementing electronic patient-reported outcome and experience measures in a health care setting: a systematic review. J Patient Rep Outcomes. 2023 Feb 14;7(1):13.\u003c/li\u003e\n\u003cli\u003eWHO Regional Office for Europe. Taking the pulse of quality of care and patient safety in the WHO European Region: multidimensional analysis and future prospects. Copenhagen: WHO Regional Office for Europe; 2024. Licence: CC BY-NC-SA 3.0.\u003c/li\u003e\n\u003cli\u003eESMO. WHO\u0026ndash;ESMO collaboration sets accessible cancer care, prevention and education as priority areas of intervention [Internet]. Dailyreporter.esmo.org; 2025 [cited 2025 Feb 3]. Available from: https://dailyreporter.esmo.org/news/who-esmo-collaboration-sets-accessible-cancer-care-prevention-and-education-as-priority-areas-of-intervention\u003c/li\u003e\n\u003cli\u003eEuropean Health Data Space [Internet]. European Commission; 2025. Available from: https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space_en\u003c/li\u003e\n\u003cli\u003eEuropean Health Data Space [Internet]. Health.ec.europa.eu. Available from: https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space_en\u003c/li\u003e\n\u003cli\u003eMcDowell BD, Klemp J, Blaes A, Cohee AA, Trentham-Dietz A, Kamaraju S, et al. The association between cancer care coordination and quality of life is stronger for breast cancer patients with lower health literacy: A Greater Plains Collaborative study. Support Care Cancer. 2020 Feb;28:887-95.\u003c/li\u003e\n\u003cli\u003eUnder Pressure: Safeguarding the Health of Europe\u0026apos;s Oncology Workforce [Internet]. Europeancancer.org. Available from: https://www.europeancancer.org/resources/publications/under-pressure-safeguarding-the-health-of-europes-oncology-workforce.html\u003c/li\u003e\n\u003cli\u003eMorabito A, Mercadante E, Muto P, Manzo A, Palumbo G, Sforza V, et al. Improving the quality of patient care in lung cancer: key factors for successful multidisciplinary team working. Explor Target Antitumor Ther. 2024;5(2):260.\u003c/li\u003e\n\u003cli\u003eEUnetCC - The European Comprehensive Cancer Center Network [Internet]. German Cancer Society; 2025 [cited 2025 Mar 3]. Available from: https://ecc-cert.org/health-service-research/eunetccc/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-research-policy-and-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hrps","sideBox":"Learn more about [Health Research Policy and Systems](http://health-policy-systems.biomedcentral.com/)","snPcode":"12961","submissionUrl":"https://submission.nature.com/new-submission/12961/3","title":"Health Research Policy and Systems","twitterHandle":"@HarpsJournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cancer, Efficiency, Implementation, Cancer policy, Cancer care coordination, Health Care Quality, Access, and Evaluation [MeSH], Quality of Health Care [MeSH], Barriers, Enablers, Quality Indicators","lastPublishedDoi":"10.21203/rs.3.rs-6429529/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6429529/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Cancer care efficiency contributes to overall healthcare systems performance. However, many healthcare systems experience challenges in measuring it effectively. All.Can, a multi-stakeholder organisation working to improve cancer care efficiency, has identified eight cancer metrics as a starting point for standardising efficiency measurement, focusing on timeliness of care, coordination of care, and patient-centeredness. This study aims to identify barriers and enablers to implementing these metrics globally and to describe the co-development of a guide to support stakeholders in embedding these metrics into healthcare workflows.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This qualitative study used a co-development approach in collaboration with the All.Can community. Semi-structured interviews were conducted to identify barriers, enablers and good practices in implementing cancer care efficiency metrics. Data were analysed using a combination of deductive and inductive coding, guided in part by the Implementation in Context (ICON) framework. A qualitative content analysis was conducted to explore the perceived actionability of contextual factors, which informed the development of an Action Guide grounded in health systems research principles. The guide was reviewed by potential end-users and launchedin September 2024.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Forty informants from 21 countries have participated in semi-structured interviews. Regulatory influences were most frequently cited as relevant factors for implementing timeliness-of-care metrics. Barriers included fragmented or missing regulations on cancer data collection and limited database interoperability, while enablers involved national strategies and standardised care pathways. For coordination-of-care metrics, regulatory issues were again central, notably the lack of regulation defining roles such as oncology nurses and care coordinators. Political influences emerged prominently for patient-reported metrics, including lack of funding and absence of systematic data collection strategies. Advocacy was often seen as a key enabler. These informed the development of an Action Guide, intended to support the implementation of cancer care metrics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: This study identified contextual barriers and enablers for implementing cancer efficiency metrics and described the co-development of the All.Can Action Guide as a practical tool for policymakers, care providers and advocates. Through mapping priority areas for action, this study may strengthen data-driven decision-making, enhance timeliness and coordination of care, and ultimately improve patient outcomes and experiences worldwide.\u003c/p\u003e","manuscriptTitle":"International multi-stakeholder collaboration to support implementation of cancer care efficiency metrics: A qualitative study to develop the All. 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