Observational health research in Europe: understanding the General Data Protection Regulation and underlying debate

Sharing sensitive data in life sciences: an overview of centralized and federated approaches

Biomedical data are generated and collected from various sources, including medical imaging, laboratory tests and genome sequencing. Sharing these data for research can help address unmet health needs, contribute to scientific breakthroughs, accelerate the development of more effective treatments and inform public health policy. Due to the potential sensitivity of such data, however, privacy concerns have led to policies that restrict data sharing. In addition, sharing sensitive data requires a secure and robust infrastructure with appropriate storage solutions. Here, we examine and compare the centralized and federated data sharing models through the prism of five large-scale and real-world use cases of strategic significance within the European data sharing landscape: the French Health Data Hub, the BBMRI-ERIC Colorectal Cancer Cohort, the federated European Genome-phenome Archive, the Observational Medical Outcomes Partnership/OHDSI network and the EBRAINS Medical Informatics Platform. Our analysis indicates that centralized models facilitate data linkage, harmonization and interoperability, while federated models facilitate scaling up and legal compliance, as the data typically reside on the data generator's premises, allowing for better control of how data are shared. This comparative study thus offers guidance on the selection of the most appropriate sharing strategy for sensitive datasets and provides key insights for informed decision-making in data sharing efforts.

Lessons learned from the development of a national registry on dementia care and support based on linked national health and administrative data

Introduction

This paper provides insight into the development of the Dutch Dementia Care and Support Registry and the lessons that can be learned from it. The aim of this Registry was to contribute to quality improvement in dementia care and support.

Methods

This paper describes how the Registry was set up in four stages, reflecting the four FAIR principles: the selection of data sources (Findability); obtaining access to the selected data sources (Accessibility); data linkage (Interoperability); and the reuse of data (Reusability).

Results

The linkage of 16 different data sources, including national routine health and administrative data appeared to be technically and legally feasible. The linked data in the Registry offers rich information about (the use of) care for persons with dementia across various healthcare settings, including but not limited to primary care, secondary care, long-term care and medication use, that cannot be obtained from single data sources.

Conclusions

A key lesson learned is that in order to reuse the data for quality improvement in practice, it is essential to involve healthcare professionals in setting up the Registry and to guide them in the interpretation of the data.

Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators

Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.

Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium

In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.

Comparing quality of breast cancer care in the Netherlands and Norway by federated propensity score analytics

PURPOSE

The aim of the study was to benchmark and compare breast cancer care quality indicators (QIs) between Norway and the Netherlands using federated analytics preventing transfer of patient-level data.

METHODS

Breast cancer patients (2017-2018) were retrieved from the Netherlands Cancer Registry and the Cancer Registry of Norway. Five European Society of Breast Cancer Specialists (EUSOMA) QIs were assessed: two on magnetic resonance imaging (MRI), two on surgical approaches, and one on postoperative radiotherapy. The QI outcomes were calculated using 'Vantage 6' federated Propensity Score Stratification (PSS). Likelihood of receiving a treatment was expressed in odds ratios (OR).

RESULTS

In total, 39,163 patients were included (32,786 from the Netherlands and 6377 from Norway). PSS scores were comparable to the crude outcomes of the QIs. The Netherlands scored higher on the QI 'proportions of patients preoperatively examined with breast MRI' [37% vs.17.5%; OR 2.8 (95% CI 2.7-2.9)], the 'proportions of patients receiving primary systemic therapy examined with breast MRI' [83.3% vs. 70.8%; OR 2.3 (95% CI 1.3-3.3)], and 'proportion of patients receiving a single breast operation' [95.2% vs. 91.5%; OR 1.8 (95% CI 1.4-2.2)]. Country scores for 'immediate breast reconstruction' and 'postoperative radiotherapy after breast-conserving surgery' were comparable. The EUSOMA standard was achieved in both countries for 4/5 indicators.

CONCLUSION

Both countries achieved high scores on the QIs. Differences were observed in the use of MRI and proportion of patients receiving single surgery. The federated approach supports future possibilities on benchmark QIs without transfer of privacy-sensitive data.

Towards trust-based governance of health data research

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research-among researchers and with data subjects-is grounded in trust, which should be more explicitly recognised in the governance of health data research.

The application of data altruism in clinical research through empirical and legal analysis lenses

Background

The legal framework for clinical research in the EU is complex and the lack of harmonization of the relevant legal and ethical rules remains one of the main challenges for stakeholders in the field. The recently adopted Data Governance Act (DGA) and the proposal for a European Health Data Space (EHDS) promise to solve the existing challenges with respect to access to and (re)use of personal data for research, but also risk to further complexify the field. The DGA introduced a novel mechanism - data altruism. Data altruism is understood as the voluntary sharing of personal and non-personal data, based on the consent of data subjects or the permission of natural and legal persons, without seeking a reward and for objectives of general interest. This study aimed to gain insights into the opinion of clinical research stakeholders on data altruism, and to critically discuss key issues pertaining to the application of data altruism from a legal point of view.

Methods

Semi-structured interviews with (1) data protection officers (DPOs) and legal experts working with commercial and academic sponsors of clinical trials, (2) investigators, and (3) members of research ethics committees. Data underwent framework analysis. The legal discussion was comprised of legal doctrinal research with focus on the DGA, EHDS proposal, and the interplay with the EU General Data Protection Regulation (GDPR).

Results

Fourteen experts took part in the interviews, more than half of which were DPOs/legal experts. Interviewees were based in seven EU Member states and the United Kingdom. The majority of participants were critical towards the data altruism mechanism and pointed out challenges and risks associated with its application.

Conclusion

Although data altruism holds the potential to facilitate data sharing, its application in clinical research at the moment is still riddled with uncertainties. The interplay of the DGA rules with the provisions of the GDPR and the EHDS proposal are insufficiently clear and further efforts from the legislator are required to build a working, patient-centered, and research fostering data altruism system.

Opt-In and Opt-Out Consent Procedures for the Reuse of Routinely Recorded Health Data in Scientific Research and Their Consequences for Consent Rate and Consent Bias: Systematic Review

BACKGROUND

Scientific researchers who wish to reuse health data pertaining to individuals can obtain consent through an opt-in procedure or opt-out procedure. The choice of procedure may have consequences for the consent rate and representativeness of the study sample and the quality of the research, but these consequences are not well known.

OBJECTIVE

This review aimed to provide insight into the consequences for the consent rate and consent bias of the study sample of opt-in procedures versus opt-out procedures for the reuse of routinely recorded health data for scientific research purposes.

METHODS

A systematic review was performed based on searches in PubMed, Embase, CINAHL, PsycINFO, Web of Science Core Collection, and the Cochrane Library. Two reviewers independently included studies based on predefined eligibility criteria and assessed whether the statistical methods used in the reviewed literature were appropriate for describing the differences between consenters and nonconsenters. Statistical pooling was conducted, and a description of the results was provided.

RESULTS

A total of 15 studies were included in this meta-analysis. Of the 15 studies, 13 (87%) implemented an opt-in procedure, 1 (7%) implemented an opt-out procedure, and 1 (7%) implemented both the procedures. The average weighted consent rate was 84% (60,800/72,418 among the studies that used an opt-in procedure and 96.8% (2384/2463) in the single study that used an opt-out procedure. In the single study that described both procedures, the consent rate was 21% in the opt-in group and 95.6% in the opt-out group. Opt-in procedures resulted in more consent bias compared with opt-out procedures. In studies with an opt-in procedure, consenting individuals were more likely to be males, had a higher level of education, higher income, and higher socioeconomic status.

CONCLUSIONS

Consent rates are generally lower when using an opt-in procedure compared with using an opt-out procedure. Furthermore, in studies with an opt-in procedure, participants are less representative of the study population. However, both the study populations and the way in which opt-in or opt-out procedures were organized varied widely between the studies, which makes it difficult to draw general conclusions regarding the desired balance between patient control over data and learning from health data. The reuse of routinely recorded health data for scientific research purposes may be hampered by administrative burdens and the risk of bias.

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

BACKGROUND

Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and processing of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland's geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations.

METHODS

To conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform.

RESULTS

For our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation.

CONCLUSION

Our findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

Challenges related to data protection in clinical research before and during the COVID-19 pandemic: An exploratory study

Background

The COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.

Materials and methods

The study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.

Results and conclusion

In total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

How to balance valuable innovation with affordable access to medicines in Belgium?

Background: Countries are struggling to provide affordable access to medicines while supporting the market entry of innovative, expensive products. This Perspective aims to discuss challenges and avenues for balancing health care system objectives of access, affordability and innovation related to medicines in Belgium (and in other countries). Methods: This Perspective focuses on the R&D, regulatory approval and market access phases, with particular attention to oncology medicines, precision medicines, orphan medicines, advanced therapies, repurposed medicines, generics and biosimilars. The authors conducted a narrative review of the peer-reviewed literature, of the grey literature (such as policy documents and reports of consultancy agencies), and of their own research. Results: Health care stakeholders need to consider various initiatives for balancing innovation with access to medicines, which relate to clinical and non-clinical outcomes (e.g. supporting the conduct of pragmatic clinical trials, treatment optimisation and patient preference studies, optimising the use of real-world evidence in market access decision making), value assessment (e.g. increasing the transparency of the reimbursement system and criteria, tailoring the design of managed entry agreements to specific types of uncertainty), affordability (e.g. harnessing the role of generics and biosimilars in encouraging price competition, maximising opportunities for personalising and repurposing medicines) and access mechanisms (e.g. promoting collaboration and early dialogue between stakeholders including patients). Conclusion: Although there is no silver bullet that can balance valuable innovation with affordable access to medicines, (Belgian) policy and decision makers should continue to explore initiatives that exploit the potential of both the on-patent and off-patent pharmaceutical markets.

Patients' and Publics' Preferences for Data-Intensive Health Research Governance: Survey Study

Background

Patients and publics are generally positive about data-intensive health research. However, conditions need to be fulfilled for their support. Ensuring confidentiality, security, and privacy of patients’ health data is pivotal. Patients and publics have concerns about secondary use of data by commercial parties and the risk of data misuse, reasons for which they favor personal control of their data. Yet, the potential of public benefit highlights the potential of building trust to attenuate these perceptions of harm and risk. Nevertheless, empirical evidence on how conditions for support of data-intensive health research can be operationalized to that end remains scant.

Objective

This study aims to inform efforts to design governance frameworks for data-intensive health research, by gaining insight into the preferences of patients and publics for governance policies and measures.

Methods

We distributed a digital questionnaire among a purposive sample of patients and publics. Data were analyzed using descriptive statistics and nonparametric inferential statistics to compare group differences and explore associations between policy preferences.

Results

Study participants (N=987) strongly favored sharing their health data for scientific health research. Personal decision-making about which research projects health data are shared with (346/980, 35.3%), which researchers/organizations can have access (380/978, 38.9%), and the provision of information (458/981, 46.7%) were found highly important. Health data–sharing policies strengthening direct personal control, like being able to decide under which conditions health data are shared (538/969, 55.5%), were found highly important. Policies strengthening collective governance, like reliability checks (805/967, 83.2%) and security safeguards (787/976, 80.6%), were also found highly important. Further analysis revealed that participants willing to share health data, to a lesser extent, demanded policies strengthening direct personal control than participants who were reluctant to share health data. This was the case for the option to have health data deleted at any time (P<.001) and the ability to decide the conditions under which health data can be shared (P<.001). Overall, policies and measures enforcing conditions for support at the collective level of governance, like having an independent committee to evaluate requests for access to health data (P=.02), were most strongly favored. This also applied to participants who explicitly stressed that it was important to be able to decide the conditions under which health data can be shared, for instance, whether sanctions on data misuse are in place (P=.03).

Conclusions

This study revealed that both a positive attitude toward health data sharing and demand for personal decision-making abilities were associated with policies and measures strengthening control at the collective level of governance. We recommend pursuing the development of this type of governance policy. More importantly, further study is required to understand how governance policies and measures can contribute to the trustworthiness of data-intensive health research.

A process evaluation of 'We Can Quit': a community-based smoking cessation intervention targeting women from areas of socio-disadvantage in Ireland

Background

Smoking poses a serious risk of early preventable death and disease especially for women living with socio-economic disadvantage (SED). A smoking cessation programme, ‘We Can Quit’, was developed in Ireland tailored to SED women. This includes group-based support delivered by trained lay local community facilitators (CFs) and free nicotine replacement therapy (NRT). The intervention was pilot tested in a cluster randomised controlled trial, ‘We Can Quit 2’. This paper reports on the WCQ2 process evaluation which assessed feasibility and acceptability of the programme and trial processes.

Methods

Embedded qualitative design using the UK Medical Research Council’s process evaluation framework. Semi-structured interviews with trial participants (N = 21) and CFs (N = 8). Thematic analysis was utilised.

Results

Peer-modelling, a non-judgemental environment, CFs facilitation of group support were viewed as acceptable programme related factors. Some participants expressed concerns about NRT side effects. Provision of free NRT was welcomed and accepted by participants, although structural barriers made access challenging. Pharmacists took on a role that became larger than originally envisaged – and the majority provided additional support to women in their quit attempts between group meetings which augmented and supplemented the intervention sessions provided by the CFs. Participants reported good acceptance of repeated measures for data collection, but mixed acceptability of provision of saliva samples. Low literacy affected the feasibility of some women to fully engage with programme and trial-related materials. This was despite efforts made by intervention developers and the trial team to make materials (e.g., participant intervention booklet; consent forms and participant information leaflets) accessible while also meeting requirements under 2018 European General Data Protection Regulation legislation. Hypothetical scenarios of direct (e.g., researcher present during programme delivery) and indirect (e.g., audio recordings of programme sessions) observational fidelity assessments for a future definitive trial (DT) were acceptable.

Conclusions

Intervention and trial-related processes were generally feasible and acceptable to participants and CFs. Any future DT will need to take further steps to mitigate structural barriers to accessing free NRT; and the established problem of low literacy and low educational attainment in SED areas, while continuing to comply within the contemporary legislative research environment.

Trial registration

WCQ2 pilot trial (ISRCTN74721694).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13957-5.

An empirical investigation into the altering health perspectives in the internet of health things

Healthcare is on top of the agenda of all governments in the world as it is related to the well-being of the people. Naturally, this domain has attracted the attention of many researchers globally, who have studied the development of its different phases, including E-Health and the Internet of Health Things (IoHT). In this paper, the difference between the recent concepts of healthcare (E-health, M-Health, S-Health, I-Health, U-Health, and IoHT/IoMT) is analyzed based on the main services, applications, and technologies in each concept. The paper has also studied the latest developments in IoHT, which are linked to existing phases of development. A classification of groups of services and constituents of IoHT, linked to the latest technologies, is also provided. In addition, challenges, and future scope of research in this domain concerning the wellbeing of the people in the face of ongoing COVID-19 and future pandemics are explored.

A Federated Generalized Linear Model for Privacy-Preserving Analysis

In the last few years, federated learning (FL) has emerged as a novel alternative for analyzing data spread across different parties without needing to centralize them. In order to increase the adoption of FL, there is a need to develop more algorithms that can be deployed under this novel privacy-preserving paradigm. In this paper, we present our federated generalized linear model (GLM) for horizontally partitioned data. It allows generating models of different families (linear, Poisson, logistic) without disclosing privacy-sensitive individual records. We describe its algorithm (which can be implemented in the user’s platform of choice) and compare the obtained federated models against their centralized counterpart, which were mathematically equivalent. We also validated their execution time with increasing numbers of records and involved parties. We show that our federated GLM is accurate enough to be used for the privacy-preserving analysis of horizontally partitioned data in real-life scenarios. Further development of this type of algorithm has the potential to make FL a much more common practice among researchers.

Position paper on management of personal data in environment and health research in Europe

Management of datasets that include health information and other sensitive personal information of European study participants has to be compliant with the General Data Protection Regulation (GDPR, Regulation (EU) 2016/679). Within scientific research, the widely subscribed'FAIR' data principles should apply, meaning that research data should be findable, accessible, interoperable and re-usable. Balancing the aim of open science driven FAIR data management with GDPR compliant personal data protection safeguards is now a common challenge for many research projects dealing with (sensitive) personal data. In December 2020 a workshop was held with representatives of several large EU research consortia and of the European Commission to reflect on how to apply the FAIR data principles for environment and health research (E&H). Several recent data intensive EU funded E&H research projects face this challenge and work intensively towards developing solutions to access, exchange, store, handle, share, process and use such sensitive personal data, with the aim to support European and transnational collaborations. As a result, several recommendations, opportunities and current limitations were formulated. New technical developments such as federated data management and analysis systems, machine learning together with advanced search software, harmonized ontologies and data quality standards should in principle facilitate the FAIRification of data. To address ethical, legal, political and financial obstacles to the wider re-use of data for research purposes, both specific expertise and underpinning infrastructure are needed. There is a need for the E&H research data to find their place in the European Open Science Cloud. Communities using health and population data, environmental data and other publicly available data have to interconnect and synergize. To maximize the use and re-use of environment and health data, a dedicated supporting European infrastructure effort, such as the EIRENE research infrastructure within the ESFRI roadmap 2021, is needed that would interact with existing infrastructures.

You Can't Have AI Both Ways: Balancing Health Data Privacy and Access Fairly

Artificial intelligence (AI) in healthcare promises to make healthcare safer, more accurate, and more cost-effective. Public and private actors have been investing significant amounts of resources into the field. However, to benefit from data-intensive medicine, particularly from AI technologies, one must first and foremost have access to data. It has been previously argued that the conventionally used “consent or anonymize approach” undermines data-intensive medicine, and worse, may ultimately harm patients. Yet, this is still a dominant approach in European countries and framed as an either-or choice. In this paper, we contrast the different data governance approaches in the EU and their advantages and disadvantages in the context of healthcare AI. We detail the ethical trade-offs inherent to data-intensive medicine, particularly the balancing of data privacy and data access, and the subsequent prioritization between AI and other effective health interventions. If countries wish to allocate resources to AI, they also need to make corresponding efforts to improve (secure) data access. We conclude that it is unethical to invest significant amounts of public funds into AI development whilst at the same time limiting data access through strict privacy measures, as this constitutes a waste of public resources. The “AI revolution” in healthcare can only realise its full potential if a fair, inclusive engagement process spells out the values underlying (trans) national data governance policies and their impact on AI development, and priorities are set accordingly.

Federated horizontally partitioned principal component analysis for biomedical applications

Motivation

Federated learning enables privacy-preserving machine learning in the medical domain because the sensitive patient data remain with the owner and only parameters are exchanged between the data holders. The federated scenario introduces specific challenges related to the decentralized nature of the data, such as batch effects and differences in study population between the sites. Here, we investigate the challenges of moving classical analysis methods to the federated domain, specifically principal component analysis (PCA), a versatile and widely used tool, often serving as an initial step in machine learning and visualization workflows. We provide implementations of different federated PCA algorithms and evaluate them regarding their accuracy for high-dimensional biological data using realistic sample distributions over multiple data sites, and their ability to preserve downstream analyses.

Results

Federated subspace iteration converges to the centralized solution even for unfavorable data distributions, while approximate methods introduce error. Larger sample sizes at the study sites lead to better accuracy of the approximate methods. Approximate methods may be sufficient for coarse data visualization, but are vulnerable to outliers and batch effects. Before the analysis, the PCA algorithm, as well as the number of eigenvectors should be considered carefully to avoid unnecessary communication overhead.

Availability and implementation

Simulation code and notebooks for federated PCA can be found at https://gitlab.com/roettgerlab/federatedPCA; the code for the federated app is available at https://github.com/AnneHartebrodt/fc-federated-pca.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Enablers and barriers to the secondary use of health data in Europe: general data protection regulation perspective

Background

The General Data Protection Regulation is a regulation in EU law on data protection and privacy in the European Union. We aimed to provide an overview of the General Data Protection Regulation (GDPR) enablers and barriers to the secondary use of health data in Europe from the research we conducted in the Joint Action InfAct (Information for Action!) WP10 Assessing and piloting interoperability for public health policy, as well as to provide an example of a national-level case study on experiences with secondary use of health data and GDPR on an example of the Austrian COVID-19 data platform.

Methods

We have identified a number of European initiatives, projects and organizations that have dealt with cross-border health data sharing, linkage and management by desk research and we conducted 17 semi-structured in-depth interviews and analyzed the interview transcripts by framework analysis.

Results

GDPR was seen as an enabler to the secondary use of health data in Europe when it comes to user rights over their data, pre-existing laws regarding data privacy and data sharing, sharing anonymized statistics, developing new data analysis approaches, patients` trust towards dealing with their health data and transparency. GDPR was seen as a barrier to the secondary use of health data in Europe when it comes to identifiable and individual-level data, data sharing, time needed to complete the process, workload increase, differences with local legal legislations, different (and stricter) interpretations and access to data.

Conclusion

The results of our analysis show that GDPR acts as both an enabler and a barrier for the secondary use of health data in Europe. More research is needed to better understand the effects of GDPR on the secondary use of health data which can serve as a basis for future changes in the regulation.

Patients' and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence

INTRODUCTION

International sharing of health data opens the door to the study of the so-called 'Big Data', which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a 'social license' is identifying the views patients and the public may hold with regard to data sharing for health research.

METHODS

We performed a narrative review of the empirical evidence addressing patients' and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients' and public attitudes were extracted from selected references and thematically categorised.

RESULTS

Twenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread-though conditional-support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability.

CONCLUSIONS

Our results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests.

Human exposome assessment platform

The Human Exposome Assessment Platform (HEAP) is a research resource for the integrated and efficient management and analysis of human exposome data. The project will provide the complete workflow for obtaining exposome actionable knowledge from population-based cohorts. HEAP is a state-of-the-science service composed of computational resources from partner institutions, accessed through a software framework that provides the world's fastest Hadoop platform for data warehousing and applied artificial intelligence (AI). The software, will provide a decision support system for researchers and policymakers. All the data managed and processed by HEAP, together with the analysis pipelines, will be available for future research. In addition, the platform enables adding new data and analysis pipelines. HEAP's final product can be deployed in multiple instances to create a network of shareable and reusable knowledge on the impact of exposures on public health.

Identifying common enablers and barriers in European health information systems

European countries possess unique health information systems (HISs) and face similar health system challenges. Investigating common enablers and barriers across Europe pinpoint where HISs need improvements to address these challenges. This study aims to identify common enablers and barriers for optimal functioning of HISs across the European Union and associated countries, and to interpret what this means for the further development of HISs in Europe. A qualitative thematic analysis was carried out based on nine countries HISs assessments. Two main observations are made. Firstly, regardless of the differences between HISs, each HIS had its strengths and weaknesses and often the same barriers and enablers arose. Secondly, barriers were identified in all HIS areas. The five most important barriers are (i) fragmentation of data sources, limited accessibility, use and re-use of data, (ii) barriers in the implementation of EHR-systems, (iii) governance issues related to unclear responsibilities, discontinuous financing and weak intra- and inter-sectorial collaboration, (iv) legal gaps and General Data Protection Regulation (mis)interpretation, and (v) limited skilled staff. The enablers identified in this study lead to potential solutions to address these. Solutions can be implemented by national initiatives, but there is considerable added value in a joint European approach. Several international initiatives provide opportunities to improve HISs, but these need to be strengthened and better geared towards tackling the identified barriers.

Barriers and Facilitators for Implementing a National Guideline to Foster the Responsible Use of Residual Biospecimens and Data in Health Research

Residual biospecimens that are stored in hospitals' diagnostic specimen archives can be used for scientific research under strict legal and ethical regulations. In the Netherlands, a Code of Conduct governs responsible secondary use of residual biospecimens. However, implementation of this Code seems to be challenging. This study aims to explore the most important factors that facilitate or hinder the implementation of the Code. In addition, it investigates what is needed to further foster the responsible use of residual biospecimens. A mixed-methods design was used. Questionnaires were sent out to pathologists, patient information centers, physicians, researchers, data protection officers (DPOs), members of research ethics committees, and members of the boards of directors of all hospitals in the Netherlands (81 hospitals). To further investigate the barriers and facilitators, interviews were conducted with pathologists, patient information centers, physician-researchers, DPOs, review boards, research coordinators, and quality managers of pathology departments. In total, 246 respondents filled out the questionnaire and 36 interviews were conducted. Major barriers for implementing were a lack of resources (time, money), a lack of attention for responsible use, and a lack of practical knowledge (knowing what to do, where to go with questions). In contrast, the perception that implementing the Code was necessary, either by the respondent or by colleagues, was considered "a driver" for implementation. Practical instruments such as checklists and roadmaps were considered necessary to foster implementation; however, the creation of such instruments was hindered by a lack of clear-cut answers regarding legal aspects. Therefore, more clarity and harmonization on how to interpret both the Code and legislation regarding secondary use were considered necessary.

Record linkage of population-based cohort data from minors with national register data: a scoping review and comparative legal analysis of four European countries

Background: The GDPR was implemented to build an overarching framework for personal data protection across the EU/EEA. Linkage of data directly collected from cohort participants, potentially serving as a prominent tool for health research, must respect data protection rules and privacy rights. Our objective was to investigate law possibilities of linking cohort data of minors with routinely collected education and health data comparing EU/EEA member states. Methods: A legal comparative analysis and scoping review was conducted of openly accessible published laws and regulations in EUR-Lex and national law databases on GDPR's implementation in Portugal, Finland, Norway, and the Netherlands and its connected national regulations purposing record linkage for health research that have been implemented up until April 30, 2021. Results: The GDPR does not ensure total uniformity in data protection legislation across member states offering flexibility for national legislation. Exceptions to process personal data, e.g., public interest and scientific research, must be laid down in EU/EEA or national law. Differences in national interpretation caused obstacles in cross-national research and record linkage: Portugal requires written consent and ethical approval; Finland allows linkage mostly without consent through the national Social and Health Data Permit Authority; Norway when based on regional ethics committee's approval and adequate information technology safeguarding confidentiality; the Netherlands mainly bases linkage on the opt-out system and Data Protection Impact Assessment. Conclusions: Though the GDPR is the most important legal framework, national legislation execution matters most when linking cohort data with routinely collected health and education data. As national interpretation varies, legal intervention balancing individual right to informational self-determination and public good is gravely needed for health research. More harmonization across EU/EEA could be helpful but should not be detrimental in those member states which already opened a leeway for registries and research for the public good without explicit consent.

Opt-Out Design for an Observational Toxicology Study Involving Intoxicated Patients at a Dance Music Event

At electronic dance music events in Belgium in 2013 to 2015, seemingly intoxicated patients were included without their informed consent in an observational toxicology study when the attending physicians determined that they needed treatment with an intravenous line. All included patients received an information letter inviting them to contact the principal investigator (PI) to obtain more information about the study and/or to inform the PI that they wanted to be excluded from it. Overall, 238 patients were included in the study. Nine participants (4%) responded to the information letter, either on their own or through their parent; none of them asked to be excluded from the study. All respondents expressed their gratitude for the information they received. The opt-out study design seemed to be acceptable to the patient-participants, and it provided a fuller picture of the drug-related medical incidents at such music events than what could likely be achieved through a study that includes only people who explicitly choose to participate. These findings may help institutional review boards when evaluating study designs involving recreational drug use, especially at electronic dance music events. Nevertheless, we warn against extrapolation to other settings where informed consent is difficult to obtain.

Governance aspects of large-scale implementation of automated surveillance of healthcare-associated infections

OBJECTIVES

Surveillance of healthcare-associated infections (HAI) is increasingly automated by applying algorithms to routine-care data stored in electronic health records. Hitherto, initiatives have mainly been confined to single healthcare facilities and research settings, leading to heterogeneity in design. The PRAISE network - Providing a Roadmap for Automated Infection Surveillance in Europe - designed a roadmap to provide guidance on how to move automated surveillance (AS) from the research setting to large-scale implementation. Supplementary to this roadmap, we here discuss the governance aspects of automated HAI surveillance within networks, aiming to support both the coordinating centres and participating healthcare facilities as they set up governance structures and to enhance involvement of legal specialists.

METHODS

This article is based on PRAISE network discussions during two workshops. A taskforce was installed that further elaborated governance aspects for AS networks by reviewing documents and websites, consulting experts and organizing teleconferences. Finally, the article has been reviewed by an independent panel of international experts.

RESULTS

Strict governance is indispensable in surveillance networks, especially when manual decisions are replaced by algorithms and electronically stored routine-care data are reused for the purpose of surveillance. For endorsement of AS networks, governance aspects specifically related to AS networks need to be addressed. Key considerations include enabling participation and inclusion, trust in the collection, use and quality of data (including data protection), accountability and transparency.

CONCLUSIONS

This article on governance aspects can be used by coordinating centres and healthcare facilities participating in an AS network as a starting point to set up governance structures. Involvement of main stakeholders and legal specialists early in the development of an AS network is important for endorsement, inclusivity and compliance with the laws and regulations that apply.

Up-to-the-Minute Privacy Policies via Gossips in Participatory Epidemiological Studies

Researchers and researched populations are actively involved in participatory epidemiology. Such studies collect many details about an individual. Recent developments in statistical inferences can lead to sensitive information leaks from seemingly insensitive data about individuals. Typical safeguarding mechanisms are vetted by ethics committees; however, the attack models are constantly evolving. Newly discovered threats, change in applicable laws or an individual's perception can raise concerns that affect the study. Addressing these concerns is imperative to maintain trust with the researched population. We are implementing Lohpi: an infrastructure for building accountability in data processing for participatory epidemiology. We address the challenge of data-ownership by allowing institutions to host data on their managed servers while being part of Lohpi. We update data access policies using gossips. We present Lohpi as a novel architecture for research data processing and evaluate the dissemination, overhead, and fault-tolerance.

Occupational Exposure to Extremely Low-Frequency Magnetic Fields and Risk of Amyotrophic Lateral Sclerosis: Results of a Feasibility Study for a Pooled Analysis of Original Data

Previous meta-analyses have suggested an increased risk of amyotrophic lateral sclerosis (ALS) associated with occupational exposure to extremely low-frequency magnetic fields (ELF-MF). However, results should be interpreted with caution since studies were methodologically heterogeneous. Here, we assessed the feasibility of a pooling study to harmonize and re-analyze available original data. A systematic literature search was conducted. Published epidemiological studies were identified in PubMed and EMF-Portal from literature databases' inception dates until January 2019. The characteristics of all studies were described, including exposure metrics, exposure categories, and confounders. A survey among the principal investigators (PI) was carried out to assess their willingness to provide their original data. The statistical power of a pooling study was evaluated. We identified 15 articles published between 1997 and 2019. Studies differed in terms of outcome, study population, exposure assessment, and exposure metrics. Most studies assessed ELF-MF as average magnetic flux density per working day; however, exposure categories varied widely. The pattern of adjustment for confounders was heterogeneous between studies, with age, sex, and socioeconomic status being most frequent. Eight PI expressed their willingness to provide original data. A relative risk of ≥1.14 for ALS and occupational exposure to ELF-MF can be detected with a power of more than 80% in a pooled study. The pooling of original data is recommended and could contribute to a better understanding of ELF-MF in the etiology of ALS based on a large database and reduced heterogeneity due to a standardized analysis protocol with harmonized exposure metrics and exposure categories. Bioelectromagnetics. © 2021 Bioelectromagnetics Society.

Scaling Up the Surveillance of Childhood Cancer: A Global Roadmap

The World Health Organization recently launched the Global Initiative for Childhood Cancer aiming to substantially increase survival among children with cancer by 2030. The ultimate goal concerns particularly less developed countries where survival estimates are considerably lower than in high-income countries where children with cancer attain approximately 80% survival. Given the vast gap in high-quality data availability between more and less developed countries, measuring the success of the Global Initiative for Childhood Cancer will also require substantial support to childhood cancer registries to enable them to provide survival data at the population level. Based on our experience acquired at the International Agency for Research on Cancer in global cancer surveillance, we hereby review crucial aspects to consider in the development of childhood cancer registration and present our vision on how the Global Initiative for Cancer Registry Development can accelerate the measurement of the outcome of children with cancer.

Open health data: Mapping the ecosystem

BACKGROUND

Governments around the world own multiple datasets related to the policy domain of health. Datasets range from vaccination rates to the availability of health care practitioners in a region to the outcomes of certain surgeries. Health is believed to be a promising subject in the case of open government data policies. However, the specific properties of health data such as its sensibilities regarding privacy, ethics, and ownership encompass particular conditions either enabling or preventing datasets to become freely and easily accessible for everyone.

OBJECTIVE AND METHODS

This paper aims to map the ecosystem of open health data. By analyzing the foundations of health data and the commonalities of open data ecosystems via literature analysis, the socio-technical environment in which health data managed by governments are opened up or potentially stay closed is created. After its theoretical development, the open health data ecosystem is tested via a case study concerning the Data for Better Health initiative from the government of Belgium.

RESULTS

Creation and assessment of an open health data ecosystem consisting of stakeholders, interests, information policies, and data preparation activities.

CONCLUSIONS

The policy domain of health includes de-identification activities, bioethical assessments, and the specific role of data providers within its open data ecosystem. However, the concept of open data does not always fully apply to the topic of health. Such several health datasets may be findable via government portals but not directly accessible. Differentiation within types of health data and data user capacities are recommendable for future research.

Prognostic factors analysis for oral cavity cancer survival in the Netherlands and Taiwan using a privacy-preserving federated infrastructure

The difference in incidence of oral cavity cancer (OCC) between Taiwan and the Netherlands is striking. Different risk factors and treatment expertise may result in survival differences between the two countries. However due to regulatory restrictions, patient-level analyses of combined data from the Netherlands and Taiwan are infeasible. We implemented a software infrastructure for federated analyses on data from multiple organisations. We included 41,633‬ patients with single-tumour OCC between 2004 and 2016, undergoing surgery, from the Taiwan Cancer Registry and Netherlands Cancer Registry. Federated Cox Proportional Hazard was used to analyse associations between patient and tumour characteristics, country, treatment and hospital volume with survival. Five factors showed differential effects on survival of OCC patients in the Netherlands and Taiwan: age at diagnosis, stage, grade, treatment and hospital volume. The risk of death for OCC patients younger than 60 years, with advanced stage, higher grade or receiving adjuvant therapy after surgery was lower in the Netherlands than in Taiwan; but patients older than 70 years, with early stage, lower grade and receiving surgery alone in the Netherlands were at higher risk of death than those in Taiwan. The mortality risk of OCC in Taiwanese patients treated in hospitals with higher hospital volume (≥ 50 surgeries per year) was lower than in Dutch patients. We conducted analyses without exchanging patient-level information, overcoming barriers for sharing privacy sensitive information. The outcomes of patients treated in the Netherlands and Taiwan were slightly different after controlling for other prognostic factors.

Population health monitoring: an essential public health field in motion

BACKGROUND

Population health monitoring, the regular and institutionalized production and dissemination of information and knowledge about the health status of a population, is an essential element of public health. Nevertheless, while epidemiology and biostatistics, for example, are well-recognized disciplines, this does not (yet) apply to population health monitoring. Over the past decade, however, it has matured as a distinct field of expertise.

OBJECTIVES

This paper presents a comprehensive model for population health monitoring and describes its current status as a field of expertise. It concludes with an overview of the most important developments that are likely to shape the health information systems and population health monitoring practices of the future.

RESULTS AND CONCLUSIONS

Combining the information pyramid (an application of the data-information-knowledge-wisdom hierarchy), describing outputs, and a so-called monitoring chain, describing activities, results in a comprehensive model for population health monitoring. The steps of the activity chain can be viewed as a stairway by which the information pyramid is climbed, reaching evidence-informed policymaking at the top. Population health monitoring has several inherent strengths, such as its high societal relevance; its integrative, comprehensive, and structured approach; and the fact that it makes use of routinely collected data. In practice, however, secondary use of routine data is often hampered by technical, motivational, economic, political, ethical, and legal barriers. Important developments that will shape health information systems and population health monitoring practices of the future include digitalization and data-driven technology, citizen science, and the growing need for intersectoral approaches. Population health monitoring practice will need to adapt in order to counteract the risks and reap the benefits that these developments hold.

Development of a semi-structured, multifaceted, computer-aided questionnaire for outbreak investigation: e-Outbreak Platform

Aggressive tracing of contacts of confirmed cases is crucial to Taiwan's successful control of the early spread of COVID-19. As the pandemic lingers, an epidemiological investigation that can be conducted efficiently in a timely manner can help decrease the burden on the health personnel and increase the usefulness of such information in decision making. To develop a new tool that can improve the current practice of epidemiological investigation by incorporating new technologies in digital platform and knowledge graphs. To meet the various needs of the epidemiological investigation, we decided to develop an e-Outbreak Platform that provides a semi-structured, multifaceted, computer-aided questionnaire for outbreak investigation. There are three major parts of the platform: (1) a graphic portal that allows users to have an at-glance grasp of the functions provided by the platform and then choose the one they need; (2) disease-specific questionnaires that can accommodate different formats of the information, including text typing, button selection, and pull-down menu; and (3) functions to utilize the stored information, including report generation, statistical analyses, and knowledge graphs displaying contact tracing. When the number of outbreak investigation increases, the knowledge graphs can be extended to encompass other persons appearing in the same location at the same time, i.e., constituting a potential contact cluster. The information extracted can also be used to display the tracing on a map in animation. Overall, this system can provide a basis for further refinement that can be generalized to a variety of outbreak investigations.

Responsible data sharing in a big data-driven translational research platform: lessons learned

BACKGROUND

To foster responsible data sharing in health research, ethical governance complementary to the EU General Data Protection Regulation is necessary. A governance framework for Big Data-driven research platforms will at least need to consider the conditions as specified a priori for individual datasets. We aim to identify and analyze these conditions for the Innovative Medicines Initiative's (IMI) BigData@Heart platform.

METHODS

We performed a unique descriptive case study into the conditions for data sharing as specified for datasets participating in BigData@Heart. Principle investigators of 56 participating databases were contacted via e-mail with the request to send any kind of documentation that possibly specified the conditions for data sharing. Documents were qualitatively reviewed for conditions pertaining to data sharing and data access.

RESULTS

Qualitative content analysis of 55 relevant documents revealed overlap on the conditions: (1) only to share health data for scientific research, (2) in anonymized/coded form, (3) after approval from a designated review committee, and while (4) observing all appropriate measures for data security and in compliance with the applicable laws and regulations.

CONCLUSIONS

Despite considerable overlap, prespecified conditions give rise to challenges for data sharing. At the same time, these challenges inform our thinking about the design of an ethical governance framework for data sharing platforms. We urge current data sharing initiatives to concentrate on: (1) the scope of the research questions that may be addressed, (2) how to deal with varying levels of de-identification, (3) determining when and how review committees should come into play, (4) align what policies and regulations mean by "data sharing" and (5) how to deal with datasets that have no system in place for data sharing.

DNA methylation data by sequencing: experimental approaches and recommendations for tools and pipelines for data analysis

Sequencing technologies have changed not only our approaches to classical genetics, but also the field of epigenetics. Specific methods allow scientists to identify novel genome-wide epigenetic patterns of DNA methylation down to single-nucleotide resolution. DNA methylation is the most researched epigenetic mark involved in various processes in the human cell, including gene regulation and development of diseases, such as cancer. Increasing numbers of DNA methylation sequencing datasets from human genome are produced using various platforms-from methylated DNA precipitation to the whole genome bisulfite sequencing. Many of those datasets are fully accessible for repeated analyses. Sequencing experiments have become routine in laboratories around the world, while analysis of outcoming data is still a challenge among the majority of scientists, since in many cases it requires advanced computational skills. Even though various tools are being created and published, guidelines for their selection are often not clear, especially to non-bioinformaticians with limited experience in computational analyses. Separate tools are often used for individual steps in the analysis, and these can be challenging to manage and integrate. However, in some instances, tools are combined into pipelines that are capable to complete all the essential steps to achieve the result. In the case of DNA methylation sequencing analysis, the goal of such pipeline is to map sequencing reads, calculate methylation levels, and distinguish differentially methylated positions and/or regions. The objective of this review is to describe basic principles and steps in the analysis of DNA methylation sequencing data that in particular have been used for mammalian genomes, and more importantly to present and discuss the most pronounced computational pipelines that can be used to analyze such data. We aim to provide a good starting point for scientists with limited experience in computational analyses of DNA methylation and hydroxymethylation data, and recommend a few tools that are powerful, but still easy enough to use for their own data analysis.

Importancia del acceso de los registros de cáncer de base poblacional a las estadísticas vitales: barreras identificadas en Colombia

Los registros de cáncer de base poblacional (RCBP) son los responsables del reporte de incidencia, mortalidad y supervivencia de los pacientes con cáncer para sus respectivas poblaciones. Los RCBP del país son definidos por la legislación colombiana como fuentes de información de los registros nacionales de cáncer para adultos y niños, pero carecen de un soporte jurídico que permita el acceso a las fuentes oficiales de información nacional y enfrentan restricciones dadas por la ley para el tratamiento de datos personales que impide la transferencia de información de los registros nacionales de cáncer y todas sus fuentes hacia los RCBP. Se analizarán los problemas de acceso a la información de estadísticas vitales del país, así como las consecuencias de estas barreras de acceso para los RCBP, y se presentarán argumentos que sustenten la necesidad de que los RCBP puedan acceder a la información necesaria para poder cumplir su objetivo.

Early detection and prevention

The rapidly increasing incidence and mortality of cancer calls for a focused effort to increase the effect of cancer‐prevention efforts. In the area of early detection, there are major differences in the preventive impact of implemented screening policies, even when solid, evidence‐based international recommendations are issued. Studies are needed to determine why evidence‐based interventions are not used and to investigate why effects are less than predicted by solid research on the subject. Currently, population‐based screening is recommended only for three forms of cancer (cervical, breast and colorectal cancer) but, given the increasing cancer burden, efforts are required to facilitate the discovery of new biomarkers for screening, as well as the identification of barriers to implementation of new cancer screening discoveries. The creation of a network of excellence in research on Cancer Prevention (Cancer Prevention Europe) is likely to significantly contribute to progress in these areas. In the present review, some possible strategies to ensure progress are discussed, with specific examples from the cervical cancer screening area.