Registry & Real-World Data Digest — Issue 03

IJsbrand den Rooijen, Giacomo Capone, Jacobus van Wyk, et al.

Summary: A January 2024 workshop held under the European Union's Accelerating Clinical Trials (ACT EU) initiative examined nearly 55,000 clinical trials recorded in European registries and asked how that data could be put to better use. The workshop identified three main opportunities: using historical registry records to design better future trials, making trials more focused on what patients need, and helping regulators and policymakers evaluate evidence more reliably. The authors also identified four things that need to happen before any of that is possible — standardizing how data are recorded, improving data quality, making different registries able to communicate with each other, and increasing transparency. One early, concrete output is a patient-facing tool called the ACT EU trial map, developed by the European Medicines Agency to help patients find relevant trials.

Why it matters: Clinical trial registries hold a large amount of information that is rarely used once a trial ends. If that data were made consistent and connected across registries, researchers could avoid designing trials that duplicate work already done, identify where evidence is missing, and help regulators make decisions more quickly. For people with rare conditions — where the number of patients in any single study is small — the ability to combine and compare records across many trials could be especially valuable.

What to keep in mind: This article reports the conclusions of a workshop discussion, not the results of a research study, so its ideas have not been tested against real-world outcomes. The four improvements the authors call for — standardization, quality, interoperability, and transparency — are widely recognized as the right goals, but they are also long-standing obstacles that have been difficult to achieve across different countries, institutions, and regulatory bodies. The patient-facing trial map is a useful first step, but a searchable tool for patients is a modest beginning relative to the full vision described. Whether the ACT EU initiative can turn these workshop conclusions into lasting infrastructure change remains an open question.

Relevance: Patient Registries | Real-World Data | Data Standards | Interoperability | Regulatory Science

Source: https://pubmed.ncbi.nlm.nih.gov/42881013/

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Ashley Jaksa

Summary: A published editorial in Value in Health makes a pointed argument: the field of real-world evidence has produced so many overlapping guidance documents — from regulators, health technology assessment bodies, and professional societies — that researchers now spend considerable effort comparing frameworks rather than generating evidence. The author contends that the core principles these documents contain are already broadly consistent across major bodies such as the US Food and Drug Administration and the European Medicines Agency. Instead of issuing more high-level guidance, the author proposes two practical steps: bringing existing standards into better alignment globally, and building a publicly available, annotated collection of real-world evidence case studies that shows how decisions were actually made and why.

Why it matters: For researchers working with patient registries or health records data, navigating competing guidance documents is a real drain on time and resources — without necessarily making the resulting research any better. Regulatory and reimbursement decisions about treatments often depend on reasoning that is never made fully explicit in formal guidance. A collection of clearly explained, real-world examples of how evidence was evaluated would help researchers understand what decision-makers actually expect, reducing uncertainty and inconsistency. For rare diseases, where small datasets and limited studies are the norm, clearer and more consistent evidentiary standards could be especially important.

What to keep in mind: This is an editorial — a professional opinion piece — rather than a research study, so it does not present new data. The author's observation that core principles already converge across major regulators is important if accurate, but it is not independently verified here. The two proposed solutions are reasonable in principle but difficult to deliver in practice. Aligning guidance across agencies in different countries with different legal frameworks requires sustained commitment that the editorial does not map out in detail. The value of an annotated case repository depends entirely on how willing decision-makers are to explain their reasoning openly — something that has historically been limited. Readers should treat this as a well-grounded call for change rather than a proven path forward.

Relevance: Real-World Evidence | Regulatory Science | Data Standards | Observational Research

Source: https://pubmed.ncbi.nlm.nih.gov/42562111/

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Seyyedeh Fatemeh Mousavi Baigi, Seyyed Mohammad Tabatabaei, Abbas Sheikhtaheri, et al.

Summary: A registered systematic review — a study that methodically searches and synthesizes existing research — analyzed 119 studies examining how data quality in health registries is defined, measured, and improved, with particular attention to artificial intelligence and machine learning approaches. The review found that most quality assessments focus on whether records are complete and accurate, while largely ignoring whether the people in a registry are representative of the broader patient population. Traditional rule-based checks and audits remain the most common quality tools. AI and machine learning applications are growing — particularly for spotting unusual entries and linking records across datasets — but they are still selective and face real barriers related to how systems connect with each other and how data are structured.

Why it matters: Registries are increasingly used to support regulatory decisions and to generate the kind of real-world evidence that influences treatment guidelines and market approvals. If the data in those registries are incomplete or unrepresentative, the conclusions drawn from them can be quietly distorted. The finding that representativeness — whether a registry genuinely reflects the full range of patients with a condition — is rarely assessed is important: a registry that captures mainly patients treated at specialist centers, for example, may paint a misleading picture of how a treatment works in ordinary clinical practice.

What to keep in mind: Systematic reviews inherit the limitations of the studies they include. The 119 studies analyzed here use varying definitions of data quality and inconsistent reporting standards, making it difficult to draw firm general conclusions. The review's finding that AI tools are underused is credible, but it also reflects a practical reality: automating fuzzy quality judgments — such as whether a clinical note makes sense in context — is much harder than automating clearly defined tasks. The authors' call for quality processes that are built into registry operations from the start, rather than applied after the fact, is directionally sound but not yet backed by evidence showing that this approach delivers better outcomes in practice.

Relevance: Patient Registries | Real-World Data | Data Quality | Clinical Informatics

Source: https://pubmed.ncbi.nlm.nih.gov/42813616/

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J Marin-Corral, N Iglesias, S Menke, et al.

Summary: This article describes a system called the Savana Next-Generation Registry (SNGR), which is designed to build research-ready datasets by reading and extracting information from the free-text portions of electronic health records — clinical notes, discharge summaries, pathology reports — using a technology called natural language processing (NLP). NLP software reads text the way a human would, identifying medically relevant information and converting it into structured data that can be analyzed. The system covers multiple languages, incorporates review by medical experts, and is designed to meet European data protection and regulatory requirements. The platform has been used in more than 65 real-world research projects and has contributed to over 30 published studies, primarily in cancer care.

Why it matters: A large share of the clinically meaningful information recorded during patient care lives in free-text notes rather than in the standardized fields that most research databases rely on. Systems that can reliably extract that information could make registry and research datasets far richer and more complete — particularly for complex conditions where a patient's full story is rarely captured in a few checkboxes. In cancer care, for instance, how a tumor is staged, what treatments were given, and how the patient responded are often described in narrative notes rather than coded fields.

What to keep in mind: This article describes the platform and its intended capabilities rather than reporting the results of a rigorous independent evaluation. The authors do not provide systematic data on how often the NLP system correctly identifies and extracts key clinical variables — measures such as accuracy and completeness across different languages, institutions, and record types. The number of publications and use cases is cited as evidence of the platform's usefulness, but publication volume reflects adoption rather than verified accuracy. Readers should view this as a credible description of a functioning system with real-world deployment, while recognizing that independent, standardized testing of extraction accuracy across varied clinical settings remains an important gap that the article does not fill.

Relevance: Real-World Data | Real-World Evidence | Clinical Informatics | Data Quality | Interoperability

Source: https://pubmed.ncbi.nlm.nih.gov/42830900/

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V Zadnik, A Duratović Konjević, M Jurtela, et al.

Summary: A large survey conducted in early 2026, as part of an EU initiative called CancerWatch, mapped 175 population-based cancer registries across 45 European countries. The survey — the most comprehensive of its kind — asked registries about their geographic coverage, how quickly they make data available, their digital infrastructure, and how prepared they are to contribute to the EU's new European Health Data Space (EHDS), a framework designed to make health data more accessible and interoperable across Europe. Key findings: cancer data reaches researchers within two years in only 69% of countries; digital systems vary widely in sophistication; and roughly one in three registries reported little or no awareness of what the EHDS will require of them.

Why it matters: Population-based registries — which aim to record every new cancer diagnosis within a defined geographic area — are a cornerstone of public health surveillance and a growing source of real-world data for research and policy. Knowing where these registries fall short in timeliness, digital capacity, and readiness for new European data standards is a necessary first step toward systematic improvement. For rare cancers and rare diseases generally, where meaningful research requires combining records from many countries, these gaps are particularly consequential: incomplete or poorly connected registries make it harder to assemble the large datasets needed to study conditions that affect relatively few people.

What to keep in mind: The survey's 91% response rate is a genuine strength and lends credibility to the overall picture it paints. However, the findings are based on self-reported answers from registry staff, which means that assessments of digital maturity and EHDS awareness reflect how registries perceive themselves rather than independently verified facts. With a 700-item questionnaire, there is also a real possibility that some respondents interpreted questions differently or experienced fatigue that affected the consistency of their answers. The authors are appropriately cautious in their conclusions and call for coordinated investment rather than overstating what the survey can prove. The directional findings — fragmented data exchange, delays in data availability, uneven readiness for new European standards — are consistent with long-standing observations about European health data infrastructure and are plausible even accounting for the survey's limitations.

Relevance: Patient Registries | Real-World Data | Data Standards | Interoperability | Data Governance

Source: https://pubmed.ncbi.nlm.nih.gov/42830857/

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Taryn Bessen, Stephen McDonald

Summary: This commentary argues that clinical quality registries — which collect safety and performance data and produce reports comparing how different clinical units or providers are doing — frequently fail to drive improvement beyond the individual teams or departments that use them. The authors identify organisational infrastructure they consider essential for registry data to influence decisions at the health-system or policy level, including governance structures, leadership engagement, and clear accountability for acting on what registry reports show.

Why it matters: Substantial resources go into building and maintaining clinical quality registries. If the information they generate remains confined to the clinical team that submitted it — without reaching the executives, governance bodies, or policymakers who have authority to make system-wide changes — much of that investment goes to waste. The problem is familiar in healthcare: data are collected, reports are produced, and then little changes because the people who could act on the findings are not receiving the information in a form they can use, or do not have a clear mandate to respond.

What to keep in mind: This is an opinion and framework piece, not a research study, so the authors' proposals cannot be evaluated the same way empirical findings would be. The core argument — that registry data need to be embedded in organisational decision-making to drive real change — is plausible and consistent with broader thinking about quality improvement, but the article does not present comparative evidence that health services with the recommended infrastructure actually perform better than those without it. One practical complication worth noting: when the number of patients at any given unit is small — as is common in rare disease care — comparing units statistically becomes unreliable, which can undermine the benchmarking that the authors champion. This is a well-reasoned contribution that identifies a genuine and underaddressed gap, but it would benefit from supporting evidence, even in the form of detailed case studies, to move beyond advocacy.

Relevance: Patient Registries | Real-World Evidence | Data Governance | Outcomes Research

Source: https://pubmed.ncbi.nlm.nih.gov/42888857/

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