Category Archives: Data sharing

Final Rule for Clinical Trial Data Reporting Published

Clinical trials, Data sharing, Research reporting standards, , , ,

On Friday of last week, the US Department of Health and Human Services published a long-awaited final rule (PDF) that governs the registration and data reporting for clinical trials with ClinicalTrials.gov. The final rule and an accompanying complementary policy issued by the National Institutes of Health (NIH) represents the formal codification and clarification of requirements first described in Section 801 of the 2007 Food and Drug Administration Amendments Act (FDAAA). These requirements oblige research sponsors or other responsible parties to register most kinds of clinical trials with an accepted, publicly available registry (such as ClinicalTrials.gov) and to report certain key data about the trial design, study population, and outcomes.

However, despite the enactment of FDAAA in 2008, compliance with many of its requirements has generally been poor, as both scholarly investigations and media reports have documented. Although registration of trials has improved during this interval, possibly due to many scientific journals refusing to publish reports from unregistered studies, basic summary data (including information about adverse events) from many clinical trials have gone unreported in the ClinicalTrials.gov registry, with academic researchers being among the worst offenders for late reporting or failure to report. In addition, although Section 801 of FDAAA includes penalties for not meeting reporting obligations, no enforcement actions have yet been taken.

The final rule, which goes into effect in January of 2017, clarifies reporting requirements and responsibilities, provides checklists for research sponsors, establishes penalties for failing to fulfill reporting obligations in a timely fashion, and obligates sponsors to furnish the full research protocol to ClincalTrials.gov. Importantly, the HHS rules and NIH policy also articulate new standards for gathering and reporting data about the race and ethnicity of trial participants—information that has often been lacking from many trials datasets.

For further details:

NIH news release summarizing new reporting requirements

National Public Radio web article and audio segment on the final rule (Francis Collins [NIH], Robert Califf [FDA], and Monique Anderson [Duke Clinical Research Institute] interviewed)

Summary of Final Rule in New England Journal of Medicine

ClinicalTrials.gov summary on Final Rule/NIH Policy

NIH Policy on Funding Opportunity Announcements for Clinical Trials

NIH Policy on Good Clinical Practice Training for NIH Awardees

 

FDA releases draft guidance for using electronic health records in clinical research

Data privacy, Data quality, Data sharing, Data standards, Electronic health records, Policy, Regulatory issues, ,

The FDA has released a Draft Guidance for Industry to facilitate the use of data from electronic health record (EHRs) in clinical investigations. The draft guidance provides recommendations on how to use EHRs as a source of data for research, ensure data quality and integrity, and satisfy the FDA’s inspection, recordkeeping, and record retention requirements. An additional goal of the draft guidance is to promote interoperability, or the ability to exchange and use information between EHR systems that capture information during patient care visits and electronic data capture (EDC) systems that support clinical investigations. Sponsors of clinical research must also consider whether there are any reasonably foreseeable risks involved in using the EHR for research—such as an increased risk of data breaches—that should be disclosed in the informed consent document.

Read the full draft guidance here.

FDA Cites Collaboratory as Part of a National System for Generating Clinical Evidence

Clinical trials, Comparative Effectiveness Research, Data sharing, Data standards, Pragmatic clinical trials, , , , , , ,

In a recent post on the FDA’s “FDA Voice” blog, Associate Deputy Commissioner Rachel Sherman and Commissioner Robert Califf describe how to overcome barriers to data sharing and create a successful national system for medical evidence generation (or “EvGen”). To foster new approaches for creating clinical evidence the authors suggest 3 principles:

“1. There must be a common approach to how data is presented, reported and analyzed and strict methods for ensuring patient privacy and data security.

2. Rules of engagement must be transparent and developed through a process that builds consensus across the relevant ecosystem and its stakeholders.

3. To ensure support across a diverse ecosystem that often includes competing priorities and incentives, the system’s output must be intended for the public good and be readily accessible to all stakeholders.”

Drs. Sherman and Califf point to substantial pioneering work being done in secondary use of data, in which data collected for clinical care are “secondarily” used for research, including projects currently underway through the NIH Collaboratory, PCORnet, and other initiatives and networks. The experience gained from these groundbreaking efforts should provide a foundation for a national system for evidence generation.

Read the full post here.

Journal Editors Propose New Requirements for Data Sharing

Data sharing, Research reporting standards, Writing and Publishing,

On January 20, 2016, the International Committee of Medical Journal Editors (ICMJE) published an editorial in 14 major medical journals in which they propose that clinical researchers must agree to share the deidentified data set used to generate results (including tables, figures, and appendices or supplementary material) as a condition of publication in one of their member journals no later that six months after publication. By changing the requirements for manuscripts they will consider for publication, they aim to ensure reproducibility (independent confirmation of results), foster data sharing, and enhance transparency. To meet the new requirements, authors will need to include a plan for data sharing as a component of clinical trial registration that includes where the data will be stored and a mechanism for sharing the data.

Evolving Standards for Data Reporting and Sharing

As early as 2003, the National Institutes of Health published a data sharing policy for research funded through the agency, stipulating that “Data should be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.” Under this policy, federally funded studies receiving over $500,000 per year were required to have a data sharing plan that describes how data will be shared, that shared data be available in a usable form for some extended period of time, and that the least restrictive method for sharing of research data is used.

In 2007, Congress enacted the Food and Drug Administration Amendments Act. Section 801 of the Act requires study sponsors to report certain kinds of clinical trial data within a specified interval to the ClinicalTrials.gov registry, where it is made available to the public. Importantly, this requirement applied to any study classified as an “applicable clinical trial” (typically, an interventional clinical trial), regardless of whether it was conducted with NIH or other federal funding or supported by industry or academic funding. However, recent academic and journalistic investigations have demonstrated that overall compliance with FDAAA requirements is relatively poor.

In 2015, the Institute of Medicine (now the National Academy of Medicine) published a report that advocates for responsible sharing of clinical trial data to strengthen the evidence base, allow for replication of findings, and enable additional analyses. In addition, these efforts are being complemented by ongoing initiatives aimed at widening access to clinical trial data and improving results reporting, including the Yale University Open Data Access project (YODA), the joint Duke Clinical Research Institute/Bristol-Myers Squibb Supporting Open Access to clinical trials data for Researchers initiative (SOAR), and the international AllTrials project.

Responses to the Draft ICMJE Policy

The ICMJE recommendations are appearing in the midst of a growing focus on issues relating to the integrity of clinical research, including reproducibility of results, transparent and timely reporting of trial results, and facilitating widespread data sharing, and the release of the draft policy is amplifying ongoing national and international conversations taking place on social media and in prominent journals. Although many researchers and patient advocates have hailed the policy as timely and needed, others have expressed concerns, including questions about implementation and possible unforeseen consequences.

The ICMJE is welcoming feedback from the public regarding the draft policy at www.icmje.org and will continue to collect comments through April 18, 2016.

Resources

Journal editors publish editorial in 14 major medical journals stipulating that clinical researchers must agree to share a deidentified data set: Sharing clinical trial data: A proposal from the International Committee of Medical Journal Editors (Annals of Internal Medicine version). January 20, 2016.

A New England Journal of Medicine editorial in which deputy editor Dan Longo and editor-in-chief Jeffrey Drazen discuss details of the ICJME proposal: Data sharing. January 21, 2016.

A follow-up editorial in the New England Journal of Medicine by Jeffrey Drazen: Data sharing and the Journal. January 25, 2016.

Editorial in the British Medical Journal: Researchers must share data to ensure publication in top journals. January 22, 2016.

Commentary in Nature from Stephan Lewandowsky and Dorothy Bishop: Research integrity: Don’t let transparency damage science. January 25, 2016.

National Public Radio interview on Morning Edition: Journal editors to researchers: Show everyone your clinical data with Harlan Krumholz. January 27, 2016.

Institute of Medicine (now the National Academy of Medicine) report advocating for responsible sharing of clinical trial data: Sharing clinical trial data: maximizing benefits, minimizing risk. National Academies Press, 2015.

Rethinking Clinical Trials Living Textbook Chapter, Acquiring and using electronic health record data, which describes the use of data collected in clinical practice for research and the complexities involved in sharing data. November 3, 2015.

NIH Health Care Systems Research Collaboratory data sharing policy. June 23, 2014.

Commentary from Richard Platt and Joakim Ramsberg in New England Journal of Medicine on challenges of data sharing from healthcare systems research. April 20, 2016.

List of International Committee of Medical Journal Editors (ICMJE) member journals.

New Living Textbook Chapter on Acquiring and Using Electronic Health Record Data for Research

Data quality, Data sharing, Data standards, Electronic health records, Pragmatic clinical trials, , , ,

Topic ChaptersMeredith Nahm Zozus and colleagues from the NIH Collaboratory’s Phenotypes, Data Standards, and Data Quality Core have published a new Living Textbook chapter about key considerations for secondary use of electronic health record (EHR) data for clinical research.

In contrast to traditional randomized controlled clinical trials where data are prospectively collected, many pragmatic clinical trials use data that were primarily collected for clinical purposes and are secondarily used for research. The chapter describes the steps a prospective researcher will take to acquire and use EHR data:

  • Gain permission to use the data. When a prospective researcher wishes to use data, a data use agreement (DUA) is usually required that describes the purpose of the research and the proposed use of the data. This section also describes use of de-identified data and limited data sets.
  • Understand fundamental differences in context. Data collected in routine care settings reflect standard procedures at an individual’s healthcare facility, and are not collected in a standard, structured manner.
  • Assess the availability of health record data. Few assumptions can be made about what is available from an organization’s healthcare records; up-front, detailed discussions about data element collection over time at each facility is required.
  • Understand the available data. A secondary data user must understand both the data meaning and the data quality; both can vary greatly across organizations and affect a study’s ability to support research conclusions.
  • Identify populations and outcomes of interest. Because healthcare facilities are obligated to provide only the minimum necessary data to answer a research question, investigators must identify the needed patients and data elements with specificity and sensitivity to answer the research question given the available data.
  • Consider record linkage. Studies using data from multiple records and sources will require matching data to ensure they refer to the correct patient.
  • Manage the data. The investigator is responsible for receiving, managing, and processing data and must demonstrate that the data are reproducible and support research conclusions.
  • Archive and share the data after the study. Data may be archived and shared to ensure reproducibility, enable auditing for quality assurance and regulatory compliance, or to answer other questions about the research.

In Nature: The Precision Medicine Initiative & DNA Data Sharing

Data privacy, Data sharing, Electronic health records, Genomics, Patient engagement, , , , ,

A recent article in Nature highlights the Precision Medicine Initiative, launched in January 2015 and spearheaded by the National Institutes of Health. Precision medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. This initiative will involve collection of data on genomes, electronic health records, and physiological measurements from 1 million participants. A main objective is for participants to be active partners in research.

But a major decision faced by the initiative’s working group is how much information to share with participants about disease risk, particularly genetic data. Though there is much debate in the field, the article suggests that public opinion on data sharing may be shifting toward openness.

The Precision Medicine Initiative working group will be releasing a plan soon. For details on the goals of the Precision Medicine Initiative, read the perspective by NIH Director Dr. Francis Collins in the New England Journal of Medicine.

 

Task Force Releases Recommendations for National Medical Device Evaluation System

Data sharing, Electronic health records, Health outcomes, , , , ,

A new report (PDF) containing recommendations for the creation of a national registry system for evaluating and monitoring medical devices has been released for public comment today. The report, a joint project of the Medical Device Registry Task Force and cover_19aug2015 the Medical Device Epidemiology Network (MDEpiNet), is available on boh the US Food and Drug Administration (FDA) website and on  the MDEpiNet website.

The report reflects the results of a year-long effort, prompted by the FDA’s Center for Devices and Radiological Health (CDER), that  is focused on fostering a national system for monitoring the use of medical devices in the “real-world” setting of patient care, once the devices have been approved for the market (known as “postmarket surveillance”).

The term “medical devices” encompasses a wide range of technologies, including implantable pacemakers, cardiovascular stents, robotic surgical devices, and artificial joint replacements, among many others. At present, information about the use of these devices in routine care settings, including safety issues reported by doctors and patients, is collected in a variety of registries and health record systems. A  networked national system, such as the one described in the task force report, would be able to unite and build upon both existing and novel data resources, thereby improving safety monitoring and accelerating the development of new devices:

“Task Force recommendations for [Coordinated Registry Network] CRN architecture, and thus for the National System, center on leveraging existing, self sustaining electronic resources, such as device registries, electronic health records, administrative data and even social media and personal mobile device sources.”

The Task Force Report offers recommendation in several key areas, including:

  • Establishing a national dialog about medical device evaluation that includes all stakeholders;
  • Leveraging existing efforts in the arena of device registries and electronic data systems;
  • Describing the desired characteristics of a national Coordinated Registry Network (CRN) for medical devices;
  • Outlining priorities for developing and refining medical devices in multiple therapeutic areas;
  • Identifying and improving methods for analyzing data on medical devices; and
  • Addressing network governance and issues related to patient privacy and informed consent.

Each of these key areas also features suggested pilot projects designed to inform ongoing efforts.

A related perspective article summarizing the National Registry System project has also been published online in the Journal of the American Medical Association.

Related Links

ClinicalTrials.gov Analysis Dataset Available from CTTI

Clinical trials, Data quality, Data sharing, Policy, Regulatory issues, Research reporting standards, Research tools, , , ,

Tools for ResearchAs part of a project that examined the degree to which sponsors of clinical research are complying with federal requirements for the reporting of clinical trial results, the Clinical Trials Transformation Initiative (CTTI) and the authors of the study are making the primary dataset used in the analysis available to the public. The full analysis dataset, study variables, and data definitions are available as Excel worksheets from the CTTI website and on the Living Textbook’s Tools for Research page.

Study Examines Public Attitudes Toward Data-Sharing Networks

Data sharing, Learning health systems, , , , , , ,

A new study examining public attitudes about the sharing of personal medical data through health information exchanges and  distributed research networks finds a mixture of receptiveness and concerns about privacy and security. The study, conducted by researchers from the University of California, Davis and University of California, San Diego and published online in the Journal of the American Medical Informatics Association (JAMIA), reports results from a telephone survey of 800 California residents. Participants were asked for their opinions about the importance of sharing personal health data for research purposes and their feelings about related issues of security and privacy, as well as the importance of notification and permission for such sharing.

The authors found that a majority of respondents felt that sharing health data would “greatly improve” the quality of medical care and research. Further, many either somewhat or strongly agreed that the potential benefits of sharing data for research and care improvement outweighed privacy considerations (50.8%) or the right to control the use of their personal information (69.8%), although study participants also indicated that transparency regarding the purpose of any data sharing and controlling access to data remained important considerations.

However, the study’s investigators also found evidence of widespread concern over privacy and security issues, with substantial proportions of respondents reporting a belief that data sharing would have negative effects on the security (42.5%) and privacy (40.3%) of their health data. The study also explored attitudes about the need to obtain permission for sharing health data, as well as whether attitudes toward sharing data differed according to the purpose (e.g., for research vs. care) and the groups or individuals among which the data were being shared.

The authors note that while data-sharing networks are increasingly viewed as a crucial tool for enabling research and improving care on a national scale, they ultimately rely upon trust and acceptance from patients. As such, the long-term success of efforts aimed at building effective data-sharing networks may depend on accurately understanding the views of patients and accommodating their concerns.

Read the full article here: 

Kim KK, Joseph JG, Ohno-Machado L. Comparison of consumers' views on electronic data sharing for healthcare and research. J Am Med Inform Assoc. 2015 Mar 30. pii: ocv014. doi: 10.1093/jamia/ocv014. [Epub ahead of print]

NIH Finalizes Policy on Genomic Data Sharing

Data sharing, Informed Consent, Policy, , , , , , ,

The National Institutes of Health has issued a final NIH Genomic Data Sharing (GDS) policy to promote data sharing as a way to speed the translation of data into knowledge, products, and procedures that improve health while protecting the privacy of research participants. The NIH news release contains highlights of the policy.

The GDS policy is an extension of and replaces the Genome-Wide Association Studies (GWAS) data sharing policy. A key tenet of the policy is the expectation that researchers obtain the informed consent of study participants for the potential future use of their de-identified data for research and for broad sharing. NIH has similar expectations for studies that involve the use of de-identified cell lines or clinical specimens.

NIH officials finalized the GDS policy after reviewing public comments on a draft released September 2013. Starting January 25, 2015, the policy will apply to all NIH-funded, large-scale human and non-human projects that generate genomic data. This includes research conducted with the support of NIH grants and contracts and within the NIH Intramural Research Program. A report from members of the NIH Genomic Data Sharing policy team appears in the August 27, 2014, advance online issue of Nature Genetics.