February 28, 2018: New Meeting Summary Examines How to Integrate Patient‐Reported Health Data for Pragmatic Research

A recently released summary from the ADAPTABLE Roundtable Meeting explores ways to better understand the sets of circumstances and considerations that could guide when and how to gather and integrate patient-reported health data with other data sources in pragmatic trials.

For outcomes that represent subjective experiences, such as pain, symptoms, and physical functioning, the patient is the unique and privileged source of information. Other patient-reported health data may not have a clear source of truth, such as co-morbidities and hospitalizations. In such cases, patient-reported health data may supplement, contradict, or agree with EHR and claims data. For example, medication data reported by patients might be a more accurate reflection of what patients are actually taking than medication data in the EHR, especially for over-the-counter medications.

Patient-reported health data come from various sources and can be feasibly collected in the conduct of a pragmatic clinical trial, but the optimal approaches for capturing and analyzing these data are unclear. Questions include how to integrate this information with other data collected as part of a study, including data from the EHR.

To better understand patient-reported health data and how to use them in pragmatic trials, 18 experts from 8 institutions convened at the roundtable meeting, coming from a wide variety of backgrounds including biostatistics, epidemiology, oncology, nursing, psychiatry, health policy, and regulation. Representatives from the NIH Collaboratory included Drs. Lesley Curtis and Rachel Richesson from the EHR Core and Dr. Kevin Weinfurt from the Patient-Reported Outcomes Core.

In addition to the meeting summary, two white papers are forthcoming. For more information about using patient-reported data in pragmatic trials, see the Living Textbook Chapter on Endpoints and Outcomes.

This effort was funded by Office of the Assistant Secretary for Planning and Evaluation at the U.S. Department of Health and Human Services through a supplement provided to the NIH Collaboratory Coordinating Center.

October 10, 2017: NIH Collaboratory Core Working Group Interviews: Reflections from the Phenotypes, Data Standards, and Data Quality Core

At the NIH Collaboratory Steering Committee meeting in May 2017, we asked Drs. Rachel Richesson and W. Ed Hammond, Co-chairs of the Phenotypes, Data Standards, and Data Quality Core, to reflect on the first 5 years of their Core’s work and the challenges ahead.

Both were pleased with how the Core was able to provide guidelines for assessing data quality and the reporting of pragmatic trials, especially around issues with phenotypes and the use of electronic health record data. Future work in this area needs to advance the development of regulations and standards for the collection of clinical data to support learning healthcare systems.

“We’ve built a community in our Core that represents a diverse group of scientists and clinicians showing the many ways to look at data challenges.”
– Dr. Rachel Richesson

In Fall 2017, the Phenotypes, Data Standards, and Data Quality Core merged with the Electronic Health Records Core. The combined Core will continue to work on data standards and quality, and approaches to define clinical phenotypes and endpoints, extract information, and discover errors in data from healthcare systems.

Download the interview (PDF).

A PDF of the May 2017 interview with leaders of the Phenotypes Core Working Group.

New Lessons Learned Document Draws on Experiences of Demonstration Projects

The NIH Collaboratory’s Health Care Systems Interactions Core has published a document entitled Lessons Learned from the NIH Health Care Systems Research Collaboratory Demonstration Projects. The Principal Investigators of each of the Demonstration Projects shared their trial-specific experience with the Core to develop the document, which presents problems and solutions for initiation and implementation of pragmatic clinical trials (PCTs). Lessons learned are divided into the following categories: build partnerships, define clinically important questions, assess feasibility, involve stakeholders in study design, consider institutional review board and regulatory issues, and assess potential issues with biostatistics and the analytic plan.

Other tools available from the Health Care Systems Interactions Core include a guidance document entitled Considerations for Training Front-Line Staff and Clinicians on Pragmatic Clinical Trial Procedures and an introduction to PCTs slide set.

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

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.

New Research Tool: Using the RxNorm System

Tools for ResearchA new research tool available on the Living Textbook provides an overview of RxNorm and explores the application of some of its associated tools in the research setting. RxNorm is a free, publicly available resource from the National Library of Medicine that provides “normalized” names and unique identifiers that make it possible to clearly identify a given drug. This allows information about medications to be exchanged across electronic health records (EHRs). In fact, the Office of the National Coordinator designated use of RxNorm as a criterion for EHR certification of interoperability and Stage 2 Meaningful Use.

The explanatory resource was developed by Michelle Smerek of the NIH Collaboratory’s Phenotypes, Data Standards, and Data Quality Core. Feedback is encouraged to help expand this tool.

In Nature: The Precision Medicine Initiative & DNA Data Sharing

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

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

PCORnet Posts Aspirin Study Protocol for Public Review and Comment

PCORnetThe National Patient-Centered Clinical Research Network (PCORnet) has recently made a draft protocol for its first randomized clinical trial available for stakeholder review. Researchers, clinicians, patients and the public are all invited to read the current draft of the study protocol and provide comments and feedback.

The ADAPTABLE Study (PDF), which will investigate whether lower- or higher-dose aspirin is better for preventing heart attack and stroke in patients at risk for heart disease, is PCORnet’s first randomized pragmatic clinical trial. Designed to leverage PCORnet’s Clinical Data Research Networks (CDRNs) and Patient-Powered Research Networks (PPRNs), the trial will serve as twofold purpose: answering a clinical question of direct importance for patients, families, and healthcare providers, and serving as a demonstration of PCORnet’s capabilities in conducting clinical research on a national scale.

Links to the proposed study protocol, a survey tool for capturing feedback, and other information about ADAPTABLE Study, including press releases, fact sheets, and infographics, are available at the link below:

ADAPTABLE: The Aspirin Study

Follow PCORnet on Twitter @PCORnetwork for updates on the ADAPTABLE #ClinicalTrial

In the News: Increase in Use of Personal Health Data

An explosion in the collection of personal data is fostering concerns about the extent to which health information is accessed—and about the privacy and confidentiality of this information. Two recent National Public Radio stories highlight a few of the burgeoning uses of these abundant data.

In the first, an insurer uses personal data to predict who will get sick so it can identify patients at highest risk for hospital admission, or readmission, and then provide them with personal health coaches. The coordinated care given to patients by the coaches (for example, arranging a visiting nurse or streamlining appointments) has been shown to improve hospitalization rates. The insurer says it follows federal health privacy guidelines for anonymity and uses the information to better serve its members.

The second story explains that results of online health searches aren’t always confidential, and data brokers are tracking information and selling it to interested parties. The author notes that data gathered on the Web are, for the most part, unregulated. Both stories raise questions about privacy and confidentiality of health information and how to best protect it.

Pragmatic clinical trials also seek to use personal health data to answer important questions on the risks, benefits, and burdens of therapeutic interventions. In a blog post in Health Affairs, Joe Selby, executive director of the Patient-Centered Outcomes Research Institute (PCORI), underscores the need for trust, support, and active engagement of patients when involving them in health data research, even with privacy protections in place. PCORI has launched the National Patient-Centered Clinical Research Network (PCORnet) as a means of harnessing large clinical data sets to study the comparative effectiveness of treatments, and a central tenet of the network is that patients, clinicians, and healthcare systems should be actively involved in the governance of the use of health information.

Read the full articles

From NPR: Insurer Uses Personal Data To Predict Who Will Get Sick
From NPR: Online Health Searches Aren't Always Confidential
From Health Affairs: Advancing the Use of Health Data in Research With PCORnet


Latest Truven Health Analytics–NPR Health Poll on Medical Data Privacy

How concerned are people about the privacy of their medical information? Not very—according to the November 2014 Truven Health Analytics–NPR Health Poll (opens as PDF). The poll asked how respondents feel about sharing their electronic health information and other data with researchers, employers, health plans, and their doctors. The majority expressed a willingness to share their anonymized health information with researchers; less than a quarter expressed willingness to share non-healthcare data with their healthcare providers.

Each month, the Truven Health Analytics–NPR Health Poll surveys approximately 3,000 Americans to gauge attitudes and opinions on a wide range of healthcare issues. Poll results are reported by NPR on the health blog Shots. Among the results of this survey:

  • 74% of respondents indicated that their physician uses an electronic medical record system.
  • 68% of respondents would share their health information anonymously with researchers.
  • 44% of respondents have looked through their health information kept by their physician.

The survey analyses were stratified by age, education, generation, and income. Poll questions were posed by cell phone, land line, and online during the first half of August 2014. The margin of error was plus or minus 1.8 percentage points. An executive summary of the survey, including questions and survey data, is here.