Category Archives: Electronic health records

Use of Data from Electronic Health Records to Customize Medical Treatments

Data analysis, Data quality, Electronic health records, ,

In a recent segment on NPR’s Morning Edition, commentators discuss the potential of using electronic health records to customize medical treatments.

Dr. Harlan Krumholz, a professor of medicine at Yale University, says comparing data in electronic health records with genomic information holds great promise for customizing individual treatments, but he warns that the quality of data collected in the medical record is not research quality. While researchers are making a positive start with initiatives such as the Precision Medicine Initiative (re-branded as the All of Us research program), medicine still has a long way to go to fully realize the potential of these data.

Dr. Harlan Krumholz will be presenting at an upcoming NIH Collaboratory Grand Rounds on January 13 from 1:00 – 2:00 p.m. ET. “What’s Next: People-Powered Knowledge Generation from Digital Health Data.” Join the meeting here.

The full article and audio can be found on NPR Shots, an online channel for health stories from the NPR Science Desk.

New NIH Collaboratory resource for the transparent reporting of PCTs

Cluster Randomized Trials, Data quality, Electronic health records, Research reporting standards, Research tools, Writing and Publishing, , , ,

The NIH Collaboratory has developed a tool to assist authors in the complete and transparent reporting of their pragmatic clinical trials (PCTs). In the PCT Reporting Template, users will find descriptions of reporting elements based on CONSORT guidance as well as on expertise from the NIH Collaboratory Demonstration Projects and Core working groups.

Particularly relevant to PCTs are recommendations on how to report the use of data from electronic health records. Other elements of importance to PCTs include reporting wider stakeholder engagement, monitoring for unanticipated changes in study arms, and specific approaches to human subjects protection. The template contains numerous links to online material in the Living Textbook, CONSORT, and the Pragmatic–Explanatory Continuum Indicator Summary tool known as PRECIS-2.

This resource is intended to assist authors in developing primary journal publications. It will be updated over time as new best practices emerge for the transparent reporting of PCTs.

Download the PCT Reporting Template.

Please note: this document opens as an Adobe PDF. If you do not have software that can open a PDF, click here to download a free version of Adobe Acrobat Reader.

This work was supported by a cooperative agreement (U54 AT007748) from the NIH Common Fund for the NIH Health Care Systems Research Collaboratory. The views presented in this document are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

Originally published on September 1, 2016.

  • Questions or comments can be submitted via email. Please add “Living Textbook” to the Subject line of the email.

Collaboratory phenotypes paper published in eGEMs special issue

Clinical trials, Data standards, Electronic health records, Learning health systems, Research tools, , , ,

A recently published special issue of eGEMs explores strategic uses of evidence to transform healthcare delivery systems. In A Framework to Support the Sharing and Re-Use of Computable Phenotype Definitions Across Health Care Delivery and Clinical Research Applications, Rachel Richesson and Michelle Smerek of the NIH Collaboratory’s Phenotypes, Data Standards, and Data Quality Core, along with coauthor C. Blake Cameron, envision an infrastructure that facilitates re-use of computable phenotypes in a learning healthcare system.

The authors elaborate on four required components of the framework:

  • Searchable libraries of explicitly defined phenotype definitions
  • Knowledge bases with information and methods
  • Tools to identify, evaluate, and implement existing phenotype definitions
  • Motivated users and stakeholders

Read the entire eGEMs open access publication here. eGEMs (Generating Evidence & Methods to improve patient outcomes), a product of AcademyHealth’s Electronic Data Methods (EDM) Forum, is a peer-reviewed, open access journal that seeks to accelerate research and quality improvement using electronic health data.

Related resources:

You can find extensive information on computable phenotypes in the Living Textbook chapter and in Tools for Research.

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.

New Lessons Learned Document Draws on Experiences of Demonstration Projects

Electronic health records, Institutional review boards, Pragmatic clinical trials, Regulatory issues, Research tools, , , , , , ,

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

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.

New Research Tool: Using the RxNorm System

Electronic health records,

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

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

PCORnet Posts Aspirin Study Protocol for Public Review and Comment

Clinical trials, Comparative Effectiveness Research, Electronic health records, Patient-Centered Outcomes Research, Pragmatic clinical trials, Randomized controlled trials, , , , , , , , ,

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