Pragmatic Health Systems Research (PHSR)

Pragmatic Health Systems Research (PHSR)

Real-world data from routine patient care are being produced in healthcare settings at a staggering and accelerating pace. Using these data to efficiently generate real-world evidence requires a deep understanding of the data generation processes, systematic attention to data quality, and the ability to translate research questions to rigorous study designs.

DCRI Pragmatic Health Systems Research (PHSR) informaticians, project managers and coordinators, and Duke faculty members, lead, advance and execute innovative and pragmatic health systems research that utilizes real-world data generated as a by-product of health care delivery to generate evidence to improve patient care.

Our Capabilities

PHSR has ongoing collaborations with biopharma and medical device companies, government agencies, insurance providers, medical associations and societies, and patient advocacy groups. These collaborations allow PHSR to conduct pre-research queries, prospective and retrospective observational studies, and interventional studies while leveraging methods that cut costs, save time, and answer questions that matter the most to patients.

PHSR provides:

  • Research network coordination and support, including site outreach, management and coordination, proposal intake, and data coordinating center activities
  • Enhanced project recruitment, utilizing real-world data to identify the best sites and potentially eligible patients
  • Data linkage among multiple sources
    • Electronic health records (EHR)
    • Medicare and private payer claims
    • Trials and registry datasets
    • Patient-reported outcomes
  • Real-world data harvest, including the development of computable phenotypes and clinical concept code lists
  • Fitness-for-use assessments of real-world datasets

Debra Harris
Associate Director
Pragmatic Health Systems Research

“Data is plentiful. Accurate and robust interpretation of the available data and its sources is the critical foundation for generating reliable evidence and medical knowledge to improve patient care.”

portrait photo

Pragmatic Clinical Trials and
Electronic Health Records

With the growing availability of clinical EHRs, pragmatic clinical trials (PCT) have access to data gathered in real-world treatment settings without needing to invest in the tremendous overhead costs associated with other data-capture systems. EHRs are being rapidly adopted in both ambulatory and hospital settings, thereby providing researchers with the potential to screen, identify, enroll, and follow large numbers of patients. Linked systems of EHR-facilitated research will make a new era of pragmatic clinical trials possible. Efficient patient enrollment and lower costs will allow studies to be done in larger, more diverse, and more representative populations. This, in turn, can potentially increase the validity and generalizability of study findings, while also improving access to research participation for under-served or under-represented groups.

Research Highlights

A New Methodology for Conducting Trials

ADAPTABLE is a pragmatic clinical trial that will compare the effectiveness of two different daily doses of aspirin widely used to prevent heart attacks and strokes in individuals living with heart disease. The study is also intended to reduce the burdens that traditional processes for research data collection impose on patients, clinicians, and practices. DCRI's PHSR team has contributed to this last aim by developing a real-world data algorithm that leverages electronic health records (EHR), as well as private and public claims data, to identify eligible patients and, supplemented by patient-reported outcomes, determine clinical trial outcomes and events via real-world datasets. Study follow-up will consist of a systematic gathering of data from health system encounters mapped to a common data model from claims data, or directly from patients, via the ADAPTABLE patient portal or call center. The study was recently cited on page 10 of the FDA’s Frame Work for Real-World Evidence Program publication as a trial currently generating real-world evidence.

Redefining Accessibility and Reliability via PCORnet

Health care in America is at an exciting precipice of data, knowledge, and innovation. But opportunities and cost have grown faster than our ability to accurately analyze outcomes as well as the quality of the information we have at our fingertips. PCORnet, a national evidence generation system in which researchers can leverage large sets of health and healthcare data gathered in real-world settings, has tapped into the expertise of DCRI's PHSR to maintain the network infrastructure for over 100 million patients' health data.

Learn more about the Common Data Model, by watching DCRI’s Lauren Cohen share the work that has gone into the PCORnet CDM and her perspective on the need to facilitate effective queries. Then read Lesley Curtis’, PhD insights in her article The Tower Of Babel In Clinical Research: PCORnet’s Common Data Model Cracks The Foundation.

The Common Data Model: Standardizing Existing Data for Rapid Response

PHSR and PCORnet are transforming how electronic health record data can be utilized through the development of a Common Data Model (or CDM) by organizing data into a standard structure.  Data sets, utilized in prospective and retrospective research, are organized in a consistent format that allows for efficient responses to research related questions. Questions can range from simply finding potentially eligible patients who match the criteria of interest to complex analyses that address critical health questions. PCORnet relies on the expertise of PHSR to develop and deploy the data collection queries and associated codelists to map real-world data to a clinical research dataset, while additionally identifying suitable sites and patients via real-world data sets to enhance patient recruitment.


Assessing the Fitness of EHR Data in Clinical Trials

EHRs are a rich source of clinical data becoming increasingly fundamental to clinical research. However, the degree to which EHR data are fit for use in clinical trials still requires rigorous evaluation. DCRI’s PSHR is engaged in an ancillary study to the HARMONY Outcomes Trial which will assess the fitness of EHR data to facilitate clinical trial enrollment, populate baseline characteristics, and identify clinical endpoints as part of a large, multinational clinical trial. This opportunity addresses a critical knowledge gap in research in which the FDA has demonstrated a significant interest. They recently cited the ancillary study on page 35 of the FDA’s Frame Work for Real-World Evidence Program publication in their appendices of demonstration projects.In the following video, the DCRI’s Brad Hammill, PhD, explains the opportunities and gaps still present in EHR data utilization.

PHSR Leadership at the DCRI

Keith Marsolo, PhD
Faculty Director
Pragmatic Health Systems Research


Debra Harris, BA
Associate Director, Operations
Pragmatic Health Systems Research

Duke Faculty Collaborator

Sudha Raman, PhD: Population Health Sciences

Select Publications

Raman S, Curtis L, Temple R Andersson T, Ezekowitz J, Ford I, James S, Marsolo K, Mirhaji P, Rocca M, Rothman R, Sethuraman B, Stockbridge N, Terry S, Wasserman S, Peterson E, Hernandez A.Leveraging electronic health records for clinical research. Am Heart J. 2018;202:13-19. doi:

Qualls LG, Phillips TA, Hammill BG, Topping J, Louzao DM, Brown JS, Curtis L, Marsolo K. Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®). eGEMs (Generating Evidence & Methods to improve patient outcomes). 2018;6(1):3. DOI:

Turley R., Mi X., Qualls L., Vemulapalli S., Peterson E., Patel, M., Curtis L. and Jones W. The Effect of Clinical Care Location on Clinical Outcomes After Peripheral Vascular Intervention in Medicare Beneficiaries. JACC: Cardiovascular Interventions. 2017;10(11):1161-1171. doi:

Hernandez A,Fleurence R, Rothman R. The ADAPTABLE Trial and PCORnet: Shining Light on a New Research Paradigm. Ann Intern Med. 2015;163(8):635. doi: