Design and analytic considerations for using patient-reported health data in pragmatic clinical trials: report from an NIH Collaboratory roundtable.

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2020-02-06

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Abstract

Pragmatic clinical trials often entail the use of electronic health record (EHR) and claims data, but bias and quality issues associated with these data can limit their fitness for research purposes particularly for study end points. Patient-reported health (PRH) data can be used to confirm or supplement EHR and claims data in pragmatic trials, but these data can bring their own biases. Moreover, PRH data can complicate analyses if they are discordant with other sources. Using experience in the design and conduct of multi-site pragmatic trials, we itemize the strengths and limitations of PRH data and identify situational criteria for determining when PRH data are appropriate or ideal to fill gaps in the evidence collected from EHRs. To provide guidance for the scientific rationale and appropriate use of patient-reported data in pragmatic clinical trials, we describe approaches for ascertaining and classifying study end points and addressing issues of incomplete data, data alignment, and concordance. We conclude by identifying areas that require more research.

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10.1093/jamia/ocz226

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Rockhold, Frank W, Jessica D Tenenbaum, Rachel Richesson, Keith A Marsolo and Emily C O'Brien (2020). Design and analytic considerations for using patient-reported health data in pragmatic clinical trials: report from an NIH Collaboratory roundtable. Journal of the American Medical Informatics Association : JAMIA, 27(4). pp. 634–638. 10.1093/jamia/ocz226 Retrieved from https://hdl.handle.net/10161/20274.

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Scholars@Duke

Rockhold

Frank Wesley Rockhold

Professor of Biostatistics & Bioinformatics

Frank is a full time Professor of Biostatistics and Bioinformatics and Faculty Director for Biostatistics at Duke University Medical Center, Affiliate Professor of Biostatistics at Virginia Commonwealth University, and Strategic Consultant at Hunter Rockhold, Inc.  His 40+-year career includes senior research positions at Lilly, Merck, and GlaxoSmithKline, where he retired as Chief Safety Officer and Senior Vice President of Global Clinical Safety and Pharmacovigilance.  He has held faculty appointments at six different universities.    Dr. Rockhold served for 9 years on the board of directors of the non-profit CDISC, most recently as Chairman, and is past president of the Society for Clinical Trials and a past member of the PCORI Clinical Trials Advisory Panel. He is currently Chair of the Board of the Frontier Science and Technology Research Foundation and a technical advisor to EMA.

Dr. Rockhold has diverse research interests and consulting experience in industry and academia including clinical trials design, data monitoring, benefit/risk, safety and pharmacovigilance and has been a leader in the scientific community in promoting data disclosure and transparency in clinical research.    Frank is widely published in major scientific journals across a wide variety of research topics.

Frank holds a BA in Statistics from The University of Connecticut, an ScM in Biostatistics from The Johns Hopkins University, and a PhD in Biostatistics from the Medical College of Virginia at Virginia Commonwealth University. Frank is an Elected Fellow of both the American Statistical Association and the Society for Clinical Trials, a Fellow of the Royal Statistical Society, an Accredited Professional Statistician, PStat®, and a Chartered Statistician, CStat.  

Tenenbaum

Jessica Dale Tenenbaum

Associate Professor of Biostatistics & Bioinformatics

Dr. Tenenbaum is a faculty member in the Division of Translational Biomedical Informatics in the Department of Biostatistics and Bioinformatics. Her primary research interests are  1. Informatics to enable precision medicine; 2. Mental health informatics; 3. Infrastructure and standards to enable research collaboration and integrative data analysis; and 4. Ethical, legal, and social issues that arise in translational research, direct to consumer genetic testing, and data sharing. Current research projects focus on analyzing electronic health record data to better understand mental illness, target resource allocation, guide treatment, and develop targeted therapeutic interventions.

Nationally, Dr. Tenenbaum plays a leadership role in the American Medical Informatics Association, serving as Chair of the Mental Health Informatics Working Group and as an elected member of the Board of Directors. She is an Associate Editor for the Journal of Biomedical Informatics and served on the advisory panel for Nature Publishing Group's Scientific Data initiative.  After earning her bachelor’s degree in biology from Harvard, Dr. Tenenbaum worked as a program manager at Microsoft Corporation in Redmond, WA for six years before pursuing a PhD in biomedical informatics at Stanford University.

Marsolo

Keith Allen Marsolo

Professor in Population Health Sciences

Dr. Marsolo is a faculty member in the Department of Population Health Sciences (DPHS) and a member of the Duke Clinical Research Institute (DCRI).  His current research focuses on infrastructure to support the use of electronic health records (EHRs) and other real-world data sources in observational and comparative effectiveness research and public health surveillance, as well as standards and architectures for multi-center learning health systems.  He serves as faculty advisor to the DPHS DataShare Shared Facility and faculty lead for the Pragmatic Health Services Research (PHSR) functional group within the DCRI.  Dr. Marsolo received his PhD in Computer Science from The Ohio State University, with a dissertation on data mining, specifically the modeling and classification of biomedical data. 

Prior to joining DPHS, Dr. Marsolo was an an Associate Professor in the Division of Biomedical Informatics (BMI) at Cincinnati Children’s Hospital Medical Center (CCHMC). While at CCHMC, Dr. Marsolo served as faculty advisor for BMI Data Services, a shared facility that supported distributed data sharing networks and also developed registry platforms to support learning networks. These included a configurable system for capturing summary or practice-level measures, and a “data-in-once” architecture that allowed information to be collected in the EHR and then be automatically transferred to a registry in order to support chronic care management, quality improvement and research.

Area of Expertise: Informatics, Data Quality, Common Data Models, Data Standards and Data Harmonization

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