*Coming Soon* LHEA On-Demand

Designing Research FAIRly – Course Intro  
When a researcher, clinician or quality improvement team designs a study, they consider many factors: 
  •     Will this research make a difference – to patients? to society? 
  •     How will we find subjects/patients or data to meet the research criteria?
  •     Will the data answer the research question?  Will it be in an analyzable format?
  •     Are the data sharing plan and the statistical analysis plan robust?
  •     Can we assure patients that their data will be protected and used wisely?
  •     Will the results be robust enough for wide dissemination? Will the results be publishable?
  •     Where do we start?
No one plans to fail, but many fail to plan—adequately and at the start.  It is heartbreaking, after designing and conducting a research study, to find that the results are not robust and publishable, or the data cannot be interpreted or shared as anticipated.  This occurred frequently during the pandemic; studies often failed to produce trustworthy results, which means patients and researchers wasted their precious time and effort.   

According to Deborah Collyar from Patient Advocates In Research (PAIR) and Leanne Larson, Parexel Access, “Many patients……..now feel that they are being viewed as simply a data ‘repository’ rather than as a person.” (1)  It is incumbent upon us, as researchers, to change this paradigm.  The data we use for research belongs to patients. We owe it to them to use their data and their time wisely.  We can start with robust planning and designing research studies FAIRly from the start.  

FAIR refers to making data Findable, Accessible, Interoperable and Reusable.  FAIR data management principles (2) have been developed to address especially the data management aspects of data sharing, which has become increasingly important for researchers.  In addition, a broader set of clinical research data sharing principles developed through the CORBEL (3) initiative when data sharing became important to journal editors. “The International Committee of Medical Journal Editors (ICMJE) believes there is an ethical obligation to responsibly share data generated by interventional clinical trials because trial participants have put themselves at risk”. (4) Thus, they developed a set of recommendations based on this belief and have encouraged others to require this as a prerequisite to publication.  In addition, funders such Howard Hughes, US National Institutes of Health (NIH), and the Gates Foundation now require that grantees make data public alongside their articles, and starting in 2023 NIH will require a data sharing plan from all grantees.  Data sharing principles are important not only to honor the contributions of patients to research, but also to protect their privacy. In addition to sound data management and planning for data sharing, it is critical to develop a research protocol such that statistical analysis plans and requirements are addressed in terms of the study population. The Good Clinical Trials Collaborative (5) has developed guidance around many of these key areas.  It is nearly impossible to address these items once a study has been initiated, much less when it has been completed.   

Data produced in the process of healthcare comes from many different sources and is sometimes referred to as Real World Data (RWD).  Regulators and others wish to use RWD to obtain Real World Evidence (RWE) to support their decisions regarding the approval and use of new treatments. In fact, the US Congress has mandated through the 21st Century Cures Act that FDA increase their use of healthcare data/RWD to augment the data from randomized clinical trials for regulatory decision-making (6) and other global regulators are also quite interested in ‘big data’ and RWD. According to Collyar and Larson, patients want Real World Answers (RWA) about what medicines and health practices will help them. But, finding trustworthy answers requires meaningful and trustworthy data.  The 26 June 2023 New Yorker article “Bitter Pill” tells the story of ALS patients, who are in some cases following the prior playbook of AIDS patients. (7) It emphasizes that patients are desperate for cures, but they obviously do not want to pay large sums of money for treatments that may not work. The only way to be confident that treatments or interventions are effective is with robust and statistically significant results/answers based on reliable data. Learning Health Systems leverage healthcare data for research to obtain results that can inform optimal shared medical decision-making by clinicians and patients.   

In this foundational course, you will learn from experts:  
  • how to ensure that patients and their concerns are at the center of the research process  
  • how studies leverage best practices and principles in designing and executing research studies that leverage healthcare data coming from a variety of sources;
  • how FAIR research design promotes Findable, Accessible, Interoperable and Reusable data and RWA;
  • how core values and characteristics of learning health systems support RWA;
  • how the use of global data standards and controlled terminologies can build in efficiencies from the start;  
  • what global regulations, guidance and data sharing requirements are applicable for your research.
Additional modules will be available to explore digital health technologies, AI and machine learning, data privacy and case studies.
We hope you enjoy this educational journey – as a patient, clinician, researcher, medical student, protocol author, patient advocate, caregiver, or another interested party. Remember, we are ALL patients!

  1. “The Promise and Problems of Real World Data and Evidence (RWD/RWE) for Patients and Companies”, blog by Deborah Collyar, Patient Advocates In Research (PAIR) and Leanne Larson, Parexel Access
  2. Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
  3. Ohmann, C., Banzi, R., Canham, S., Battaglia, S., Matei, M., Ariyo, D., Becnel, L., Bierer, B., Bowers, S., Clivio, L., Dias, M., Druml, C., Faure, H., Fenner, M., Galvez, J., Gheris, D., Gluud, C., Groves, T.,  Houston, P., Karam, G., Kalra, D., Knowles, R., Kreleza-Jeric, K., Kubiak, D., Kushinke, W., Kush, R., Lukkarinen, A., Marques, P.S., Newbigging, A., O’Callaghan, J., Ravaud, P., Schulunder, I., Shanahan, D., Sitter, H., Spalding, D., Tudur-Smith, C., van Reusel, P., van Veen, E., Visser, G.R., Wilson, J., Demotes-Mainard, J., “Sharing and reuse of individual participant data from clinical trials:  principles and recommendations”, British Medical Journal Open, 2017:7:e018647, doi: 10.1126/bmjopen-2017-018647   
  4. ICMJE Statement: https://www.icmje.org/news-and-editorials/data_sharing_june_2017.pdf  
  5. Good Clinical Trials Collaborative: https://www.goodtrials.org/  
  6. 21st Century Cures Act and FDA: https://www.fda.gov/regulatory-information/selected-amendments-fdc-act/21st-century-cures-act21s t  
  7. Lewis-Kraus, Gideon, “Bitter Pill”, New Yorker, 26 June 2023