Evidence generation

Grand Rounds January 17, 2025: Design for Diversity: Designing Studies for Representativeness and Generalizability (Christopher J. Lindsell, PhD)

Posted on by Sophia Ramirez

Speaker

Christopher J. Lindsell, PhD
Professor and co-Chief, Biostatistics, Duke University
Director, Data Science and Biostatistics, DCRI
Director, Biostatistics and Bioinformatics, CTSI
Editor in Chief, Journal of Clinical and Translational Science

Keywords

Study Design; Diversity; Health Disparities; Evidence Generation

Key Points

  • Health disparities are factors that contribute to preventable differences in health status and outcomes. They can be environmental, sociocultural, behavioral, and biological. These are preventable differences with adverse effects for populations.
  • When research teams don’t consider factors that change outcomes for certain populations but not others, research can contribute to a difference in health status and outcomes. A flawed evidence generation system compounds the problem.
  • One popular solution is to measure and adjust for diversity variables; however, research teams often get the variable wrong or use it incorrectly.
  • By designing for diversity, research teams can begin to address the generalizability of evidence; develop an understanding of factors that contribute to success or failure of interventions among diverse populations; and remove the evidence generation system as a contributor to health disparities.
  • Designing for diversity is an optimization problem. Historically, study designs have been optimized for the researcher; Dr. Lindsell proposed that researchers optimize for the participant.
  • Research that is optimized for the participant is rigorous and flexible; safe and practical; and complete and simple. Participants should be embedded in every part of the research process. This can be difficult – there are tradeoffs involved – but it is effective.
  • The interface between data generation and data use is crucial. Making systems that work to bring in the right information and systems that use that information appropriately are two pieces of the same puzzle.
  • Dr. Lindsell included a call to ditch the ordinary subgroup analysis, noting that groups are not binary and not all groups have meaning. He suggested a focus on interaction terms.

Discussion Themes

Institutions should be supporting research teams in their ability to achieve diversity; this should be a matter of course, rather than something to be achieved without support and then celebrated as a remarkable accomplishment.

Looking forward, as data infrastructure becomes increasingly robust, research teams and communities may be able to collaborate to build a more complete understanding of individuals’ health states and who may be in need of an intervention.

May 5, 2020: Dr. Robert Califf Discusses Next Steps for Reforming the Evidence Generation Ecosystem After COVID-19

Posted on by Gina Uhlenbrauck

In case you missed the May 1 keynote address by Robert M. Califf, MD, MACC, you can now listen to the recorded webinar and Q&A. Dr. Califf, head of strategy and policy for Verily Life Sciences and Google Health, kicked off the Collaboratory’s Grand Rounds workshop series, Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials.

His presentation outlined several opportunities to drive change and rebuild clinical research in the aftermath of COVID-19, including:

  • Evaluate what has and has not worked in the changes that have been made in response to the crisis
  • Allocate a significant part of recovery funding to transition issues in evidence generation, especially at the interface of medicine and public health
  • Do everything possible to fix the “purposefulness issue”:
    • Create methods for deciding the most important questions
    • Reward behavior that gets important questions answered quickly
  • Develop inclusive networks driven by people with the health problems of interest; increase incentives for clinicians and investigators that lead to reliable and faster evidence generation (balance financial focus with purpose); and automate mapping of EHR data beyond individual systems

“The effective use of digital information such as electronic health records, telehealth, applications, and patient-reported outcomes should free up effort to fix the human components that are holding us back.” – Dr. Robert Califf

View the full presentation for more insights from Dr. Califf.

Stay tuned for these upcoming presentations in the series:

May 1, 2020: Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Keynote-Can the COVID-19 Crisis Lead to Reformation of the Evidence Generation Ecosystem? (Robert Califf, MD, MACC)

Posted on by Gina Uhlenbrauck

Speaker

Robert Califf, MD, MACC
Head of Strategy and Policy
Verily Life Sciences and Google Health

Topic

Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Keynote-Can the COVID-19 Crisis Lead to Reformation of the Evidence Generation Ecosystem?

Keywords

Electronic health records; Digital health; Mobile health; Coronavirus; COVID-19; Ecosystem; Clinical trials; Evidence generation

Key Points

  • The HERO Registry and RECOVERY Trial are good examples of a rapid clinical research response to the urgent COVID-19 health crisis.
  • Among the essential steps to move the evidence generation system in the right direction:
    • Evaluate what has and has not worked in the changes made in response to the crisis
    • Allocate a significant part of recovery funding to transition issues in evidence generation, especially at the interface of medicine and public health
    • Increase purposefulness by creating methods for deciding the most important questions and rewarding behavior that gets those questions answered quickly

Discussion Themes

The COVID-19 pandemic has shone a spotlight on disparities in our current healthcare delivery system. How can we avoid leaving the most vulnerable of society behind?

Telemedicine can be a framework for the integration of research and clinical care. But the digital element must be integrated with the human element. The routine and effective use of digital information should free up effort to fix the human components that are holding us back.

We’ve been trying to modernize clinical trial design for decades (factorial/sequential/adaptive designs for example). While some positive movement in the past month has been made, the research enterprise remains largely conservative when it comes to design modernization. How do we make more rapid progress?

Tags

#pctGR, #COVID19, @Collaboratory1, @Califf001