Grand Rounds Archive

Grand Rounds August 1, 2025: Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression (Kenneth L. Kehl, MD, MPH)

Posted on by Sophia Ramirez

Speaker

Kenneth L. Kehl, MD, MPH
Assistant Professor of Medicine and Physician
Dana-Farber Cancer Institute

Keywords

Artificial Intelligence; Cancer; Notification; Enrollment; Patient Identification

Key Points

  • Historically, less than 10% of adults with cancer enroll in clinical trials. At the same time, many trials struggle to reach their accrual goals. One possible contributor is that many trials of novel therapies for cancer have specific molecular criteria.
  • Dana Farber Cancer Institute (DFCI) developed MatchMiner, a computational matching tool, to connect patients to trials. However, identified patients often weren’t at a place in their treatment when information about trials was relevant. The research team was interested in whether they could train an artificial intelligence (AI) model to identify “trial-ready” patients.
  • The team conducted an implementation pilot, providing clinicians and research staff with weekly spreadsheets containing predictions of clinical trial “readiness” as identified by AI. The majority of identified patients were found to be ineligible upon RN review. Of those who were eligible, the majority opted not to move forward with the trial referral. At the end of the 9-month pilot, 6 AI-identified patients had been consented and enrolled in a therapeutic trial.
  • To assess the impact of AI-driven identification of trial-ready patients, the team launched OPTIONS (Optimizing Precision Trials with an artificial Intelligence driven Oncologist Notification System). The primary outcome of the trial was enrollment in any DFCI therapeutic clinical trial.
  • Patients with solid tumors were randomized into either a control group, in which they could be identified by the standard MatchMiner workflow, or 1 of 2 intervention groups. In the intervention arms, treating oncologists for genomically-matched patients with progressive disease and anticipated changes in treatment were contacted via email. In group 3, patients who met the readiness criteria were manually reviewed before the oncologists were contacted.
  • They found that, though the AI models successfully predicted which patients with active or progressive cancer may need treatment changes, sharing the trial information with oncologists did not increase trial enrollment.
  • This intervention addressed 1 barrier to trial participation. Other barriers may include eligibility criteria that goes beyond genomics and recent progression; and factors related to patient or oncologist preference, such as the motivation for participating, the complexity of the trial, and time toxicity.
  • Dr. Kehl concluded with a reminder that while AI can accelerate clinical cancer research by rapidly identifying clinical trial options for patients, impact requires integration. AI must be applied thoughtfully and continuously evaluated, and researchers should be aware of the pitfalls and shortcuts associated with the technology.

Discussion Themes

The DFCI team is currently working on MatchMiner-AI: an open-source tool that they hope will improve the accessibility of clinical trials for all patients by providing a list of relevant clinical trials. They’re running a pilot study focused on incorporating MatchMiner-AI with the historical tool.

It’s easier to train a model than it is to deploy it in a complicated healthcare context. Given that the tool performs as hoped, there are evidently implementation challenges that still need to be worked out.

The study team considered training the model on a more proximal task – i.e., “Predict whether this patient will enroll in a clinical trial.” However, they were concerned that this would introduce biases – a pertinent concern with AI models – based on which patients typically have the opportunity to enroll in clinical trials.

While there may be use cases in which providing the trial information directly to patients would be more efficient, this would need to be done carefully. Information about worsening cancer, for instance, is best contextualized in a conversation with an oncologist.

Grand Rounds July 18, 2025: State of Clinical Trials: An Analysis of ClinicalTrials.gov (Adrian F. Hernandez, MD, MHS; Rebecca D. Sullenger, MPH; Sara Bristol Calvert, PharmD; Karen Chiswell, PhD; Christopher J. Lindsell, PhD)

Posted on by Sophia Ramirez

Speakers:

Adrian F. Hernandez, MD, MHS
Executive Director
Duke Clinical Research Institute

Rebecca D. Sullenger, MPH
Duke University School of Medicine
MD Student | Class of 2026

Panelists:

Sara Bristol Calvert, PharmD
Director of Projects
Clinical Trials Transformation Initiative

Karen Chiswell, PhD
Statistical Scientist
Duke Clinical Research Institute

Christopher J. Lindsell, PhD
Director, Data Science and Biostatistics
Duke Clinical Research Institute

Keywords

Clinical Trials; Enrollment; Pragmatic Clinical Trials; Policy; Data Science

Key Points

  • A study of clinical trials from 2007 to 2010 found that the field was dominated by small trials and contained significant heterogeneity in methodological approaches, including reported use of randomization, blinding, and Data Monitoring Committees.
  • Clinical trials in the United States may be limited by legal, regulatory, and cost-related barriers. In a study of patient enrollment for cardiovascular clinical trials, the authors concluded that the U.S. had more trial sites than Eastern Europe or South America, but enrolled significantly fewer patients per site. These trends highlight the need for improved clinical trial infrastructure.
  • The presenters noted several promising trends in the field: growth in pragmatic clinical trials; high interest in clinical trial innovation from regulatory bodies and funding agencies; and the rapidly evolving capacity of clinical trials, particularly around accessibility.
  • The presenters provided an updated picture of the clinical trials landscape in the U.S., based on retrospective analyses of interventional clinical trials registered on ClinicalTrials.gov between 2018 and 2024.
  • They found that many trials remain small, lack a control group, and are incomplete after 5 years. Although small clinical trials without controls may be appropriate or necessary in specific contexts, such trials are also less likely to produce actionable data.
  • National policies prioritizing a more rapid, rigorous evidence generation system will likely be necessary to create a clinical trial ecosystem best equipped to advance public health.
  • In light of these insights, the team shared 5 potential policy approaches to improve the evidence-generation system in the U.S.:
    • Streamline trial start-up processes, institutional review board approvals, and contracting;
    • Enable scalable technologies to support greater participation;
    • Invest in modern clinical trial design strategies;
    • Require public reporting of key performance indicators and pay-for-performance results; and
    • Create stronger data sharing requirements and accountability rules.

Discussion Themes

Though the team utilized existing fields in ClinicalTrials.gov for their data, future research may utilize the key word search (i.e. adaptive platform trials) or natural language processing to investigate the state of clinical trials.

The value of small (<100 participants) trials was debated by the panelists. Though they do have a time and place, the high proportion of Phase III trials that enrolled less than 100 participants was surprising and concerning.

There are some limitations to ClinicalTrials.gov, namely in data entry. The more complex the trial, the more difficult it is to submit in a timely fashion. The system may post a barrier to embracing modern clinical trial design strategies.

Academia will also need to make policy changes to facilitate a healthier clinical trials ecosystem. The way career development and promotion pathways are structured, researchers are incentivized to lead small, potentially duplicative trials. Institutions need to reward, compensate, and value individual contributions to large-scale programs; i.e., the informative trial over the individually led trial.

Grand Rounds July 11, 2025: Novel Approaches to Recruiting Clinical Sites for Embedded Pragmatic Clinical Trials: Insights from the AIM-Back Trial (Trevor Lentz, PT, PhD and Tyler Cope, PT, DPT, ACT)

Posted on by terren.green@duke.edu

Speakers

Trevor Lentz, PT, PhD
Tyler Cope, PT, DPT, ACT
Duke Clinical Research Institute
Duke Department of Population Health Sciences
Durham Veterans Administration

Keywords

AIM-Back; Clinical site recruitment; Cluster randomized trial; Low back pain; Recruitment funnel

Key Points

  • Low back pain is an impactful condition that is more common in the veteran population. Typical low back pain care involves imaging and pharmacologic treatments that don’t always resolve pain issues and may lead to more invasive injection-based or surgical measures that often don’t result in better outcomes.
  • Research has shown that non-drug treatments (eg, cognitive behavioral therapy [CBT], yoga, physical therapy [PT]) are effective but not often used.
  • The AIM-Back trial (Improving Veteran Access to Integrated Management of Back Pain), an embedded pragmatic cluster randomized trial, sought to restructure care practices in Veteran’s Administration (VA) healthcare systems to promote and facilitate 2 clinical non-drug pathways that are supported by established guidelines as first-line treatment for low back pain.
  • Two care pathways were developed in coordination with VA clinicians, veterans, and care givers: (1) Sequenced Care Pathway – This pathway provided an initial onsite physical therapy evaluation and treatment session followed by weekly telehealth physical activity training for 6 weeks. The patient then saw the physical therapist again and was either discharged or provided with 6 weeks of training in psychologically-informed practices to help patients manage pain. (2) Pain Navigator Pathway – In this pathway, a local site clinician who was trained by the study team as a pain navigator discussed and facilitated alternative treatments for low back pain (eg, PT, yoga, CBT, massage). Patient follow up at both 6 and 12 weeks assessed progress and outcomes.
  • AIM-Back used a novel and intentional recruitment method, borrowing the concept of the business sales funnel, to generate as many site leads as possible. The recruitment process was systematic involving a 3 step framework: (1) Identify leads, (2) Approach leads, (3) Engage and select sites.
  • In step 1, leads were identified through Warm Market methods (sites known to the researchers), by Leveraging Data (evaluating lists of providers for potential fit), and through traditional Promotional Outreach efforts (advertising through networks and listservs). AIM-Back identified 184 leads from 53 VA healthcare systems.
  • Step 2 involved approaching leads through email messages. AIM-Back learned that promoting the trial in a way that helps clinicians solve their problems instead of asking clinicians to help with the research was more likely to yield the site. AIM-Back received responses from 23 VA healthcare systems.
  • In step 3, AIM-Back engaged personnel at all levels, from leadership to clinicians, to assess feasibility and buy-in at the site. AIM-Back selected 19 participant sites within 10 VA healthcare systems.
  • The Promotional Outreach strategy proved most effective with 9 (47.4%) of sites resulting from this strategy. The Leveraging Data strategy netted 6 (31.6%) sites, and 4 (21.1%) sites came from the Warm Market strategy. Site recruitment took approximately 3.6-3.8 months on average.
  • 17 sites enrolled 1817 Veterans with most sites (n=16) meeting or exceeding the minimum enrollment goal. When sites chose not to participate, they cited a reluctance to change their existing programs, a lack of clinicians or resources, or they were already participating in similar trials.

Discussion Themes

AIM-Back messaging evolved over the course of recruitment from a more traditional trial marketing email to an email that was more personal, short, and leveraged the standing of Duke University. This more personal approach to recruitment led to better relationships with sites during the trial.

Project management software can be helpful for tracking follow up with site leads and communication during the recruitment process.

One overall goal of AIM-Back was to set up a new clinical program that could continue after the end of the trial. Sites were given training materials for the centralized study components and support from AIM-Back was stepped down slowly. Sites that chose to continue the intervention trained a physical activity/whole health coach and a PT for the psychologically informed PT portion of the intervention.

Indicators of a potentially successful site included qualitative components that reflect a high level of engagement such as high interest and excitement in the study along with a sufficient patient population.

Read more about the AIM-Back trial design.

Grand Rounds June 27, 2025: Building Electronic Tools To Enhance and Reinforce CArdiovascular REcommendations for Heart Failure (BETTER CARE-HF) (Amrita Mukhopadhyay, MD, MS)

Posted on by Sophia Ramirez

Speaker

Amrita Mukhopadhyay, MD, MS
Eugene Braunwald, MD Assistant Professor of Cardiology
The Leon H. Charney Division of Cardiology Department of Medicine
Division of Healthcare Delivery Science Department of Population Health
NYU School of Medicine
NYU Langone Health

Keywords

Heart Failure; Electronic Health Record; Prescribing

Key Points

  • Heart failure is a major public health issue and a leading cause of hospitalization, affecting over 6 million Americans. Mineralocorticoid antagonists (MRA) are a potentially life-saving treatment but are under-prescribed in patients with heart failure with reduced ejection fraction (HFrEF). Closing this treatment gap could save over 20,000 lives in the U.S annually.
  • Electronic Health Record (EHR) tools could be a low-cost, scalable way to improve prescribing. However, there’s wide variability in EHR tool development and design. The optimal delivery and timing of EHR tools is unknown.
  • EHR tools fall into 2 categories: alerts and messages. Alerts apply to a single patient at a time and pop up during a clinical encounter; messages apply to multiple patients at once and are seen between encounters. The BETTER CARE-HF team designed both in accordance with Cognitive Load Theory and Nudge theory, applying the concepts of positioning, the split attention effect, default option, the transient information effect, and social influence.
  • They hypothesized that A) among patients with HFrEF who are evaluated by a cardiologist in the outpatient setting, an alert or a message will improve prescribing of MRA as compared to usual care, and B) the alert would be more effective than the message.
  • The researchers approached the pilot study as a “qualitative phase,” in which they would solicit feedback from participants and refine the intervention. They made several modifications to the EHR alerts and messages in response, and noted that guiding frameworks and pilot-testing were critical to designing an electronic intervention.
  • The pilot study was followed by a pragmatic trial that took place in over 60 practices in the NYU Langone Health System. Patients were cluster-randomized to an alert arm, message arm, or usual care. The primary outcome was new MRA prescription during the study period.
  • In the alert arm, nearly 30% of MRA-eligible patients were newly prescribed MRA – a highly statistically significant increase. The alerts were effective across all practice settings but were especially effective in high-volume settings.
  • In the message arm, 15.6% of MRA-eligible patients were newly prescribed MRA. Compared to 11.7% in the usual care arm, this was still a statistically significant increase, but was less effective than the alerts. Looked at another way, the number of MRA-eligible patients needed to result in one prescription was 25.6 in the message arm, compared to 5.6 in the alert arm.
  • An automated, EHR-embedded, tailored, and selective alert delivered at the time of the visit more than doubled prescribing of MRA as compared to usual care. Well-designed EHR tools could save lives.
  • Despite EHR tool effectiveness, busy physicians may still be hesitant. Too many tools can cause fatigue and burnout; concerns about workload and time costs can hinder uptake. Conversely, EHR tools that save time and reduce cognitive load may be more beneficial in busy practices. A post-trial survey indicated that cardiologist perceptions were generally favorable towards the BETTER CARE-HF tools, with some notable differences when asked about workflow.
  • The research team is conducting a multi-center trial to assess the effectiveness of the alert at other institutions, specifically across 3 high-volume health systems around the country. They are actively seeking other institutions to join the trial and encouraged attendees to reach out if interested.

Discussion Themes

The research team started by compiling EHR data on the current gap in care at NYU Langone. Having that real-time data helped the health system, and the physicians were a part of it, recognize that the intervention was necessary – despite their predisposition that they were delivering high-quality care.

This intervention was targeted to a specific population (cardiologists at NYU Langone) and a specific treatment (MRA) for a specific condition (HFrEF). In a different setting or if there was a different treatment involved, implementation may need to be adjusted.

Dr. Mukhopadhyay noted that folks who saw how the intervention worked were often surprised by how rarely the alert was triggered. She suspects that the selective nature of the intervention helped drive the intervention’s effectiveness by preventing burnout.

Working with a single IRB that understood the intention behind a learning health system helped standardize regulatory expectations across sites and facilitated onboarding.

Grand Rounds June 20, 2025: The BedMed Trials: Does the Timing of Blood Pressure Medication Matter? (Scott Garrison, MD, PhD, CCFP)

Posted on by Sophia Ramirez

Speaker

Scott Garrison MD, PhD, CCFP
Professor, University of Alberta, Department of Family Medicine
Director, Pragmatic Trials Collaborative

Keywords

Hypertension; Blood Pressure; Blood Pressure Medication; Medication Timing

Key Points

  • In 2010, the Monitorización Ambulatoria para Predicción de Eventos Cardiovasculares (MAPEC) trial found that hypertensive patients who took once-daily blood pressure (BP) medication at night, as opposed to in the morning, had a 61% reduction in major adverse cardiovascular events (MACE).
  • These results came with a credible rationale: BP is higher during the day than overnight, and overnight BP is a better predictor of cardiovascular events than daytime BP. Theoretically, patients taking BP medication at bedtime could preferentially lower overnight BP. But there were also good reasons to be skeptical of the results, and clinical guidelines remained unchanged.
  • To further investigate whether the timing of BP medication had an effect on MACE, Dr. Garrison and his team conducted 2 randomized controlled trials: BedMed and BedMed Frail. The former was conducted in a hypertensive primary care population; the latter in a hypertensive continuing care population. They conducted them separately, given the differing risks and benefits for the populations and the likely underrepresentation of frail or complex older patients in BedMed.
  • In the early stages, Dr. Garrison came across several unexpected challenges. There were restrictions around data access; regulations around billing for trial-related procedures in British Columbia; and the time it took to identify a data partner.
  • In both trials, the intervention group took a once-daily BP medication when getting ready for bed. In BedMed, the control took a once-daily BP medication upon waking up in the morning; in BedMed Frail, the control had no change in their existing routine (which typically meant taking their BP medication in the morning). Given the unique needs of the trial population, BedMed Frail utilized opt-out consenting.
  • The primary outcome for both trials was all-cause death or hospitalization/emergency department visit for stroke, acute coronary syndrome, or heart failure. In BedMed, they used an intent-to-treat analysis, with patients participating (via active or passive follow-up) in the study for a median of 4.6 years. In BedMed Frail, they used a modified intent-to-treat analysis, with patients participating for a median of 1.1 years due to high mortality in the study population.
  • The research team found that no additional cardiovascular benefit is conveyed from taking BP medication at bedtime. Conversely, their results concluded that these medications can be safely taken at bedtime, so patients should incorporate them into their routine whenever they are least likely to forget it.

Discussion Themes

Dr. Garrison noted that he was more confident in the negative result for the BedMed trial than for BedMed Frail, given that the adjusted hazard ratio of 0.88 and the unadjusted ratio of 0.93 in the latter. A 12% reduction in the outcome (which was largely driven by death) may still be meaningful to patients.

Designing a trial that was workflow-friendly for physicians was a top priority for the research team and was critical to obtaining buy-in for and executing this trial.

A major accomplishment of BedMed and BedMed Frail was developing a network of volunteer physicians and a data partner who would collaborate with the Pragmatic Trials Collaborative on future trials.

Grand Rounds June 13, 2025: Fit for Purpose: Improving the Ethical Oversight of Pragmatic Clinical Trials (Stephanie Morain, PhD, MPH; Nancy Kass, ScD; Ruth Faden, PhD, MPH)

Posted on by Sophia Ramirez

Speakers

Stephanie Morain, PhD, MPH
Associate Professor, Berman Institute of Bioethics & Department of Health Policy & Management
Johns Hopkins University

Nancy Kass, ScD
Phoebe Berman Professor of Bioethics & Public Health
Berman Institute of Bioethics & Department of Health Policy & Management
Johns Hopkins University

Ruth Faden, PhD, MPH
Philip Franklin Wagley Professor of Biomedical Ethics
Berman Institute of Bioethics & Department of Health Policy & Management
Johns Hopkins University

Keywords

Comparative Effectiveness Research; Research Ethics; Oversight; Fit for Purpose

Key Points

  • There are 2 key problems with the ethical oversight of comparative effectiveness research (CER): insufficient evidence to guide key clinical decisions and challenges with ethical oversight for trials aimed at guiding those decisions.
  • The vast majority of clinical decisions are still made in the absence of high-quality evidence. For example, fewer than 10% of current recommendations in cardiology are based on the highest quality evidence; expert opinion, on the other hand, guides over 40% of recommendations.
  • There are challenges with ethical oversight in clinical trials, particularly when comparing existing therapies in widespread clinical use. The traditional approach to research ethics holds that research is conceptually different from care, undertaken for the sake of future patients. The oversight system, established in the 1970s, ensure that the risk/benefit ratio was acceptable; that people knew they were taking part in a study, and that it is not equivalent to care; and that people can voluntarily agree (or refuse) to take part.
  • But the reality isn’t so tidy: A clinical trial really might be someone’s “best treatment option.” In the meantime, clinical care has wasted billions of dollars delivering care that was unproven, unnecessary, or in error. Ongoing learning in healthcare settings is essential but must have sound ethical oversight.
  • Clinical research is not all the same; oversight must be matched (“fit”) to the specifics of the study. Sometimes it does, e.g. for studies of experimental, pre-market products, with high uncertainty. But one-size fits-all oversight can be problematic, e.g. for CER on approved products, and excessive oversight results in a greater-than-appropriate burdens for researchers and collaborating clinicians.
  • The team at the Berman Institute proposed a new model to improve the “fit for purpose” of research ethics oversight that might be feasible within current regulatory structures. There were two key considerations: participation’s impact on welfare and on autonomy. Oversight bodies should consider how much additional risk and burden is introduced with participation and studies shouldn’t restrict a decision that would have been available and meaningful to patients.
  • To achieve “fit for purpose” oversight, observational studies will require minimal oversight due to minimal increased risk compared to usual care, and no restriction of meaningful choice. Randomized trials will require case-by-case evaluation.

Discussion Themes

The origins of informed consent have their roots in paternalism, in which a physician makes all the judgement calls on behalf of a patient. Yet researchers and clinicians must make judgement calls about which of the many decision points involved in care are worth highlighting; to run through all of them risks losing an emphasis on those that have more serious implications.

The team noted that respect for autonomy (like other ethics commitments) is not absolute. It is bounded by other morally important duties, such as promoting welfare and seeking justice. In the clinical context, it’s also bounded by tradeoffs where patients have other interests.

Grand Rounds June 6, 2025: The REDCap Advanced Randomization Module: A Trial Innovation Network Project to Support the Needs of Modern Trials (Jonathan D. Casey, MD, MSc)

Posted on by Sophia Ramirez

Speaker

Jonathan D. Casey, MD, MSc
Assistant Professor, Pulmonary & Critical Care, Vanderbilt University
Co-PI, Vanderbilt Trial Innovation Center
Director, Coordinating Center, Pragmatic Critical Care Research Group

Keywords

Randomization; Randomized Clinical Trial; REDCap; Innovation

Key Points

  • In a traditional randomized trial, trial procedures—including eligibility criteria, group allocation, intervention, and sample size—are specified before the trial and proceed unchanged throughout trial conduct. There are challenges associated with this method. Trials are expensive and take a long time; they’re designed to answer only 1 question; they commonly provide results that are underpowered and are therefore uninformative; they aren’t generalizable; and more.
  • For each of these issues, there are proposed solutions. Platform trials attempt to answer multiple questions within a single trial. Adaptive trials either increase allocation for better-performing groups (response-adaptive) or minimize imbalances (covariate-adjusted). Pragmatic or decentralized trials attempt to address generalizability.
  • To support these advanced trial designs, researchers may need a platform with the capacity to add or drop groups; randomize multiple times within the same record; generate randomization sequences that change allocation probabilities; and more.
  • REDCap is a secure web platform for building and managing online databases, available at no cost to nonprofit, academic, and government organizations. It’s one of the most commonly used platforms for clinical trials, and has included an embedded tool for randomization since 2012.
  • The original REDCap randomization tool embedded randomization into the data collection instrument and allowed one randomization for each study record. Users were able to stratify by sites or other key variables. However, there were gaps: users couldn’t add or drop a group; change the allocation ratio; randomize into multiple domains or at multiple points in time; and more.
  • This was identified as an area for improvement by Dr. Casey’s team in 2023, and the REDCap Advanced Randomization Module was developed. The new tool supports multiple randomizations, blinding, more meta-data, integration with non-REDCap systems, and more.
  • The next steps for this project include a methods and dissemination manuscript, which is currently under review; the incorporation of the randomization functionality into REDCap’s 21CFR Part 11 Validation framework; and the exploration of methods to support randomization within the EHR for pragmatic, EHR-embedded trials.
  • Clinical trials need to be efficient because resources – from personnel to funding—are limited. Innovators in the clinical trials space can target logistical efficiency, regulatory efficiency, or statistical efficiency. The REDCap Advanced Randomization module focuses on statistical efficiency.
  • Dr. Casey posited that the toughest question for clinical trial efficiency is when to use which design tool. Investigators facing these decision points can reach out to the Trial Innovation Center for guidance.

Discussion Themes

The Advanced Randomization Module has received a positive reception from the REDCap user base since its release in October. The group has also helped the REDCap team think through ways to refine the new features. Importantly, there have been no documented disruptions to ongoing projects.

In terms of clinical acceptability, the research team can track how many people are using the modules. How clinicians interpret and accept advanced the randomization features is harder to track, but the team is open to ideas.

There are some risks associated with introducing these complex tools into clinical settings; they increase the complexity of interpretation and can lead to unanticipated errors. Some people have raised concerns that a clinician audience might have a limited understanding of the biases that adaptive randomization can introduce.

The REDCap team is working on some exciting features for the next version of REDCap, including identity verification; data sharing and real-time data availability; and participant-mediated data sharing.

Grand Rounds May 30, 2025: Embedding Randomization Into Clinical Care in Learning Healthcare Systems: Insights From the KP-VACCINATE Trial (Ankeet S. Bhatt, MD, MBA, ScM)

Posted on by Sophia Ramirez

Speaker

Ankeet S. Bhatt, MD, MBA, ScM
Cardiologist, Kaiser Permanente San Francisco Medical Center
Research Scientist, Kaiser Permanente Northern California Division of Research
Adjunct Professor, Stanford University School of Medicine

Keywords

Nudges; Behavioral Science; Vaccination; Influenza; Implementation Science

Key Points

  • Implementation science is the scientific study of methods and strategies that facilitate the uptake of evidence-based practice and research into regular use by practitioners and policymakers.
  • While many implementation science interventions have targeted patients and providers, relatively few have been scaled at the system level with the ability to be replicated in other healthcare delivery systems. Dr. Bhatt’s team was interested in using a cyclical framework to address this gap in the evidence.
  • Behavioral science emerged as a promising area for this project. In recent years, the practice of employing nudges – subtle changes in design that can impact human behavior without restricting choice – has gained traction in the tech sector and in the public eye more broadly.
  • Dr. Bhatt’s team had worked with a group of Danish researchers on a sequence of nationwide clinical trials: NUDGE-FLU, NUDGE-FLU-2, and NUDGE-FLU-CHRONIC. These trials improved influenza vaccination rates in Denmark through randomization to different behavioral science-informed messaging strategies.
  • Vaccination rates in the U.S. have been stagnant for many years, and most systems are not reaching the minimum target of 70% compliance. Dr. Bhatt’s team, inspired by the NUDGE trials’ success, launched the Kaiser Permanente VACCination Improvement with Nudge-based CardiovAscular Targeted Engagement (KP-VACCINATE) Trial.
  • KP-VACCINATE is a fully embedded, randomized clinical trial assessing the effectiveness and timing of cardiovascular-focused nudge communication when it comes to vaccine uptake in a diverse U.S. population. It was developed in collaboration with Danish partners from the NUDGE trials and will be one of the largest clinical trials ever completed.
  • At the time of presentation, KP-VACCINATE was an ongoing, a 4-arm, 1:1:1:1 randomized clinical trial. The primary outcome is influenza vaccination rates assessed with 6 co-primary outcomes. Patients in Arm 1 receive nudges at Touchpoints 1 & 2; patients in Arm 2 receive nudges at Touchpoint 1; patients in Arm 3 receive nudges at Touchpoint 2; and patients in Arm 4 receive usual care.
  • This model is embedded in an integrated healthcare delivery system and may be readily transferable to other areas of patient, clinician, and health system engagement. Seamless collaboration between the research and operational teams was paramount for stakeholder engagement, implementation, and subsequent analysis.

Discussion Themes

In the interest of pragmatic systemwide inclusion, inclusion criteria were broad and most exclusion criteria pertained to an inability to receive health care system outreach. They also allowed for local adaptation to a unified protocol.

One barrier to conducting this kind of research is that not all healthcare systems are receptive to A/B randomization. When socializing KP-VACCINATE with operational teams, Dr. Bhatt pointed out that many health systems already conduct this kind of testing, albeit informally. Healthcare operates on incomplete evidence; decisions are made based on an integration of clinician judgement and the data we have on hand. This approach could improve systems’ ability to assess these strategies and integrate them into usual care.

Grand Rounds May 16, 2025: Pivoting Clinical Trials Into a New and Evolving World (Jeffrey A. Spaeder, MD; Adrian F. Hernandez, MD, MHS)

Posted on by Elizabeth Mccamic

Speakers

Jeffrey A. Spaeder, MD
Chief Medical and Scientific Officer
Senior Vice President
IQVIA

Adrian F. Hernandez, MD, MHS
Executive Director
Duke Clinical Research Institute
Vice Dean
Duke University School of Medicine

Keywords

Clinical Research; Clinical Trials; Industry Trials; Accelerating Research

Key Points

  • The U.S. lags behind in recruitment for cardiology trials. Even though the U.S. has the most sites, significantly fewer patients are enrolled. These trends suggest underlying legal, regulatory, and cost-related barriers, highlighting the need for improved clinical trial infrastructure.
  • Additionally, teams are growing, trust in science in the U.S. is low, and some health trends, such as obesity, hypertension, and diabetes, are going the wrong way. The U.S. leads avoidable deaths per 100,000 and could fall further behind, all while health care costs are rising.
  • If you are looking at the value of healthcare that is delivered in the U.S., we pay more than other countries but have worse outcomes. Healthcare expenses account for about 28% of the U.S. Federal budget. More than 90% of the volume of prescription drugs are generic with the exception of immunology, obesity, and diabetes. Retail net pricing of prescription drugs in the U.S. accounts for only 14% of all healthcare expenditures. These factors may lead policymakers to see an imbalance of expense to outcome.
  • This means for clinical trials there is an increased focus of using real-world data to make informed decisions, shorten timelines, and inform efficacy and safety. It will also be important to make sure endpoints are clinically relevant and more of an emphasis on strategy-focused research. There may also be more of an emphasis on improving outcomes from a lens of prevention
  • In industry, biopharma funding levels are increasing, with an emphasis on later-phase assets, and funding trends have returned to pre-COVID-19 levels. An increasing proportion of studies are initiated by emerging bio-pharma (EBP) sponsors. While overall measures of complexity has increased modestly, sites have experienced a greater increase – and so have study participants.
  • If there is a desire to increase industry-sponsored or other types of studies at academic medical centers, contracting timelines must be reduced, intellectual property causes significant churn with little value, IRB staffing and responsiveness is critical, cost and efficiency need to be appropriate value for expense, and principle investigators need to have actual availability for study activities.

Discussion Themes

-The U.S. conducts more clinical trials on rare diseases than other countries. Does that impact the numbers? The data from this presentation was from cardiovascular trials. The data was from common chronic cardiovascular diseases. The U.S. is an attractive place to conduct studies because the FDA regulatory timelines are predictable and fast, and the U.S. market is attractive, but enrollment per site is generally lower than it is elsewhere.

-How has IQVIA looked at drivers of cost and efficiency? Cost per patient has increased, driven by the complexity of studies and how imaging and other tools get built into studies. Investigators are trying to make studies more patient-centric, collecting data remotely, making visits fewer. There has also been an increased duration of studies, which is more costly. Time has real cost implications for sponsors.

-Is decentralization of trials a solution? It can be – hybridization can be helpful. How can you meet the patient where they are. You need clinician engagement but there are a lot of things that happen from beginning to end that could be decentralized. It has to be used selectively in the right situation.

-Is a centralized IRB a solution? They have real value if they have expertise and fast turnaround time – if they are credible, rigorous, and have experienced staff. In some situations, studies use a centralized IRB and then go through an institutional IRB as well.

Grand Rounds May 2, 2025: Fluid REStriction in Heart failure versus liberal fluid UPtake: The FRESH-UP Study (Roland RJ van Kimmenade, MD, PhD)

Posted on by Sophia Ramirez

Speaker

Roland RJ van Kimmenade, MD, PhD
Cardiologist, Radboud University Medical Center
Nijmegen, the Netherlands

Keywords

Heart Failure; Fluids; Cardiology

Key Points

  • We are facing a pandemic of heart failure (HF), with an incidence of 1 – 20 cases of heart failure per 1,000 people. The incidence of HF is stable – if not declining – but mortality remains high, at about 15 – 30% after one year. Attributable health care costs are up, and the prevalence of HF in the general population is increasing.
  • Orthopnea and edema are symptoms of heart failure caused by congestion, or “fluid retention.” This has led to an intuitive assumption that patients should monitor their fluid intake to 1.5 – 2L per day (including beverages, ice cream, soup, and some fruit). Patients are advised to do things like chew gum or suck on frozen grapes to relieve dry mouth and thirst.
  • The literature supporting fluid restriction is limited; as of 2018, the studies supporting it had small sample sizes and heterogeneous populations. They found no differences in mortality and hospitalization. Sets of clinical practice guidelines from 2021 and 2022 also noted that more evidence was needed for fluid restriction, and that existing evidence was low quality.
  • To address this gap in the evidence, the research team used crowdfunding to conduct the Fluid REStriction in Heart failure versus liberal fluid Uptake (FRESH-UP) Study. The randomized, open-label, multicenter clinical trial study took place between May 17, 2021 and June 13, 2024.
  • The primary outcome was health status at 3 months, as assessed by the Kansas City Cardiomyopathy Questionnaire – Overall Summary Score (KCCQ-OSS). The key secondary outcome was thirst distress at 3 months, as assessed by the Thirst Distress Scale for patients with HF (TDS-HF).
  • Participants were randomized to one of two arms: liberal fluid intake (no restriction) or fluid restriction, with a maximum of 1500 mL of fluid per day.
  • After three months, the research team found that the difference in KCCQ-OSS (adjusted for baseline scores) was 2.17, with a p value of 0.06. These findings favor liberal fluid intake, but the primary outcome was not met.
  • Thirst distress was higher in the fluid restriction group. No differences were observed for safety events between groups.
  • The FRESH-UP study questions the benefit of fluid restriction in chronic HF.

Discussion Themes

Patient-centered research is key in pragmatic trials; this trial came about because a patient voiced their discomfort and questioned the validity of fluid restriction. The researchers took this as a cue to question a key assumption in their field.

The Dutch Heart Foundation facilitated the crowdfunding, from the legal requirements to the website. The money raised from crowdfunding got them far enough to apply for a second grant.

As in clinical practice, the pragmatic nature of the trial made it difficult to guarantee participant fidelity throughout the entire experiment (though they did monitor intake at week six). The research team conducted a survey of participants afterwards to assess adherence. 93% of the patients reported that they adhered well to their regimes.

“Gaps in Evidence” in clinical guidelines is not a summary of failure, but a source of inspiration!