Grand Rounds Archive

Grand Rounds April 25, 2025: Automated Response Technology Integrated into EMR and Physician-Patient Communication (Ming Tai-Seale, PhD, MPH)

Posted on by Sophia Ramirez

Speaker

Ming Tai-Seale, PhD, MPH
Professor
Departments of Family Medicine and Medicine (Bioinformatics)
University of California San Diego School of Medicine
Director of UC San Diego Learning Health Systems Science Center

Keywords

Electronic Health Record; Artificial Intelligence; MyChart; Patient Messages; Large Language Models; Clinician Well-Being; Mental Health

Key Points

  • Physician work is increasingly centered around the electronic health record (EHR). It consumes nearly 50% of scheduled clinic time. The volume of patient messages in MyChart increased significantly from 2020 to 2022, and remains much higher than pre-pandemic levels.
  • Research published in Health Affairs and JAMA Network Open suggests that this influx of inbox messages is detrimental to physicians’ well-being. The emotional timbre of messages from patients plays a role, as well; in an analysis of EHR inbasket messages, the research team found messages from patients that contained expletives, vitriol and personal attacks.
  • The research team sought to examine the association between generative AI (GenAI)-drafted replies for patient messages and physician time spent on answering messages. They were also looking at the quality of GenAI-drafted replies for messages dealing with mental heath concerns.
  • The team created a prompt within the EHR that gave physicians the option to either use an AI-generated response as a starting point or to start with a blank reply. Messages eligible for responses drafted by GenAI included refills, results, paperwork, and general questions.
  • The pilot study took place from June 16 to July 12, 2023, targeting primary care attending physicians at University of California San Diego. 52 physician volunteers received the intervention; the 70 physicians in the control arm did not.
  • In the pilot study, clinicians who were given the option of a GenAI-drafted reply spent more time reading patient messages. There was no change in average reply time.
  • When clinicians received messages dealing with mental health issues, replies drafted by more recent versions of GenAI had more utility than older versions.
  • The physicians expressed that they valued the GenAI-drafted replies as a compassionate starting point for their communication. They noted areas for improvement, like a robotic tone, and emphasized the continued need for human oversight and intervention.
  • The study team acknowledged potential risks when using large language models (LLMs) in mental health communication. These included a loss of human touch and empathy; overreliance and deskilling; and privacy and security risks.
  • This is an ongoing effort. Next steps include using LLMs to facilitate analyses of qualitative data on electronic patient-clinician communication; triangulating qualitative and quantitative data in the EHR; and aiming for a more comprehensive understanding of mental health communication and how LLMs might improve its quality.

Discussion Themes

Anecdotally, the researchers have heard from physicians that ART technology – which Epic and Microsoft continue to refine – seems to have improved. But issues still remain, such as GenAI recommending patients see clinicians from external hospital systems.

When a modified GenAI-drafted reply was sent to a patient, a disclaimer was included: “Part of this message was generated automatically.” The research team felt that it was important to provide this transparency and disclose to patients when AI contributed to the messaging they received.

Health systems and professional organizations must develop standards advocating for equity in the implementation of and access to these tools.

Grand Rounds April 18, 2025: Colchicine and Spironolactone Post-MI — A Review of the Late-Breaking Results of the CLEAR OASIS 9 Trial (Sanjit S. Jolly, MD, MSc, FRCPC)

Posted on by Sophia Ramirez

Speaker

Sanjit S. Jolly, MD, MSc, FRCPC
Interventional Cardiologist, Hamilton Health Sciences
Stuart Connolly Chair in Cardiology
Professor of Medicine, McMaster University

Keywords

Myocardial Infarction; Cardiology; Heart Failure; Colchicine; Spironolactone

Key Points

  • 20 years ago, an article published in Nature hypothesized that if we could find a cardioprotective drug to lower cardio-reactive protein (CRP), we could eliminate heart disease.
  • Over the last 2 decades, there have been successes and failures on that front. The Cardiovascular Inflammation Reduction Trial (CIRT) found that methotrexate did not reduce the rate of major adverse cardiovascular events. The Canakinimab Anti-inflammatory Thrombosis Outcomes Study (CANTOS) found that higher doses of canakinumab reduced cardiovascular (CV) death, myocardial infarction (MI), or stroke by over 15% during follow-up.
  • The CoLchicine and spironolactonE in patients with myocardial infARction/SYNERGY Stent Registry – Organization to Assess Strategies of Ischemic Syndromes 9 (CLEAR SYNERGY OASIS 9) Trial was a large, simple, randomized trial of 7,000 patients with ST-elevation myocardial infarction or large non-ST-elevation myocardial infarction. Participants were randomized in a 2×2 factorial; first to either colchicine or placebo, then to either spironolactone or placebo.
  • The primary outcome in the first factorial was the effect was treatment with colchicine vs placebo on a composite of CV death, MI, stroke, or IDR. The co-primary outcomes in the subsequent factorial were the effects of spironolactone vs a placebo on 1) a composite of CV death or heart failure (HF) and 2) a composite of CV death, HF, stroke, or MI.
  • There have been 2 large trials looking at colchicine in cardiovascular disease: COLCOT and LODOC02. The CLEAR trial started before the results of the COLCOT trial, as the research team believed a larger confirmatory trial with more power was needed and replication of power results were important for Class 1 indications in guidelines. CLEAR is the largest trial of colchicine in acute MI, with substantially more events than prior trials.
  • In the first factorial, they found that while CRP was reduced with colchicine, acute and long-term colchicine did not reduce the composite of CV death, MI, stroke, or ischemia-driven revascularization. Colchicine was also associated with an increase in diarrhea, a known side effect of the drug. The research team believes the role of colchicine post-MI remains uncertain.
  • There have been 2 trials looking at Mineralocorticoid Receptor Antagonists (MRA) post-MI in patients without HF: REMINDER and ALBATROSS. Their results left some questions unanswered.
  • In the second factorial, they found that routine spironolactone post-MI did not reduce either co-primary outcome. There was a reduction in new or worsening heart failure, and on-treatment analysis suggests a potential benefit.

Discussion Themes

Outcomes have improved remarkably over the last 20 years, such that HF event rates in a population with predominantly ST-elevation MI are around 3%; a significant drop from the roughly 20% HF event rate in that population 20 years ago. That makes it more difficult to show treatment effects in this population.

The study team developed their inclusion criteria to select for a study population that would be applicable in standard clinical practice. The trial became more pragmatic as the study went on as a result of pivots they made in response to the COVID-19 pandemic.

Key challenges were driven by the COVID-19 pandemic. These included shipping expenses, which spiked significantly; shifting logistics, regarding who would receive the materials; and a pause in recruitment. The study team also came up against varying drug approvals in different locations; this was a global trial, taking place over roughly 70 sites in 11 countries.

Grand Rounds April 11, 2025: Pridopidine in ALS: Results from the Healey Platform Trial (Jeremy M. Shefner, MD, PhD)

Posted on by Sophia Ramirez

Speaker

Jeremy M. Shefner, MD, PhD
Professor of Neurology
Barrow Neurological Institute

Keywords

ALS; Platform Trial; Phase 2 Trial

Key Points

  • Amyotrophic Lateral Sclerosis, or ALS, is an age-related degenerative disease affecting the primary motor neurons in the brain and the alpha motor neurons in the spinal cord. It causes weakness in the limbs, breathing muscles, and facial muscles. Males are affected significantly more than females; 1 in 700 men will die of ALS.
  • The average survival after the onset of the first ALS symptom is about 4 years – a small improvement despite decades of clinical trials. Treatment modestly prolongs both survival, function, and quality of life for patients with ALS.
  • In the last decade, 2 drugs has been approved by the U.S. Food and Drug Administration (FDA) for use in patients with ALS. These drugs reached Phase 3 or approval on the basis of small trials; however, subsequent large multinational trials failed to meet their primary endpoints, leading to the withdrawal of one agent and a reduction in the use of another.
  • There is a robust pipeline of drugs in early development and a network of high-quality study sites. However, clinical evaluation is slow, for many reasons: the episodic nature of ALS requires new staffing and training for every trial; start-up is slow; participants wish to reduce placebo assignments as much as possible; and costs are excessive.
  • The HEALEY phase-2 platform trial was developed to meet the needs of the ALS community and with the ultimate goal of moving drugs that were more likely to succeed to phase 3. It’s intended to function as a perpetual trial, as patient-friendly as possible, with a broad set of inclusion criteria so that a placebo group can be shared between trials.
  • This approach has several advantages over traditional clinical trials: It reduces the number of participants who must be assigned to the placebo group; it cuts time; and it cuts costs. Since 2020, 7 drugs have gone through the pipeline.
  • One of these drugs is Pridopidine. Participants were randomized 3:1 to receive either Pridopidine or a placebo for 24 weeks. The primary outcomes were change in the ALS Functional Rating Scale-Revised (ALSFRS-R) total score and survival.
  • While Pridopidine was safe and well tolerated, there was no overall effect on the primary endpoint. However, potentially meaningful signals were seen suggesting efficacy in secondary endpoints, particularly measures of motor speech performance. And in participants with definite ALS and baseline time from symptom onset of 18 months or less – a prespecified group characterized by rapid disease progression – Pridopidine had a greater impact.
  • While sample sizes were small in the subgroup analyses, the magnitude of the effects seen – as well as their consistency – add to the body of evidence suggesting that Pridopidine may have an impact on patients with ALS. The results support further evaluation of pridopidine in a phase 3 study, which is currently being planned.

Discussion Themes

HEALEY is a phase 2 platform trial, so the anticipation is that drugs that show promise will go into larger trials. It’s important to note that the size of these individual arms are as large or larger than other treatment programs that have led to FDA approval in the past.

The research team’s inclusion criteria allows for a broad selection of participants, with disease onset up to 3 years and a minimal vital capacity of 50%. This is broader than other ALS trials, developed with the need for ALS patients to have access to a broader range of experimental therapeutics in mind.

Participants are drawn to this platform because there is a smaller chance that they’ll receive a placebo. However, they must be on board with receiving any of the drugs being studied. This is a different discussion than people are used to having in trial recruitment, where typically a single drug or drug combination is being studied. Investigators must explain that all of the drugs are viable options.

Adaptation is a challenge; changes to the protocol are a big commitment. After a change is made, data from the past placebo groups can’t be used.

Grand Rounds March 28, 2025: A Cross-Sectional Study of GPT-4–Based Plain Language Translation of Clinical Notes to Improve Patient Comprehension of Disease Course and Management (Anivarya Kumar, BA; Matthew Engelhard, MD, PhD)

Posted on by Sophia Ramirez

Speakers

Anivarya Kumar, BA
Fourth-Year Medical Student
Duke University School of Medicine

Matthew Engelhard, MD, PhD
Assistant Professor, Department of Biostatistics & Bioinformatics
Duke University School of Medicine

Keywords

Health Literacy; Large Language Models; Artificial Intelligence; Electronic Health Records

Key Points

  • Limited health literacy (HL) has tangible effects on morbidity and mortality: it’s associated with higher rates of hospital admissions and readmissions; medication nonadherence; healthcare costs; and all-cause mortality. 9 in 10 adults have limited HL, and rates are 2 – 3 times lower in marginalized populations.
  • 71% of patients report accessing their electronic health records (EHRs) to read documentation from their clinical visits, particularly the discharge summary notes (DSNs). But clinical notes have low levels of readability, hindering patients’ ability to engage in shared decision-making.
  • The research team looked at whether a Generative-Pre-trained-Transformer-4 (GPT-4)-based plain language translation of DSNs could improve patient comprehension of disease course and management.
  • 533 patients, recruited from a pool of EHR users, were randomly assigned 4 DSNs to assess. After reading the DSNs – 2 translated into more accessible language, 2 untranslated – patients answered questions assessing their objective comprehension, subjective comprehension, confidence, and time spent on each DSN.
  • Compared to the untranslated DSNs, objective understanding of the translated DSNs increased by 6.1%; subjective understanding increased 18%; confidence increased 45%; and average time spent with the DSNs decreased 51%.
  • The research team concluded that GPT translation of DSNs significantly improved patient comprehension of disease course and management and optimized time spent reading them. The effect was significantly greater in marginalized populations with historically low health literacy, reducing the gap in comprehension scores between patient populations.
  • Limitations included the use of standardized DSNs as opposed to real-world DSNs; the use of MyChart when enrolling patients, leading to a participant group with a higher baseline HL; and the modest number of Hispanic patients enrolled in the study.
  • Race is a significant and independent factor for HL. Preliminary data suggests that GPT translation can help close this gap. The research team identified this as an area for further study.

Discussion Themes

While discharge instructions alone can be great for providing patients with action items, they lack some of the context that DSNs can provide, lending the patient a more complete understanding of their condition.

The advantages of providing pre-generated materials, as opposed to pointing patients to an large language model (LLM) like Chat GPT for a more interactive explanation of their condition, include the potential for screening by a healthcare professional and less of a burden on the patient.

The study team ended up favoring “semantically-focused” translations over translations that focused solely on simplifying the language or avoiding jargon. When the LLM was asked to focus on semantics, it was more likely to define concepts and their implications.

Health literacy and reading level are not necessarily on par, and patient-centric or accessible language/LLMs are very important to consider. This may require further investigation, e.g. through qualitative interviews.

Grand Rounds March 21, 2025: Generative Artificial Intelligence in Clinical Trials: A Driver of Efficiency and Democratization of Care (Alexander J. “AJ” Blood, MD, MSc)

Posted on by Sophia Ramirez

Speaker

Alexander J. “AJ” Blood, MD, MSc
Associate Director, Accelerator for Clinical Transformation Research Group
Instructor of Medicine at Harvard Medical School
Cardiologist and Intensivist
Brigham and Women’s Hospital

Keywords

Artificial Intelligence; Cost; Large Language Models; Enrollment; Eligibility; Recruitment

Key Points

  • The Accelerator for Clinical Transformation (ACT) is a research group that seeks to use emerging technology to try and expand access to healthcare and improve quality and quantity of healthcare delivery. They focus on team-based models and scalable applications.
  • It’s becoming more expensive and time-consuming to move a drug from the clinical trial stage to approval. Patient recruitment is the leading driver of costs in clinical trials, and 55% of trials that fail to complete cite low accrual rate as the reason for study termination. There’s pressure from industry to conduct clinical trials in a way that is faster, cheaper, and better for both the patients and the research environment.
  • ACT conducted a pilot study in which they embedded a Large Language Model (LLM) tool called RECTIFIER into an active clinical trial of patients with heart failure. RECTIFIER is an AI-powered, comprehensive software application able to ask and answer questions about unstructured clinical data. In a pilot study, RECTIFIER determined patient eligibility with higher accuracy and specificity than study staff, indicating its potential to streamline screening.
  • LLMs are the engines that power the software. There are two key challenges that need to be taken into consideration to use these tools effectively: 1) there’s a content window – a limit to the amount of Electronic Health Record (EHR) data you can pull in; and 2) Using LLMs is expensive.
  • Following up on the pilot study results, ACT conducted a prospective randomized controlled trial: The Manual Versus AI-Assisted Clinical Trial Screening Using LLMs (MAPS-LLM) trial. MAPS-LLM compared two methods for analyzing a randomized pool of potentially eligible participants: manual review by study staff, and RECITIFIER-augmented review by study staff. Their primary endpoint was eligibility determination.
  • They found that AI-assisted patient screening using the RECTIFIER system significantly improved eligibility determination and enrollment compared with manual screening in a heart failure clinical trial.
  • ACT concluded that implementing AI-assisted tools like RECTIFIER can enhance clinical trial efficiency, reduce resource utilization, and promote equitable recruitment, potentially leading to faster trial completion and earlier patient access to novel therapies. Generative AI is likely to play a significant role in the future of clinical trials.

Discussion Themes

Study staff in the MAPS-LLM intervention arm were able to direct more time and effort towards contacting patients and managing patients with the time they would have spent reviewing charts and manually screening the EHR.

The rate of eligibility between the two arms was equivalent; the difference was, the AI-augmented group was able to assess twice as many potentially eligible patients.

While this tool can do a lot of analytical work, a human element will be essential to utilizing it effectively and to bringing “human intelligence” to participant enrollment.

The ACT team has started to pilot this technology in other disease areas, including cardiology more broadly, endocrinology, oncology, and gastroenterology.

Grand Rounds March 14, 2025: Spillover Due to Constraints on Care Delivery: A Potential Source of Bias in Pragmatic Clinical Trials (Sean Mann)

Posted on by Sophia Ramirez

Speaker

Sean Mann
Senior Policy Analyst
RAND Corporation

Keywords

Development Economics; Spillover; Bias; Pragmatic Clinical Trials

Key Points

  • Individually randomized, parallel-group embedded pragmatic trials randomly assign patients to a new healthcare intervention or to a control group that receives some form of usual care. They take place in real-world health settings, where clinical resources can be scarce.
  • If an intervention increases patient use of scarce resources – e.g., appointments, hospital beds, provider attention – this can reduce the availability of those resources for the control group and bias results. This is known as negative spillover, or crowding out, in the field of development economics. However, spillover due to resource constraints is absent from the major frameworks that inform clinical trial methods.
  • 4 conditions must be met for spillover to affect trial results: 1) Resources are shared across trial arms 2) Care delivery resources are constrained or limited in some way 3) The intervention being studied affects utilization of the scarce resource 4) Having fewer resources available to care for patients affects their health outcomes. These conditions are fairly common in pragmatic trials.
  • Spillover is not just a source of bias; it has implications for patient safety. If negative spillover occurs, patients who are assigned to a control arm are no longer receiving usual care as it’s commonly understood. Mann provided strategies that research teams can use to detect spillover or avoid it entirely, including utilizing a cluster-randomized design or a demand-balanced trial design.
  • Spillover remains hypothetical, and positive spillover is also possible. Study results affected by spillover can still be a valid indication that an intervention affects care utilization.
  • In many pragmatic trials, spillover is likely negligible. Mann and his colleagues at Rand are trying to help determine when spillover concerns should prompt changes to study design or justify additional data collection and analysis. They recently published a paper in Trials that explores the issue in further detail: Mann, S. Negative spillover due to constraints on care delivery: a potential source of bias in pragmatic clinical trials. Trials 25, 833 (2024). https://doi.org/10.1186/s13063-024-08675-9

Discussion Themes

While the Cochrane Risk of Bias Tool v. 2.0 (RoB 2) can be useful for looking at disparities in the level of care provided to the control group versus the intervention group, it exclusively looks at bias due to lack of blinding.

IRB applications could be expanded to include further questions about how resources are being used at a study site, how a study may potentially increase demands on those resources, and how it might affect others who are receiving those health services.

Clinical settings aren’t necessarily a zero sum game; negative spillover will apply in certain contexts, while in others the presence of an intervention will lead to positive spillover or no effect.

Grand Rounds March 7, 2025: A Trial of a “Kidney Action Team” for Hospitalized Patients with Acute Kidney Injury (F. Perry Wilson, MD MSCE)

Posted on by Sophia Ramirez

Speaker

F. Perry Wilson, MD MSCE
Associate Professor of Medicine and Public Health
Director, Clinical and Translational Research Accelerator
Yale University
New Haven, CT

Keywords

Electronic Alerts; Acute Kidney Injury; Action Team

Key Points

  • Acute Kidney Injury (AKI), or abrupt decline in kidney function, is common, affecting about 15% of hospitalized patients. A hospitalized patient with AKI has an inpatient mortality rate 8.5% higher than average. However, early recognition and nephrologist involvement can improve clinical outcomes.
  • First, the research team conducted a multicenter, parallel-group, randomized controlled trial (RCT) to test the effect of an electronic alert system on best practice utilization and three clinical outcomes (progression of AKI, dialysis, and death). The pragmatic trial, Electronic Alerts for Acute Kidney Injury Amelioration AKA ELAIA-1, instituted “best practice alerts” in the electronic medical record.
  • The Grand Unified Theory of Electronic Alerts states that alerts can’t work if 1) the provider already knows what’s wrong with the patient; 2) they don’t care about what’s wrong with the patient; 3) they have no specific action to take in response; or 4) the action doesn’t matter – i.e., it doesn’t change outcomes.
  • For ELAIA-2, the second iteration of the trial, the researchers focused on one tenet of this theory: alerts should be tied to actions. This open-label, parallel group RCT used alerts to encourage cessation of kidney-relevant medications – NSAIDs, RAASi, and PPI. They looked at rates of cessation of one of those medications and clinical outcomes (progression of AKI, dialysis, and death).
  • Though they found that automated alerts for AKI can increase medication cessation, there was limited evidence that these alerts would change clinical outcomes. The rate of discontinuation was highest for PPIs, which are an under-recognized contributor to AKI. Alerts may be beneficial in physicians whose patients are receiving PPIs – a population that tends to be sicker.
  • These findings led to a new hypothesis: AKI is heterogenous, caused by many factors. The research team sought to customize recommendations given to providers. To this end, they created a Kidney Action Team (KAT) with the goal of improving in-hospital mortality and AKI progression.
  • The KAT-AKI trial, a multicenter RCT administered across 2 hospital systems, looked at the proportion of recommendations implemented in 24 hours and clinical outcomes (progression of AKI, dialysis, and death). 34% of KAT recommendations were implemented within 24 hours in the intervention arm compared to 24% in usual care. However, this also did not have an effect on clinical outcomes.
  • The research team concluded that more personalized AKI alerts could potentially lead to better outcomes.

Discussion Themes

An optimized user interface – e.g., delivering information at the right place in a provider’s work flow, catching them at the right time – may further increase the adoption of best practices.

There’s some doubt about the nephrotoxicity of RAAs. In the ELAIA-2 study, though there were higher rates of RAA discontinuation in the intervention group, the clinical outcomes were nearly identical.

The heterogeneity of AKI patients interfered with the intervention’s effectiveness. To improve clinical outcomes, researchers may want to devote resources to prevention rather than response.

Grand Rounds February 28, 2025: Behavioral Economic and Staffing Strategies To Increase Adoption of the ABCDEF Bundle in the Intensive Care Unit (BEST-ICU): Protocol, Challenges, and Major Updates (Eduard Vasilevskis, MD, MPH; Michele C. Balas PhD, RN, CCRN-K, FCCM, FAAN)

Posted on by Sophia Ramirez

Speakers

Eduard Vasilevskis, MD, MPH
Professor of Medicine
Department of Medicine, Division of Hospital Medicine
University of Wisconsin-Madison

Michele C. Balas PhD, RN, CCRN-K, FCCM, FAAN
Associate Dean of Research
Dorothy Hodges Olson Distinguished Professor of Nursing
University of Nebraska Medical Center College of Nursing

Keywords

Intensive Care; ICU; Implementation; Evidence-Based Practices

Key Points

  • With recent increases in survivorship for Intensive Care Unit (ICU) patients has come the rise of Post-ICU Syndrome, or PICS. PICS is characterized by cognitive and physical impairment; financial toxicity; and family impacts. Some of the factors associated with PICS are modifiable: Sedation use, for example, immobility, and mechanical ventilation.
  • A set of evidence-based best practices based on these modifiable factors are encapsulated in the ABCDEF Bundle: Assess, prevent, and manage pain; Both spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs); Choice of analgesia and sedation; Delirium: assess, prevent, and manage; Early exercise and mobility; and Family engagement.
  • In a study of 68 ICUs, patients treated with all elements of the ABCDEF bundle in a given day had better outcomes. The next day, they were 70% less likely to be on a mechanical ventilator; 65% less likely to be in a coma; and 40% less likely to be delirious. Though there wasn’t a significant impact on pain, the likelihood of being discharged from the hospital increased by 20%.
  • We have a safe and efficacious set of evidence-based practices that people can deliver in the ICU. However, many of them are not being delivered to critically ill patients. And they’re not being delivered due to numerous implementation challenges clinicians experience in everyday care.
  • The Behavioral Economic and Staffing Strategies to Increase Adoption of the ABCDEF Bundle in the Intensive Care Unit (BEST-ICU) study aims to evaluate 2 strategies grounded in behavioral economic and implementation science theory to increase adoption of the ABCDEF bundle. The strategies target a variety of ICU team members and known behavioral determinants of ABCDEF bundle performance.
  • BEST-ICU is ongoing. The hybrid type III effectiveness-implementation pragmatic trial will take place in 3 hospitals and 12 ICUs across 33 months. The study team will monitor fidelity through real-time monthly tracking of audit and feedback information and through direct observation by Registered Nurse (RN) Implementation Facilitators.
  • Over 3,000 work intensity surveys have already been completed, split between RNs and non-nurses. Given the intensive nature of these surveys and the dearth of studies investigating work intensity in the ICU, this alone will be a notable contribution to the literature.
  • The research team outlined some of their sticking points around dashboard development and data acquisition/sharing, as well as how they’ve addressed these challenges. Solutions included the standardization of definitions for bundle process elements and engagement of clinical, operational, and legal leadership from the University & Health system.

Discussion Themes

Patient-reported pain was the only outcome that didn’t improve following full implementation of ABCDEF bundle. Dr. Balas noted that patients who aren’t in a coma anymore can then report pain. Dr. Vasilevskis pointed out that the same goes for delirium, which is far preferable to coma from a mortality perspective.

Dr. Balas suggested that a patient who is more cognitively engaged and able to report pain is actually in a better spot, as it enables medical staff to treat them.

Grand Rounds February 21, 2025: Texting for Behavior Change: Lessons Learned Across 2 Interventions to Improve Chronic Care Management (Michael Ho, MD, PhD; Sheana Bull, PhD)

Posted on by Sophia Ramirez

Speakers

Michael Ho, MD, PhD
Kaiser Permanente Colorado

Sheana Bull, PhD
University of Colorado School of Public Health

Keywords

Text Messaging; Artificial Intelligence; Chatbots; Health Behaviors

Key Points

  • Ample evidence now exists demonstrating the benefit of using text messaging in support of health behavior and access to care. It’s ubiquitous, increasing reach; theory in message design is impactful; and it can improve adherence to medical appointments and health behaviors.
  • Two NIH Collaboratory Trials, Nudge and Chat 4 Heart Health (C4HH), test the effectiveness of text messaging interventions to support behavior change. Nudge randomized patients to receive usual care, generic texts, behavioral texts, or behavioral texts plus chatbot messages. Their primary outcome was medication adherence.
  • C4HH, the subsequent trial, is randomizing patients to receive a generic text message curriculum; an AI chatbot messaging curriculum; or AI chatbot messages plus proactive pharmacist support. Their primary outcome is cardiovascular risk factors, as measured by the American Heart Association’s “Life’s Essential 8” adherence.
  • Nudge used an opt-out consent approach where CC4H used an opt-in consent approach. In the former, the research team noted, patients who identified as Black, Hispanic, and primary Spanish speakers were more likely to remain in the study. An opt-out approach in the appropriate context may be a way to diversify clinical trial populations and improve external validity of results.
  • The use of AI chatbots allows users to generate questions in their own words and the system to retrieve a response from a closed, curated library.
  • Message engagement is key to text messaging interventions. Participants in the Nudge study who were randomized to optimized texts had more questions. Questions were related to medications, refill logistics, and costs. The study team hypothesizes that the optimized texts may have led to greater patient engagement, and therefore more questions about their medications.
  • Over 12 months, the Nudge study found no significant difference in the rates of prescription refills, between the 3 intervention arms and usual care. CC4H is ongoing, and will send a higher volume of messages in an effort to engage patients and change patient behavior.
  • So far, the top 5 topics in messages initiated by C4HH participants have been healthy eating, physical activity, managing cholesterol, quitting smoking, and medication management.

Discussion Themes

The study team had to be very careful to ensure that patient health data, including cell phone numbers and the messages sent, were encrypted. Vendors and phone carriers were not able to access this data and it was not stored on their servers.

One of the challenges they encountered was that their systems weren’t integrated into the health care organizations’ pharmacies or electronic health records. The integration piece will be key to any future sustainability.

As technology evolves significantly over the course of, say, a 5-year study, developing the skillset to utilize interactive interventions or a SMART design could be helpful for investigators interested in conducting research in this area.

Grand Rounds February 14, 2025: A Clustered-Randomized Stepped-Wedge Pragmatic Trial to Enhance Goals-of-Care Communication for Older Adults with Cancer (ACP PEACE) (Angelo Volandes, MD, MPH; James A. Tulsky, MD)

Posted on by Sophia Ramirez

Speakers

Angelo Volandes, MD, MPH
Vice Chair of Research, Department of Medicine
Dartmouth Health
Professor of Medicine, Geisel School of Medicine

James A. Tulsky, MD
Poorvu Jaffe Chair, Department of Supportive Oncology
Dana-Farber Cancer Institute
Professor of Medicine, Harvard Medical School

Keywords

Palliative Care; Goals of Care; Advanced Care Planning; Cancer; Oncology

Key Points

  • Cancer is one of the leading causes of death for people age 65 and older, and patients have diverse preferences for medical care. However, most patients are unfamiliar with advance care planning (ACP) and clinicians are often unprepared to discuss it. Ultimately, many patients do not have goals-of-care (GOC) conversations with their providers, leading to billions of dollars in unwanted (and painful) interventions.
  • The Advance Care Planning: Promoting Effective and Aligned Communication in the Elderly (ACP PEACE) trial tested a pair of interventions – ACP Decisions and Vitaltalk – to help prepare clinicians and elderly patients to have GOC conversations.
  • ACP Decisions consists of short, accessible video decision aids that aim to help patients share in decision making. They offer a scalable, speedy strategy to improve GOC, and were associated with an increase in GOC conversations in smaller trials.
  • Vitaltalk is a communication training for clinicians discussing goals of care in serious illness. It is evidence-based, designed around the idea that learning new skills requires practice, observation, and feedback. Vitaltalk is associated with documented improvement in conversation quality.
  • ACP PEACE was a large, pragmatic, multicenter stepped-wedge trial that compared an intervention period and a control period, AKA usual care. The trial occurred across three healthcare systems (A, B, and C) and began with 36 clinics, 6 months before the onset of the COVID-19 pandemic. In April 2020, the trial was re-randomized across 29 clinics.
  • Participants were 65 and older with advanced cancer. The primary endpoint was documentation of a GOC conversation.
  • The study team found a 6.8% increase in ACP documentation during the intervention period, driven by a 6.9% increase in documented GOC conversations. There was no statistically significant increase in documentation of referrals to palliative care or to hospice. There was no statistically significant decrease in the limitation of life-sustaining treatments.
  • The results varied significantly by healthcare system. In Healthcare System A, documentation decreased by nearly 8% over the course of the study – whereas in Healthcare Systems B and C, it increased by 11% and 8.3%, respectively.
  • The researchers considered whether GOC conversation documentation was the right target. There has been a conversation in palliative care about how helpful these documents are; goal-aligned medical care (goal concordance) might be a better target.
  • Volandes and Tulsky noted that the approach to pragmatic clinical trials should better reflect the shifting nature of healthcare in the U.S. Researchers in this space must be better stewards of limited resources, so that interventions are sustainable and outcomes are useful to decision-makers.

Discussion Themes

Efforts to enhance rigor in intervention development may prevent effective interventions from getting to scale. Leaders in this space need to make it easier to get implement and test interventions, even if that means they aren’t perfectly optimized.

Right now, researchers are disincentivized to move quickly during the UG3 start-up year. Funders could incentivize research teams to move more quickly, e.g., by encouraging them to use leftover funds to conduct another study.

People in healthcare don’t see 10 years ahead – they see 1 to 2 years ahead. If pragmatic trials are meant to inform decision makers, it’s incumbent on researchers to provide the information healthcare systems need in a manner that is not outdated.

Ongoing partnerships with appropriate health systems can provide a platform for more efficient intervention implementation across different areas of healthcare. For instance, the research team conducted three other trials in Healthcare System C within the time it took them to complete ACP PEACE.