Ankeet S. Bhatt, MD, MBA, ScM
Cardiologist, Kaiser Permanente San Francisco Medical Center
Research Scientist, Kaiser Permanente Northern California Division of Research
Assistant Professor, Kaiser Permanente Bernard J. Tyson School of Medicine
Adjunct Professor, Stanford University School of Medicine
Keywords
Vaccination; Learning Health System; Implementation Science; Nudges; Influenza; Cardiovascular
Key Points
Every year, influenza leads to over 500,000 deaths and 3-5 million severe cases globally. It increases the risk of cardiovascular (CV) events like myocardial infarction and heart failure. Though health guidelines strongly recommend annual influenza vaccination, rates remain suboptimal globally and persistent inequities exist. There’s an urgent need for novel, effective, and scalable strategies to improve influenza vaccination rates.
The KP-VACCINATE trial is one of the largest ever conducted, randomizing over 3.6 million patients in under 30 days. It included several pragmatic elements, such as coordination with existing vaccine promotion efforts; randomization performed by operational health system teams; and endpoint capture fully embedded in the electronic health record.
The study team assessed the effect of a cardiovascular-focused nudge communication on influenza vaccination rates and found that there was no effect. Despite the negative results, the trial establishes that pragmatic and rapid randomization of communication strategies is operationally feasible at scale with routine healthcare workflows in the US.
Discussion Themes
The study team targeted a larger-than-usual population in order to 1) demonstrate the feasibility of randomization within a large-scale health system, and 2) be well-powered for subgroup analyses that could help tailor future interventions.
Dr. Bhatt viewed the negative result as an illustration of the importance of design and context for interventions based in behavioral science, rather than an indication that nudges are ineffective.
Future directions may include involvement of the broader care team, with primary care providers and specialty providers playing a potentially critical role in nudging patients towards vaccine uptake.
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.
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
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.
