You studied neuroscience as an undergraduate and are now a clinical expert in ethical AI. How did your career path unfold?

Both of my parents are internal medicine physicians, so I grew up seeing firsthand how meaningful and fulfilling a career in clinical medicine can be. At the same time, I was always deeply interested in mathematics and technology.

As an undergraduate at Massachusetts Institute of Technology, one formative experience was a course I took in graph theory, focused on its ability to reveal complex patterns in data — an approach that translates to understanding medical data and potentially supporting better clinical decision-making. During medical school, I also completed an M.B.A., which reshaped how I viewed healthcare and the need for systems-level change. After medical school and residency, I completed a master’s degree in bioinformatics to further refine how I might drive some of these systematic changes. In my case, I was interested in using data and technology to improve patient care.

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When I joined Mayo Clinic as a clinician, I also started working with Mayo Clinic Platform. As a Mayo Clinic Platform medical director, I began engaging regularly with startups presenting their AI-driven solutions. Physicians must sort through hundreds of AI tools to determine which one is most suitable to their needs. This led me to ask critical questions: How do we ensure that these tools are responsibly developed and deployed from start to finish? How do we clearly communicate this complex information to healthcare providers so that they can adopt these tools with confidence and trust?

Synapse is your current research and development project. Can you tell us what this tool is and how it will impact care for patients?

Synapse is a clinical decision support tool we are building to help clinicians make sense of complex patient information. From the start, we are designing it with responsible AI principles in mind. That means being clear about how it works and building in monitoring to check for accuracy and bias.

At its core, Synapse uses a knowledge graph, which is a way of mapping relationships between pieces of information. A knowledge graph connects things like symptoms, diagnoses, medications, test results and social factors so we can see how they relate to one another. By organizing information this way, the tool can surface insights that are tailored to the specific patient in front of the clinician, rather than offering a one-size-fits-all answer.

Technology has so much potential to positively impact our patients, providers and workforce if done methodically, ethically and with patient outcomes at the forefront of the conversation.

— SONYA MAKHNI, M.D., M.S.

Instead of just saying “treat atrial fibrillation this way,” Synapse can recognize that this particular person is, say, a 40-year-old pregnant patient with specific comorbidities, and then combine what the guidelines recommend with actual outcome data from similar patients we’ve treated.

Ultimately, the goal is to provide clinicians with tools they can immediately understand and trust while also revealing connections we might have missed, like social determinants or environmental factors that impact health.

What makes Mayo Clinic a unique leader in the conversation around ethical AI?

Physicians and researchers at Mayo Clinic are empowered by the breadth of patient data available to them and the institution’s unparalleled clinical expertise. Through Mayo Clinic Platform, we have access to the largest curated, de-identified clinical dataset in the world, so we have a massive base to pull from when it comes to developing and testing new AI tools and assessing them for bias.

Mayo Clinic clinicians are truly the best of the best, particularly when it comes to treating serious or complex disease. I am grateful that Mayo Clinic encourages thoughtful exploration and innovation in this space. Technology has so much potential to positively impact our patients, providers and workforce if done methodically, ethically and with patient outcomes at the forefront of the conversation. As a global leader in healthcare, it is essential that Mayo Clinic drives these important conversations.

The post Building Ethical AI With Sonya Makhni, M.D., M.S. appeared first on Mayo Clinic Magazine.

I have said that “data + people = new knowledge,” and “new knowledge = more cures.” AI is now the exponent in these equations. It compounds the impact of data and people by helping us see signals earlier, validate them faster and move discoveries into practice at greater speed. But this can only happen when the foundation is the right one. Healthcare data must be ingested, enriched, vectorized, governed and connected on a platform. Only then can we use AI at scale to move from observation to insight, from insight to trial, and from trial to more cures for patients. 

At Mayo Clinic, this is the purpose of Mayo Clinic Platform, which now includes 54 million de-identified patient lives across four continents. The goal is to help researchers and solution developers find signals across real-world clinical experience and test those insights quickly. Having the right data architecture on the right platform safely available to humans and agents is showing results. 

One of the clearest examples is clinical trials, essential to developing more cures. A modern data architecture can make clinical trials faster, smarter and more targeted. For example, using Platform data, Joseph C. Ahn, M.D., and his team have simulated disease progression in alcohol-associated hepatitis against 10,000 synthetic patients and 1,400 actual patients, with nearly identical survival patterns. In another example, Cui Tao, Ph.D., and Nansu Zong, Ph.D., and their team fully emulated a randomized trial comparing warfarin and aspirin using Platform observational data. Preparing and validating the dataset took months, compared with 12 years for the original trial. Trial design, end points and statistical power should be highly informed by AI run on a modern platform data architecture before most, if not all, large clinical trials are initiated. 

Every data point in healthcare should serve one purpose: improving outcomes and developing more cures for patients.

— Gianrico Farrugia, M.D.

Within orthopedic surgery, Matthew P. Abdel, M.D., and his team leveraged Platform clinical data to help predict surgical site infections before total knee replacement surgery. They built a virtual patient cohort and generated a synthetic control arm to develop an AI-driven predictive model that could identify high-risk patients before surgery and enable the care team to intervene early. 

A similar approach is changing research for brain tumors. Our chair of Neurosurgery in Rochester and chief medical officer for Mayo Clinic Platform, Gelareh Zadeh, M.D., Ph.D., had previously spent five years building a cohort of a few thousand patients with brain tumors. Using Platform, the team could immediately begin working with a population approaching 4,000 patients with glioblastomas and 5,000 patients with meningiomas, with an average of 16 years of longitudinal data per patient, as well as 5 million clinical notes, 15,000 MRIs and thousands of structured data points.  

This scale and depth of data create opportunities to uncover patterns that would otherwise remain hidden. For example, Dr. Zadeh’s lab is studying whether blood sugar levels and seizure medications are linked to better outcomes for brain tumor patients. Early analyses suggest that controlling glucose levels may help patients with brain cancer and possibly other cancers, and they also suggest that certain seizure medications — such as lamotrigine and levetiracetam — may be associated with longer survival in patients with malignant brain tumors. These findings are strong enough to influence patient care decisions and have led to two clinical trials. 

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We also need to link molecular biology to patient outcomes, and that is the purpose of our Bioresource and Research Data Atlas initiatives. Bioresource collects samples like blood, plasma and tissue and connects them to detailed patient information. Currently, more than 6.6 million samples from more than 219,000 patients have been brought together into one centralized digital system. Our Research Data Atlas then brings all this information together — biospecimens, patient data, lab results, imaging and more — into one place so researchers can work across genomics, spatial biology and cellular imaging in one environment. 

These are just a few examples that demonstrate why rearchitecting healthcare data should be a global imperative requiring investments at a national level. It is one of the most important steps we can take to accelerate cures. AI is the exponent, but our data architecture is the base — and now we must remake it for a new era of inquiry. 

This article was originally published on LinkedIn on June 30, 2026. 

The post Rearchitecting Healthcare Data for More Cures appeared first on Mayo Clinic Magazine.

Information overload continues to vex clinicians. The sheer quantity of data available in a patient’s electronic health record (EHR) alone makes it almost impossible to obtain a comprehensive picture of their condition. And while artificial intelligence-enabled algorithms are helping to summarize these reports, it’s not enough.

One solution is to develop a visualization system that quickly puts all the patient’s most important information at a clinician’s fingertips. That information needs to include not just content from the EHR but details on their genetic makeup and environmental exposure to toxins, input from wearables, published systematic reviews and meta-analysis, and so much more. That’s exactly what knowledge graphs (KGs) are designed to do. The latest research demonstrates that these tools are accomplishing that feat. 

What Is a Knowledge Graph? 

A KG is “a network of real-world entities — i.e., objects, events, situations or concepts — and illustrates the relationship between them. This information is usually stored in a graph database and visualized as a graph structure, prompting the term knowledge graph.”   

These visualization tools have a long history in healthcare, dating back to the famous graphic created by the English physician John Snow in the 1800s. As Figure 1 illustrates, he was able to link cholera outbreaks to water pumping stations in London. That connection became crystal clear when one looked at his map. The areas in the city circled in red represented the greatest number of cholera cases, most of which clustered around the Broad Street pump, circled in green.  

The cause-effect relationship between microbe-saturated water and cholera may be obvious to 21st century clinicians, but to Dr. Snow’s colleagues, it was a revelation. Similarly, clinicians and researchers who are deploying knowledge graphs are seeing hidden insights that are having an impact on patient care. 

Why Knowledge Graphs Are Important 

To date, there’s evidence to show that KGs are playing an important role in repurposing drugs so that they can be used to treat conditions they were not originally approved for. They can also improve clinical decision support when linked to EHR data, enabling them to detect hidden patterns, which in turn improve diagnostic predictions and treatment options. There’s also reason to believe KGs can support precision medicine and contribute to clinical research by generating better hypotheses and improving the reasoning process. 

These impressive accomplishments take advantage of a KG’s basic structure, which includes nodes, edges and labels — the so-called triple. As Figure 2 illustrates, nodes can include various types of data, including disease phenotypes, exposure to specific environmental factors, drugs and diet. Edges represent the relationships between these nodes, and labels can be the text used to explain the relationships. They can be as simple as a caption for a table or be more complex, referring to variables plotted on an X and Y axis. 

Figure 2 comes from a group of investigators who created a KG called SPOKE, an acronym for scalable precision medicine open knowledge engine. Their system took advantage of 41 specialized databases, 21 types of nodes and 55 types of edges. These data sources included content from molecular and cell biology, pharmacology, and clinical practice. Morris et al explain: “SPOKE has been used for a variety of biomedical applications including drug repurposing … disease prediction and interpretation of transcriptomic data … among others. More recently, we developed an algorithm to embed electronic health records onto SPOKE, which, when combined with machine learning techniques, enables a wide range of applications relevant to precision medicine.” 

Ziad Obermeyer, M.D., a professor at the University of California, Berkeley, once said: “The complexity of medicine now exceeds the capacity of the human mind.” With the flood of new data resources now available, that complexity has grown exponentially. Well-constructed KGs are “connecting the dots,” helping clinicians manage this information overload. As they find their way into routine medical practice, there’s reason to believe they will improve patient outcomes. 

This article was originally published on Mayo Clinic Platform.

The post A Deeper Dive Into Knowledge Graphs appeared first on Mayo Clinic Magazine.

Mayo Clinic is leading patient-centered healthcare transformation through our Bold. Forward. strategy, which aims to accelerate the discovery, translation and delivery of more Cures for both chronic and acute diseases; to Connect people with data to create new knowledge and deliver scalable, end-to-end solutions; and to Transform healthcare by creating its first comprehensive, scalable, artificial intelligence (AI)-enabled care transformation platform — Mayo Clinic Platform.  

To accomplish true healthcare transformation, we are also transforming our physical spaces through Bold. Forward. Unbound., which reimagines space across all of Mayo Clinic’s campuses by introducing new facilities that combine innovative care concepts and digital technologies, blending inpatient and outpatient care to deliver and scale healthcare in entirely new ways.  

To envision what care can look like in 2030, let’s trace a potential patient’s journey through Mayo Clinic of the future.  

THE PATIENT EXPERIENCE OF THE FUTURE 

Meet Emily, a patient who begins her Mayo Clinic experience hundreds of miles away from Mayo Clinic in Rochester. She is seeking treatment for end-stage liver disease complicated by severe aplastic anemia, a condition in which the bone marrow stops producing enough new blood cells. This complex diagnosis requires both a liver transplant and cell therapy for bone marrow failure. Through a virtual consultation that includes her local doctor and Mayo Clinic specialists, her care team conducts a thorough evaluation, develops a diagnostic and treatment plan, and establishes a trusted, warm relationship with her. 

When it’s time to leave home to travel to Mayo Clinic, Emily receives digital directions, parking instructions and a personalized itinerary through the Mayo Clinic digital interface. The digital interface provides step-by-step navigation from home to her assigned parking ramp, tailored to her appointment and mobility needs. Her itinerary, care team photos and contacts, and visit details are all available in the app, reducing uncertainty and supporting a seamless experience. 

Upon her arrival, a dedicated support team easily recognizes and greets Emily, guiding her to her destination and ensuring she feels confident and cared for at every step. While on campus, Emily becomes part of Mayo Clinic’s “Interconnected Complex Care Neighborhood,” a unique care environment specifically designed for patients with serious and complex conditions like Emily’s.  

Unlike traditional healthcare settings where patients navigate between disconnected departments across a campus, neighborhoods bring together services in one centralized, welcoming environment. The neighborhood features strategically connected, flexible spaces — from the initial consultations to treatment planning to recovery support. These spaces can be reconfigured based on evolving needs. Co-located diagnostic and treatment options mean Emily receives her imaging, lab work and even procedures without going to another building. Most importantly, the neighborhood includes comfortable spaces where she and her family can connect with other patients facing similar journeys, creating a supportive community during her treatment.

Emily’s patient room is filled with natural light and an ergonomic layout, creating a calming environment for Emily and an efficient workspace for her care team. Before caregivers enter her room, a digital entryway display provides instant access to her personal information, with badge scanning for confidentiality. Robotic assistants automate supply delivery for her needs and even deliver her in-room meals. In front of her, an interactive digital whiteboard displays Emily’s daily schedule, upcoming appointments and progress toward going home. Environmental controls allow Emily to adjust the room’s lighting and sound for her comfort, and advanced camera systems quietly monitor her safety and enable virtual visits with loved ones.

Meanwhile, digital technologies and AI operate seamlessly in the background to support Emily and her care team, enhancing rather than interrupting human connections. For example, AI optimizes appointment timing across multiple specialists and digitally delivers relevant patient education material as her care journey progresses, helping her trust and feel confident in the care plan. AI also assists Emily’s care team by organizing clinical information, transcribing and summarizing relevant conversations, and surfacing relevant clinical insights into her complex medication regimen. This technological support means Emily’s team can deliver both compassionate and data-driven care, and she and her family experience a deeply personal, human touch throughout her treatment, recovery and beyond.

HEALING AT HOME 

After her stay at Mayo Clinic, Emily returns home to continue her post-treatment monitoring, thanks to support from her local doctor and connected devices that allow her team to monitor her health status from afar. Digital AI health tools track her vital signs and medication adherence, with alerts sent to her care team when values fall outside normal ranges, when doses are missed or when AI tools detect changes not visible to the human eye.  

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During her virtual check-ins, the team reviews trends in her data and symptoms to identify changes that might indicate complications, prompting adjustments to her monitoring schedule or in-person evaluations. Between visits, her care team stays connected through digital tools, enabling early intervention when concerning patterns emerge — either through in-person support or care from a distance.  

Emily’s journey in 2030 underscores the transformative power of fully integrated physical and digital healthcare services for both patients and care teams. Mayo Clinic continues to build this future through the choices and investments we make today. 

The post Emily’s Story: A 2030 Patient Experience  appeared first on Mayo Clinic Magazine.

In Minnesota, Bold. Forward. Unbound. in Rochester represents a $5 billion investment over six years. It embodies Mayo Clinic's most significant and forward-looking vision for the future of healthcare by integrating our physical and digital infrastructure and blending inpatient and outpatient care. By 2030, Mayo Clinic will transform the Rochester campus and establish a new model for continuous, digitally integrated, patient-centered care.

Craig Daniels, M.D., critical care physician and medical director for Bold. Forward. Unbound. in Rochester, sat down with Mayo Clinic Magazine’s editorial team to provide an inside look at what fuels Mayo Clinic’s vision and motivates him to help lead this transformation. This interview has been edited for clarity.

How will these spaces be radically different from today’s healthcare environment?

We recognize that patients today experience outpatient, inpatient and virtual care — all delivered in different environments — which can feel quite bumpy. With Bold. Forward. Unbound. in Rochester, we are striving to create an environment where care is seamless for patients.

As we began designing the future of care as a single, integrated experience, we realized that traditional outpatient, inpatient and digital spaces would not work. Our spaces must be flexible to meet patients’ needs wherever they are in their Mayo Clinic healthcare journey.

That means designing buildings that do more than house care — they actively support and enhance it. For example, we are creating care "neighborhoods" where diagnostics, imaging, consultations and procedures occur in one continuous environment, reducing the need for patients to move from place to place.

We're also incorporating healing design principles in every element — spaces filled with natural light, expansive winter gardens, and areas of rest and reflection for both patients and their loved ones. We're integrating technology not as a layer on top, but as an embedded member of the care team: ambient intelligence, robotics, predictive analytics and automation will allow our teams to focus more on the human aspects of caregiving.

At Mayo Clinic, we’ve always understood that the physical environment can shape medical outcomes. Just as Dr. Henry Plummer’s vision for the Plummer Building transformed medicine a century ago, this next generation of care environments will transform how we deliver hope and healing — not just for today, but for the next hundred years.

To fully live our primary value — the needs of the patient come first — we must design our spaces with patients at the center.

— Craig Daniels, M.D.

Why is now the right time for this investment?

Healthcare is at the precipice of transformation. As stewards of Mayo Clinic — the world’s leader in healthcare — we must lead this transformation and make Mayo Clinic and all healthcare better for patients and staff.

We have the tools, the technology and an incredibly talented staff who dedicate their lives to improving patient outcomes and experiences. This allows us to solve increasingly complex problems and deliver more cures. Combined with physical spaces in a new healthcare design centering on patients’ needs, we will elevate our collaborative care model to provide even more hope and healing in the world.

This is the moment when digital technology, artificial intelligence, robotics and human-centered design are converging — and Mayo Clinic is uniquely positioned to bring them together to transform how care is delivered.

Bold. Forward. Unbound. is not just an investment in buildings — it’s an investment in people, in tools that reduce burdens on staff, and in care environments that foster teamwork, innovation and healing. These spaces are designed to be flexible and intelligent, evolving with patient needs and medical advancements over the next century.

We cannot stand still. We have clarity of purpose, a shared vision and the momentum to act. Now is the time.

Tell us more about the “neighborhoods.” What is innovative about this concept?

To fully live our primary value — the needs of the patient come first — we must design our spaces with patients at the center. This means centralizing care teams and services around patients' unique needs. Neighborhoods at Mayo Clinic are innovative care environments designed to transform how healthcare is delivered and to elevate the experience of both patients and staff.

Historically, healthcare buildings have been built around departments and specific services. Think about the fact that almost all radiology equipment is located on the bottom floor of a hospital. This means that patients often need to travel significant distances between appointments for their imaging. This is also largely true for laboratory and specialty care.

By creating care neighborhoods, we'll reduce the distance patients need to travel for appointments and more closely situate things they most often will need. We believe they will experience better care, better outcomes and greater comfort throughout their entire time at Mayo Clinic.

These neighborhoods allow our teams to work side by side, surrounded by familiar spaces and supported by curated digital tools — breaking down the boundaries that have historically separated departments and stages of care. This will foster greater team-based collaboration, continuous innovation, and integration of clinical practice, research and education.

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What motivates you most about this work?

The Mayo-Franciscan “RICH TIES” values — Respect, Integrity, Compassion, Healing, Teamwork, Innovation, Excellence and Stewardship — perfectly align with our primary value of putting patients’ needs first. I am driven to live out our values through the transformational work of Bold. Forward. Unbound.

Even at an incredible place like Mayo Clinic, opportunities like this don’t come along very often, and so I am excited for my colleagues and me to directly contribute to building and experiencing these new spaces that will provide even better care to our patients and care teams.

It’s a generational moment to reimagine how we deliver care, to remove barriers for our staff, and to shape a future where patients receive more seamless, compassionate and innovative care than ever before. We’re building something that will carry forward the mission of Mayo Clinic — not just for today’s patients, but for those we haven’t met yet, and for future staff members who will carry this work forward long after we’re gone. That sense of responsibility — of stewardship — is what drives me.

The post Building Tomorrow’s Healthcare With Craig Daniels, M.D. appeared first on Mayo Clinic Magazine.

Through her groundbreaking Fostering African-American Improvement in Total Health (FAITH!) program at Mayo Clinic, she partners with Black churches to combat cardiovascular health disparities. She has focused her clinical practice and research on making preventive care more accessible and effective for all patients. She sat down with Mayo Clinic Magazine to share her connection to her work.

Growing up, you witnessed firsthand how cardiovascular disease affected your church community. Can you take us back to a specific moment or experience that first sparked your interest in becoming a cardiologist?

The African American church was the foundation of my upbringing in Charlotte, North Carolina. I saw so many people passing away from preventable diseases like heart disease and stroke. It was devastating to see these people who had helped to raise me pass away so early.

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One of the key moments that I remember was when our pastor passed away as a result of diseases that could have been prevented if he’d had the right care and resources. He was the shepherd of the flock, and there was an immediate change in the atmosphere within the church without its leader. I have carried that moment with me. I still honor our pastor, and I hope that I’m honoring him by giving back and making sure we combat the health disparities that affect the community.

You’ve pioneered innovative approaches to community health. What inspired you to create the FAITH! program, and how has it transformed cardiovascular care in underserved communities?

During my public health studies at Johns Hopkins University, I took a course that charged us with coming up with a way to influence health disparities and to promote health within the surrounding Baltimore, Maryland, community. It was a group project, and we jointly created the FAITH! program. We said, “What’s the institution that has been here for centuries that has had the most influence on this population?” and it was the Black church. And we said, “Why don’t we come up with a program that partners with a Black church that can then promote heart health?”

We can seize this moment to have an impact on communities that have been historically overlooked.

— LaPRINCESS BREWER, M.D., M.P.H.

That’s how FAITH! was born. We approached a church that was a stone’s throw away from Johns Hopkins to see if they would be interested in partnering with us. I was able to expand FAITH! to Minnesota when I started my cardiology fellowship at Mayo Clinic, and it has continued to flourish.

Could you tell us about your vision for the future of preventive cardiology? How might your current work addressing health disparities help shape that future?

I’m truly amazed at the advances we’ve had throughout my career in managing chronic diseases and cardiovascular disease risk factors. I am really looking forward to further innovations through technology, including mobile health, wearables and artificial intelligence that can address many of those risk factors early on to prevent people from getting heart disease in the first place. I also am looking forward to preventive cardiology focusing more on the social and behavioral aspects of medicine and public health, particularly the social and structural determinants of health.

We can seize this moment to have an impact on communities that have been historically overlooked. We need to take a holistic approach — looking at patients’ environments and how those environments influence what we are recommending, and if they even have the capacity to engage in many of our recommendations. We need to help address those environmental factors that may promote or hinder them from achieving the best health outcomes.

The post Caring in Community: LaPrincess Brewer, M.D., M.P.H. appeared first on Mayo Clinic Magazine.

Imagine if you could create a digital clone of yourself that can be used to test various treatment options to determine which one is best for your real self. As strange as this may sound, it’s no longer in the realm of science fiction.

What Are Digital Twins?

According to consulting firm McKinsey & Co, “digital twin is a digital replica of a physical object, person, system or process, contextualized in a digital version of its environment. Digital twins can help many kinds of organizations simulate real situations and their outcomes, ultimately allowing them to make better decisions.”

In the inanimate world, that could include a computer model of an airplane that can be used to test out new design concepts or safety features, or a digital twin that simulates the functioning of a piece of machinery that needs an update. It's likely about $73.5 billion will be spent on this technology by 2027, including product, data and system twins.

How Are Digital Twins Used?

A recent study from Scientific Reports illustrates how the technology can be used in a medical setting. Indian investigators enrolled over 1,800 patients with type 2 diabetes and created a digital twin (DT) for each patient that simulated their metabolic status, dietary intake, blood glucose levels and lifestyle habits, enabling the twin to predict a patient’s outcomes.

Shamanna et al explained: “The DT system continuously collects and analyzes data from various sensors and inputs, allowing it to offer personalized dietary and lifestyle recommendations that are precisely calibrated to minimize PPGRs [postprandial glucose response] and improve overall glycemic control. The DT platform will suggest the right food to the right participant at the right time based on current readings. The behavioral nudges provided by the digital twin were accompanied by human coaching.”

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This kind of individualized advice goes way beyond what is offered to patients with diabetes, who typically receive recommendations based on static guidelines and the results of the blood glucose.

The study results suggest digital twin technology works. At one-year follow-up, patients on the program saw significant improvement in hemoglobin A1c levels, with a drop of 1.8%, and 89% achieved a drop to less than 7%, a goal that diabetes experts recommend. They also required significantly less antidiabetes medication and experienced better weight reduction and less insulin resistance.

Similarly, researchers from Yale School of Medicine, University of Oxford and elsewhere have shown that digital twin technology has the potential to transform cardiovascular medicine. Thangaraj et al explain that these cardiac replicas can “enhance disease phenotyping, enrich diagnostic workflows, and optimize procedural planning. Digital twin technology is rapidly evolving in the setting of newly available data modalities and advances in generative artificial intelligence, enabling dynamic and comprehensive simulations unique to an individual. These twins fuse physiologic, environmental and healthcare data into machine learning and generative models to build real-time patient predictions that can model interactions with the clinical environment to accelerate personalized patient care.”

In simple English, the healthcare data they refer to integrates various diagnostic procedures — e.g., ECGs, cardiac imaging and vital signs — with several other multimodal sources, including content from an individual patient’s electronic health record, their lifestyle decisions, and their exposure to climate change, medications, environmental toxins and so on. These resources enable clinicians to make predictions about what is likely to happen to the real patient being profiled. Studies suggest, for instance, that digital twins may help cardiologists estimate an individual’s risk of ventricular arrhythmias if they already have ischemic cardiomyopathy by using certain anatomical substrates, triggers and modulators.

Digital Twins in Action

Phyllis M. Thangaraj, M.D., Ph.D., a cardiology fellow at Yale School of Medicine, and her colleagues provide an example of how the technology might work.

Ms. K, 76 years old, has heart failure, preserved ejection fraction, type 2 diabetes, obesity and hypertension. Her electronic health record offers additional data, including an enlarged left atrium, and a note recommending her diuretic be paused because hydrochlorothiazide has lowered her potassium level and increased uric acid.

Her digital twin model is created based on all her data and runs a simulation of different blood pressure and diuretic drugs, comparing it to other patients with similar profiles. The twin also takes into account the latest guidelines and randomized controlled trials, finally recommending the patient be put back on hydrochlorothiazide and several other medications.

While this scenario is not yet within reach of most healthcare providers, it has the potential to profoundly transform patient care.

This article was originally published on Mayo Clinic Platform.

The post Digital Twin Technology Has Potential to Redefine Care appeared first on Mayo Clinic Magazine.

Gianrico Farrugia, M.D., president and CEO, highlights Mayo Clinic leaders who exemplify these competencies with the hope that their stories will inspire others to come forward to lead healthcare transformation at this critical juncture.

“Leads self” means taking action to address personal well-being, manage stress and mitigate burnout while modeling these behaviors for others and using these actions to be a more effective, productive and innovative leader. 

Prioritizing self-care helps us maintain stamina for the leadership journey. Self-care takes many forms, and at Mayo, one of the ways we prioritize self-care is by finding joy and fulfillment at work. Personally, I have always found joy in my work as a researcher, and despite the demands of current or previous leadership roles, I have kept research as part of my life as a source of fulfillment. I also designate three days a month of “brain freedom” for personal reflection or stimulating conversation with thought leaders internal and external to Mayo Clinic. 

Prioritizing personal and professional development is also essential to self-care. To support this, we have created self-guided activities that focus on social, financial, emotional and physical well-being, as well as collaborative workshops and coaching groups to enhance work-life integration and meaning in work. 

Self-care in healthcare also requires proactive steps to mitigate burnout, including embracing new technologies and innovations like automation that free up time for more meaningful tasks. 

Vijay Shah, M.D., Kinney Executive Dean of Research and Carol M. Gatton Professor of Digestive Diseases Research, exemplifies the competency of “leads self” through his efforts to support well-being and his personal commitment to consistent self-reflection. 

While leading Mayo Clinic in Rochester’s Department of Medicine, Dr. Shah initiated a transformative strategy to support well-being and professional growth amid the ongoing nationwide threat of physician burnout. Through his leadership, the department has introduced new well-being programs tailored to diverse wellness needs, including piloting the Headspace mental health app prior to its rollout across Mayo Clinic and launching a well-being coaching program that improved clinician well-being scores by 17% using the World Health Organization well-being index. Dr. Shah also initiated career development strategies to better support physicians at every career stage, implementing a six-month program to help them create personalized career plans. 

Recognizing the critical need to ease the burden of clinical documentation for all members of the care team, Dr. Shah also led our Electronic Health Record (EHR) Reimagined Challenge to encourage staff to share their innovative ideas for how to make Mayo’s EHR work better. As a result, departments have implemented new documentation solutions, utilized AI to enhance note-taking during patient visits, tested AI-generated message prompts in patient portals, and categorized patient messages based on required actions. These innovations have created new and better ways to serve our patients while helping improve work experiences for care teams. Dr. Shah is now serving as the Kinney Executive Dean of Research and Carol M. Gatton Professor of Digestive Diseases Research, where his approach to self-development is helping to encourage and inspire others to persevere through change and lean into the digital transformation of our research shield at Mayo Clinic. 

On a personal level, Dr. Shah believes the hardest part of leadership is often self-management. To help better promote that capability within his own career, each morning he dedicates time to self-reflection, asking himself — What did I do well yesterday? What could I do better? He approaches these questions with genuine curiosity about his interactions and how to improve them.

This article was originally published on LinkedIn.

The post Vijay Shah, M.D., Leads Transformational Change Through Self-Care appeared first on Mayo Clinic Magazine.

Gianrico Farrugia, M.D., president and CEO, highlights Mayo Clinic leaders who exemplify these competencies with the hope that their stories will inspire others to come forward to lead healthcare transformation at this critical juncture.

Leadership requires a forward-thinking, entrepreneurial mindset. We need people who are forward thinkers and are able to also use business acumen to guide decisions and balance risk with reward. 

Within medicine, we all have a responsibility to foster innovation to advance cures for patients. Most recently, our focus has been to harness the transformative potential of all forms of AI innovation to shape the future of healthcare. Already, we are using 63 AI algorithms across the organization to improve patient care, with more than 220 under development. From the beginning, we’ve also committed to being a leader in safe, ethical AI — co-founding the Coalition for Health AI, which put forth a first-ever blueprint for ethical AI in healthcare. 

To spur innovation within and outside of Mayo, Mayo Clinic Business Development sources, identifies, develops and secures new diagnostics and therapies not only for the benefit of our patients but for patients everywhere. 

Mayo’s Peter Noseworthy, M.D., M.B.A. — a professor of medicine, chair of the Division of Heart Rhythm Services, and medical director of Business Development — is the definition of “forward thinking,” possessing an entrepreneurial mindset and encouraging others to embrace innovation to transform healthcare. 

Dr. Noseworthy helps lead a multidisciplinary team that is developing novel ECG software-based analysis tools, making them available to others across the globe and many of which have resulted in intellectual property disclosures and several patents. Dr. Noseworthy is also leading efforts within Mayo Clinic Business Development to bridge science and clinical practice to drive innovation. Over the past four decades, Mayo Clinic Business Development has propelled a multitude of inventions to patients, made numerous strategic investments within and outside of the organization, supported the filing of over 9,500 patents, and contributed intellectual property and know-how to help launch more than 350 startups and companies. 

Dr. Noseworthy and the Mayo Clinic Business Development team are also challenging clinicians to contribute beyond the traditional practice of medicine by encouraging creativity and rewarding innovative thinking. This includes providing employees with opportunities to develop and share Mayo Clinic intellectual property, share expertise and contribute to co-development partnerships. This approach not only supports the career growth of innovators within Mayo but also helps advance our vision of promoting clinician and scientist engagement in the transformation of healthcare. 

Dr. Noseworthy advocates for continuous innovation and encourages other physicians to seek out formal business training to not only provide additional fulfilling career pathways but also help the organization stay resilient and future-focused.

This article was originally published on LinkedIn.

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Gianrico Farrugia, M.D., president and CEO, highlights Mayo Clinic leaders who exemplify these competencies with the hope that their stories will inspire others to come forward to lead healthcare transformation at this critical juncture.

In times of transformation, we need leaders who engage with others to guide change. People with this competency navigate ambiguity by remaining grounded in our core values while helping others in the organization see the benefits of change. 

One of Mayo Clinic’s founders, Charlie Mayo, M.D., famously said, "Today the only thing that is permanent is change." This is just as important today as when he said it more than 90 years ago. Leaders must become master change agents, while remaining servant leaders, which means they must be dedicated to our primary value — the needs of the patient come first — while building consensus around innovative, unconventional ways to accomplish it. 

Ajani (AJ) Dunn, FACHE, chief administrative officer of Mayo Clinic in Florida, embraces ambiguity and complexity and is an excellent example of “engages others” to lead change. 

In 2019, AJ led our effort to establish Advanced Care at Home, which offers acute, inpatient-level care to people in the comfort of their own homes. 

Realizing the critical need for more flexible care options during the pandemic, AJ helped Mayo Clinic bring together multiple elements, including our Platform, our internal digital health teams and an external implementation partner, Medically Home, to create a more seamless hospital-at-home care experience. Even amid significant ambiguity, AJ deftly surrounded himself with a network of stakeholders and experts — from nursing and physician leaders to supply chain and IT teams — to help shape a vision for the new program. 

To foster support for the new program, AJ consistently connected every aspect of the project back to its primary goal of improving patient care, emphasizing that the new care model would enable patients to heal in the comfort of their own homes and manage their conditions in a familiar environment. 

By embedding the program’s patient-centered vision in all aspects of his leadership, AJ helped foster both enthusiasm and commitment to making the care model a success. Today, more than 29,500 patients have been treated through this care model, and studies have shown that hospital-quality care at home has reduced infections and falls, and improved patient outcomes and satisfaction.

This article was originally published on LinkedIn.

The post Ajani Dunn Engages Others to Lead Change appeared first on Mayo Clinic Magazine.