The Health Pulse

Bryan Vaughn is passionate about bending the cost curve in health care. As Senior Vice President, Hospitals and Health Systems at Labcorp, he focuses on the role of diagnostics in delivering better, more affordable care. On this episode, Vaughn notes that impactful partnerships across the health care ecosystem can help drive the cost of critical diagnostics down, creating a win for all stakeholders. When it comes to analytics, he is excited to see Labcorp’s wealth of health data empowering and informing patients and their doctors today—as well as the potential for predictive analytics and Artificial Intelligence (AI) to improve health outcomes in the future.

Krishna Tangirala is an expert at uncovering insights about pharmaceutical products in the real world. He is Head of Data Analytics and Director of Field Outcomes Research at Organon Pharmaceuticals. In the first part of this episode, Tangirala talks to Alex about how stakeholders use health economics and outcomes research throughout the pharmaceutical life cycle to better understand the value, potential and safety of drug products. He also discusses new and emerging applications for real-world data (RWD) in pharma, including external control arms and digital twins and the potential for technology to solve challenges around managing, analyzing and visualizing data insights from RWD.
 
Next, Sherrine Eid, Global Lead for Real-World Evidence and Epidemiologist at SAS, joins Alex. Eid is passionate about mathematically modeling disease patterns and finding ways to intervene and improve outcomes. For her, it’s all about using the best tools at her disposal to help people live their healthiest, best lives. Eid discusses the role of RWD and connected devices to enable personalized medicine and shares her perspective on the value of personalized health information as a diabetes patient.

Dr. Iulia Vann, Public Health Director in Guildford County, NC, is passionate about public health and data-driven decision making.

On this episode of the Health Pulse Podcast, Dr. Vann discusses the importance of prevention, the public health response to the COVID-19 pandemic, lessons learned about closing gaps in data and analytics and resiliency.

Dr. Vann explains that effective public health strategies include strong relationships with local partners, communication and planning for health equity measures, like putting 40% of vaccines aside for historically marginalized communities. Data modernization is another crucial element for health organizations to serve their communities better. Requiring agencies to integrate data from different systems and ensuring the data is transparent and reliable is essential in making data-driven decisions as a public health agency. She explains how Guilford County partnered with SAS to create dashboards to monitor program performance and public health areas of focus, such as chronic diseases, cancer and environmental health, to make the best possible decisions for their community.

SAS’ Andy Bayliss works with life sciences manufacturers, applying AI and machine learning to improve their processes at scale. On this episode of the Health Pulse Podcast, he tells Alex that pharmaceutical manufacturers are experts at reliably delivering high-quality products. They must be because it’s a highly regulated industry with a patient at the end of every product.
  
 The opportunity to utilize technology energizes Bayliss. Technology like sensors and computer vision allows continuous monitoring to spot trends and potential deviations earlier in pharmaceutical manufacturing. It’s about giving the human expert additional insight to create meaningful action.

Dr. Michel van Genderen, physician, AI leader and founder of the Datahub at Erasmus Medical Center in the Netherlands, shares his passion for ethical AI in hospitals.
  
Could AI be a game-changer for the health care industry? Dr. van Genderen thinks so, and explains the two biggest global health care challenges are the shortage of personnel and an increasing health care demand. He believes trustworthy AI could alleviate these pressures and solve clinical challenges faster. For example, Erasmus Medical Center developed an AI model used in the intensive care unit that decreases the administrative workload for nurses. 
 
Using AI in a responsible, ethical and sustainable manner is crucial to its adoption in clinical settings so that health care professionals trust AI when they use it at the bedside. To develop and deploy AI models in clinical settings, a group of multidisciplinary teams comes together, including data scientists, data engineers, physicians, nurses, patients and more, which is the remit of the Datahub at Erasmus Medical Center. Adhering to ethical guidelines is crucial when teams develop models, monitor their performance and adopt them in clinical or operational settings. Dr. van Genderen is optimistic that all industries will be able to benefit from AI, as long as decisions made with analytics and AI are ethical, trustworthy, explainable and fair.

Steven Lehmann is passionate about the impact of data science in business. He is Head of Data Science and Analytics Strategy for Johnson & Johnson in EMEA. He also wrote the book Digital Jackpot on what it really takes to make data driven decisions that matter in business. Hint, the answer often isn’t more data. On this episode of the Health Pulse Podcast, he talks with Alex about the importance of telling the right story with data so that people will listen. He introduces the concept of data elasticity in finding the right balance between enough data and the speed at which you need to make business decisions in order to solve real-world problems. Data elasticity allows data scientists and business leaders to make strong recommendations with imperfect data, knowing that their recommendations would still hold within a reasonable margin of error in the data.  When it comes to the explosion of data, AI and advanced analytics, he reminds us that these are excellent tools, but the individuals and organizations who can make the best use of them to drive impact will ultimately succeed.

Dr. Meg Schaeffer, an Epidemiologist and Public Health Advisor at SAS and an elite athlete and champion for health equity, is a perfect example of what passion for public health looks like.

In this episode, Dr. Schaeffer speaks about the evolution of the bird flu and explains that North America, Europe, Asia and some African countries are in the midst of the largest bird flu outbreak, with millions of birds culled. Monitoring outbreaks is crucial to predict the future of health care and to prevent a human pandemic. She also talks about health equity and the importance of combining quantitative with qualitative data to understand population needs and challenges. This helps design effective programs that reduce inequities. There is currently a lack of qualitative data, leading to resource misalignments, Schaeffer explains. Combining interviews, focus groups and text data with advanced analytics could be the key to currently overlooked insights. Despite challenges the health care industry is facing, being an elite, world-ranked triathlete has taught Dr. Schaeffer there is always a way – that temporary discomfort leads to success. She is optimistic about the future of health care with the dedication of the public health workforce and cutting-edge software, supporting decision-making processes.

Dr. Richardus Vonk, VP, Head of Oncology Statistics and Data Management at Bayer, wants to see cancer become a manageable disease in his lifetime. With as many as one in two people getting cancer at some point in their lives, the goal to better treat and eventually prevent and cure cancer is incredibly impactful. On this episode of the Health Pulse Podcast, Vonk sits down with host Alex Maiersperger to discuss the role of data, analytics, AI and automation in advancing cancer research and drug development. He explains that AI is playing an important role in early detection of cancer but has yet to find widespread adoption in drug development. Automation is important because it frees up time at the end of clinical trials to explore the science and uncover valuable insights to inform care. When it comes to analytics software, Vonk thinks the future is a mix of commercial and open source. What’s more important according to Vonk, is expanding access and ability to share data, while protecting patient privacy, and using the right tool to answer the right questions.

More than a decade ago, Bruno Boulanger made a big bet on applying Bayesian statistics in clinical trials. At the time, very few in the industry thought the method, which applies probabilities to statistical problems, had a place in clinical development. Boulanger saw an opportunity, founding a company that quickly grew and was acquired by CRO PharmaLex in 2018, where he now serves as global head of statistics and data science.

In this episode, Boulanger explains how Bayesian statistics uses probability and prediction to solve challenges in the increasingly complex world of clinical research and clinical trial design. Bayesian statistics allows researchers to expand decision making for clinical trials beyond its participants, which is imperative for trials targeting rare diseases. Looking forward, Boulanger is optimistic about the expansion of therapeutic innovation combined with digitalization and data science to meet the unmet needs of patients. 

All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.

What makes value-based care work? Bryony Winn shares her views on key enablers, implementation challenges and how they can be overcome. Winn is President of Health Solutions at Elevance Health. Being born and raised in Africa, educated in the UK, having worked in Europe as a consultant and moved to the United Stated, Bryony Winn has a truly international career path and a wealth of knowledge of different health care systems. 

On this episode, host Alex Maiersperger and Winn talk about the role technology plays in integrating care systems. She tells us a big challenge is patients are often treated for conditions in isolation, without taking a whole-person approach. Data integration and deep partnerships across different health and social care providers are crucial for full transparency and insights into a person’s whole health, enabling providers and payers to make value-based care work and tailor care more effectively.

Simultaneously, Winn addresses some criticism value-based care models have received, as some don’t believe the concept is working. She explains the industry’s initial narrow view, believing the shift to value-based care is only a change of payment models. Winn emphasizes data integration and infrastructure around payment models are needed. Despite some of the challenges and criticism, she remains optimistic about value-based care models and their role in affordability, high quality care and high experience scores. 

All presentations represent the opinions of the presenter and do not represent the position or the opinion of SAS.