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Co-founder & CEO

In response to the COVID-19 pandemic, our team will be interviewing experts from across the ecosystem to bring the HLTH community timely facts and updates. About Sean Duffy: Sean is certain that behavioral medicine is at an incredible tipping point of innovation, thanks to technology and design. He holds a BS in Neuroscience from Columbia University, was an MD/MBA candidate at Harvard, and formerly worked for Google and IDEO.

COVID-19 Discussion with Omada Health

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General Manager

Clinical trials are more complex than ever. Pharmaceutical companies, medical device companies, and clinical research organizations (CROs) are collecting more research data than ever. The amount of data from novel sources that support decentralized trials has also increased over the last several years. As a result, research sites and clinicians are struggling to meet sponsor deadlines for increasingly complex trials.   Technology can help solve this challenge, when it’s deployed appropriately. Here are four tips for managing clinical trial complexity:   1) Stay focused on the experience When I say experience, I mean that in a couple of different ways. First, we should focus on the experience of the user – the sponsor team designing and conducting the trial. Better workflows can make the difference between meeting and missing a critical research decision point or deadline. Second, and just as important if not more so, we should focus on patient and clinician experience. The future of trial recruitment will be heavily influenced by the patient’s expectations for a smooth digital experience and the clinician’s ability to deliver to sponsor expectations.  2) Enable direct data flow Direct data flow, meaning the ability to collect data directly at the source (i.e., the patient, clinical setting, directly from equipment or testing systems) and flow that data to the sponsor systems, has gained momentum with the COVID pandemic and the associated healthcare disruption. Direct data flow is complex, and some technologies contribute to complexity, especially if they are not connected to each other or otherwise inhibit data flow by requiring data transformations.   As an example, clients are more frequently asking how electronic health records (EHRs) can be directly integrated with electronic data capture (EDC) systems to simplify data collection for clinical trials and better integrate that into clinician workflows. There are significant differences between how healthcare data is collected in a clinician setting versus how it is collected for clinical research. As the industry identifies ways to smartly apply technology solutions and data transformation that reduce the data disparities between the use cases, the ability to connect clinical data with clinical trials data becomes a viable path forward.   3) Apply artificial intelligence (AI) and machine learning (ML) strategically When working with AI and ML technologies, it’s important to have a specific purpose and a clearly defined use case/problem statement to be solved. We were among the first to apply AI to medical coding and have had success in that area for a long time, showing that machine learning solutions embedded within workflow can significantly reduce overall effort. Because of this experience, we are working on other targeted applications of machine learning, specifically for streamlining operational workflows and improving overall quality.  4) Lean into the expertise of your technology vendor Research requires completing a host of difficult tasks in support of complex trial designs. Technology vendors should be able to help solve those challenges. They should be able to proactively advise in these cases and not just be reactive recipients of information.  For example, adaptive clinical trial design enables planned modifications to one or more aspects, which offers distinct advantages. We helped a client with adaptive trial design, so that researchers can add multiple treatment arms throughout the study lifecycle. Another client used adaptive design to enable adjustments to the randomization schedule, based on the variable or unequal probability of treatment assignment.  Complexity will continue to increase in the clinical trial space, but innovative technologies continue to help teams rise to the challenge. Applying these principles can also help future-proof clinical trial design in the years to come.  Jennifer Duff is Merative’s General Manager for Zelta. She has more than 24 years of experience in the Life Sciences industry and specializes in enabling and scaling industry-leading services and technology solutions for biopharma clients.

4 Tips When Using Tech to Manage Clinical Trial Complexity

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Q&amp;A with Paul Roma In response to the COVID-19 pandemic, our team will be interviewing experts from across the ecosystem to bring the HLTH community timely facts and updates. HLTH Team: As a business leader, how are you setting priorities and managing your organization through these unprecedented times? COVID-19 has disrupted everyone. As a business leader, I need to make sure that we’re taking care of our employees and clients. Many people are working from home, maybe they’re juggling taking care of kids or parents, they could be struggling with stress or anxiety. Our clients are wrestling with the same issues we are. It’s more important than ever for employees to be flexible and stay connected – with each other and with clients.  I’m proud of the way our teams have stepped up to support our clients, partners and communities. IBM is aligning with needs across industries to help address business continuity, security risks, supply chains, remote workforces, and of course, supporting health and human services. IBM has several initiatives to help companies prepare their workforce for the new normal. For example, <a href="https://www.ibm.com/products/return-to-workplace-advisor" target="_blank">IBM Return-to-Workplace Advisor</a> helps employers monitor data and make evidence-based decisions about when to return to the workplace. HLTH Team: What’s the role of advanced technology in a pandemic? How is it helping patients right now? Patients have a lot of important questions right now. For example, people might ask their providers how they can tell if they have COVID-19, or where they can go for testing. They might need to check coverage with their health plans or employers. Or they might need unemployment or food assistance from government agencies. People are flooding healthcare and human services organizations with these questions at the same time some call centers are managing their own remote work situations. Organizations can use AI to help connect people to the answers and resources they need. This is especially important during times of crisis. Conversational AI can help these organizations answer common questions about COVID-19. We’ve shared some examples in a <a href="https://newsroom.ibm.com/2020-04-02-IBM-Offers-Watson-Assistant-for-Citizens-to-Provide-Responses-to-COVID-19-Questions" target="_blank">news release</a> about how government and healthcare organizations around the world are using Watson Assistant for Citizens to help answer people’s questions quickly and accurately. HLTH Team: What are some other ways advanced technology and AI are helping organizations with COVID-19 response efforts? One important way AI is being used by health systems is to help providers on the front lines. AI can help surface the information providers need – such as evidence-based drug and disease information – at the point of care. They can make more informed decisions if they have access to the latest evidence. We’ve given free access to <a href="https://www.ibm.com/products/dynamed-and-micromedex-with-watson" target="_blank">DynaMed and Micromedex with Watson</a> to help providers with access to high-quality content about drugs and diseases, including COVID-19. Life sciences companies are working hard to find a way to prevent, contain and treat COVID-19. It’s a challenge to work under this timeline, because clinical development is a long process. One of IBM’s key initiatives is to help accelerate discovery around COVID-19, and there are a number of efforts underway – including our high-performance computing consortium. We are also offering IBM Clinical Development free of charge to eligible research teams focused on COVID-19. We’ve been able to help sponsors get several COVID-19 trials running across 35 different sites. One example, Bionical Emas, published a <a href="https://bionicalemas.com/case-study/covid-19-pneumonia-case-study/" target="_blank">case study</a> about how it was able to set up a clinical trial on COVID-19 in five business days.  Employers are using advanced tech to make better decisions, too. Right now, employers are deciding about when employees can return to the workplace. They have to do it in a way that protects employee health while balancing the needs of their customers and clients. Lots of factors come into play for each worksite. Local COVID-19 infection rates, employee symptoms and health risk factors, local regulations, company policies…and these factors keep changing all the time. As I mentioned earlier, IBM is working to help employers support their employees in the new normal. <a href="https://www.ibm.com/products/return-to-workplace-advisor" target="_blank">IBM Return-to-Workplace Advisor</a> fits into that effort, as it’s designed to help employers and employees look at all of these data sources together and determine how best to proceed for their organizations. As one final example, public health officials are looking to technology to help mitigate the spread of COVID-19 as states ease social distancing rules. Contact tracing can help case workers identify clients who have been infected and follow-up with anyone who might have been exposed. These are powerful capabilities to help slow the spread of the disease.  HLTH Team: How has COVID-19 affected advanced technology adoption? In the race to respond to COVID-19, I think we have seen some acceleration around digital transformation and the adoption of things like telehealth, as well as advanced technologies, AI and blockchain. Here’s just one example: a blockchain-powered network is helping address medical supply shortages. Many of us have heard of how COVID-19 has exhausted supply chains for things like masks, gowns or other equipment needed. Other companies have stepped up to mass produce some of these items – but before hospitals and state agencies can purchase from them, they have to, first, identify these new suppliers, validate they are a trusted supplier, and be able to see what they’ve got in their inventories, real-time. To help with that, IBM launched <a href="https://www.ibm.com/blockchain/solutions/rapid-supplier-connect" target="_blank">IBM Rapid Supplier Connect</a>, which is designed to help government agencies and healthcare organizations find and onboard new vendors. Advanced technologies, cloud, AI, blockchain are all proving to be useful tools in the COVID-19 crisis. I expect healthcare will continue to use them to solve our toughest challenges. About Paul Roma: Paul Roma is the Global General Manager for IBM Watson Health, an organization helping to lead the transformation of health around the world by applying next-generation technologies, such as data, analytics, AI and hybrid cloud, to address the most pressing health challenges globally. Watson Health partners with the greatest minds in the healthcare world – including Memorial Sloan Kettering, Mayo Clinic, the Broad Institute of MIT and Harvard among others in life sciences, health plans and tech – to research, develop, train and test our technologies.

COVID-19 Updates with Paul Roma

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Ever hit ‘Accept’ on the Terms &amp; Conditions of a newly downloaded app, skipped the fine print, and scrolled all the way down to move ahead? It’s a likely scenario, but now we’re facing the reality of what we may have agreed to. Up until recently, most of us fell for this standard practice, something the tech industry counted on and benefited from: gathering personal data from mobile devices and well beyond the app. What they did not account for was the consumer distrust of this sneaky behavior, developing very protective boundaries around the use of their private information, once becoming informed. For example, Apple recently updated its privacy label to clearly reveal how data is obtained, giving the consumer a choice. At that time, a reported 95% of all Meta (formerly known as Facebook) users with an iPhone iOS opted not to share their data*. Social media platforms could expect a hit to their revenues and could see people start to leave the platform as a compromise of their non-health data privacy breeds mistrust. Healthcare industry is no different, but there’s time to correct the pattern Healthcare systems and payers are using consent forms in the same way and with a similar purpose, having patients sign away their rights to their data, and not fully explaining the multitude of secondary data sales (from operational improvements to clinical research) that they may have unknowingly agreed to share. As this becomes more apparent, if healthcare systems do not get out in front of this they risk consumers questioning the intent of their care teams and the security of their personal information. They can easily say, “if I pay for my services at the hospital, I expect that only the provider and I will access my data for my personal care. When did I agree to having my data re-used and re-sold?” Legally in almost all states, healthcare systems actually do own the data that they collect – though this is not apparent to many patients. Neither are the long-term repercussions if that data is ransomed, stolen, or used to make more expensive healthcare products or services that might be out of their price range. Healthcare systems and organizations have a vital opportunity to rebuild trust with their consumers by embracing privacy by consent and being transparent with the use of their data. Consumer as a Partner: Two-way trust system The opportunity is ripe for building consumer engagement around creating transparent methods of information gathering. Safely, securely, and in most recent cases, virtually, consumer engagement can be the differential consent-based business model that can harness user trust through reciprocal data sharing and rewards for participation. So, who is doing this right? One of the best examples of a privacy-based consent approach is the All of Us Research Program, led by the National Institutes of Health, with support from Scripps Research Translational Institute, where Dedalus has been conducting ongoing customer service with participants. With a unique and intimate view into this two-way engagement approach, it’s clear that consumer trust can be gained when there’s unwavering privacy in this current environment and they’re positioned as a key stakeholder. While stating ambitious goals of recruiting one million or more participants, the most notable part of the program is that it was designed around privacy and security, to build trust with communities, especially those who have been underrepresented in biomedical research, including racial and ethnic minorities, LGBTQ+ people, residents of rural areas, and other groups. As a trusted partner, Dedalus developed and maintains an ongoing FISMA Moderate security posture. In other words, <a href="https://www.dedalus.com/na/perspectives/all-of-us-research-program/" target="_blank">Dedalus</a> operates under an extensive set of security controls while engaging with participants and when collecting their healthcare data. Positioning participants as active partners, helping to guide efforts and decide how their data will be used for research, is only going to lead to more trust, discovery and interest in their wellbeing in the long term. The <a href="https://clicktime.symantec.com/3Er1xHV7YUpvYiSwEiSp5F97Vc?u=http%3A%2F%2Fjoinallofus.org%2F" target="_blank">All of Us</a> Research Program to date, has engaged more than 400,000 participants in sharing their data, and is the first of any program that provides information back to the participant, if interested, as a benefit of their participation. The participant is also made aware of the outcomes their data has served, developing a true partnership when the reciprocation is valued on both sides and utilized for the greater good of our future generations. *<a href="https://www.bloomberg.com/news/articles/2021-07-14/facebook-fb-advertisers-impacted-by-apple-aapl-privacy-ios-14-changes" target="_blank">https://www.bloomberg.com/news/articles/2021-07-14/facebook-fb-advertisers-impacted-by-apple-aapl-privacy-ios-14-changes</a> About Dr. George Mathew, CMO George Mathew, M.D. M.B.A, F.A.C.P. is the Chief Medical Officer for Dedalus Group, North America, and serves as the clinical informaticist, expert and healthcare thought leader to our customers in the transforming healthcare marketplace of payer, provider, life sciences and federal, state and local government healthcare businesses. His experience includes consulting, technology development, and business development work at GE, Goldman, Sachs and Co., WebMD, Pfizer, Medidata Solutions, and Aetna/CVS. Dr. Mathew brings a strong technology innovation focus to this role having founded a healthcare technology start-up earlier in his career and continues to advise several healthcare IT startups through the Health 2.0-NYC community. George is based in the greater New York City area and continues to practice medicine as a hospitalist.

Healthcare Data Privacy: Who's Doing It Right?

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