“Since successfully growing Conversa and selling it to Amwell, Chris took on very significant sales and marketing leadership roles at Amwell. I’ve seen him create and implement several innovative growth strategies that our teams benefited from and most importantly drove success in growing / accelerating Prospect and Customer opportunities. As he has led our product marketing, sales and business development teams he was recognized by those respective teams with some of the company’s highest employee engagement results. Chris is a strategic thinker and problem solver who worked collaboratively across all levels of the organization - his integrity, credibility and trust were instrumental to both his and our organizations success.”
(Christopher) Chris Edwards
Raleigh, North Carolina, United States
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"Chris is a measurable executive who is a proven business growth catalyst”.
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Compliant Health Care Solutions
Predictive AI Helps Providers Plan Patient Care Health systems like West Tennessee Healthcare are using AI platforms that can map out a patient’s predicted stay, allowing clinicians to plan discharges and even coordinate with payers on insurance coverage. Click the link below to read the full article.
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The INNOVATORS
In "LEADERS of the Month" for September, we feature 3 healthcare thought leaders from large healthcare systems talking about how innovation are fostered in large organizations in a highly regulated and complex industry, healthcare innovation trends and their advice to startups who are disrupting the industry. Chris Coburn, Chief Innovation Officer at Mass General Brigham, discusses how the organization advances discoveries from Harvard faculty and transitions them into the marketplace. Currently, only 6% of their over 7,000 faculty members are involved in projects with the potential for true commercial outcomes. Mass General Brigham Innovation has launched various initiatives to address this gap, including a $500 million venture fund; “First Look”—rapid-fire presentations showcasing the latest research from leading Mass General Brigham scientists; “Un-Met Clinical Needs”- 100 key opinion leaders in healthcare weighing in on the top un-met clinical needs in medicine today; Emerging Tech Zone – Hands-on exploration of some of the latest digital and AI-based healthcare technologies, all aimed at translating research into adoption and commercial outcomes. Dr. Fritz Francois serves as Executive Vice President and Vice Dean, Chief of Hospital Operations at NYU Langone Health. He oversees all patient care activities on the Manhattan campus, ensuring the highest standards of quality and safety. Dr. François discusses NYU Langone's approach to innovation, which leverages data to enhance quality, safety, workforce efficiency, and patient satisfaction while achieving financial goals. He encourages startups to aim for a "moonshot" in their endeavors. Dr. Christopher Longhurst, chief clinical and innovation officer at UC San Diego Health, discusses the impact of AI on healthcare. While he thinks there is overpromising results for the next 3 to 5 years, emphasizing the importance of rigorously evaluating tools and innovations to ensure it works, Dr. Longhurst is very optimistic about AI's long-term impact on healthcare. He envisions that in 7 to 10 years, a wide array of advancements will significantly improve the experiences in both delivering and receiving care. He advises startups to focus on People, Process and Technology. Startups' problem solutions need to align with workflow and generate value for the system. Follow The INNOVATORS to stay on top of innovation.
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Paul Buehrens
Assuming the chart is accurate, or close. Let's realize that insurance provides no treatment and other than paying the bills does exactly nothing for health. They like to call themselves health plans, so we don't call them bill payers. Then there are many other forms of intermediary that also do not provide any care or health. The system has converted from transactions to financially support caregiving, into caregivers and patients supporting profit taking transactions. This is upside down.
32 Comments -
Timothy Nobles
As I've continued to reflect on the recent Nashville Health Care Council Data and AI event, I found myself considering the intersection of data interoperability and the need to leverage healthcare data in a compliant way for AI to truly live up to its promise. At Integral, where we focus on automating regulated data compliance to enable collaboration and AI innovation, questions often arise about HCOs' data challenges, interoperability vs. collaboration, data quality impacts, and balancing innovation with risk. To gain some guiding thoughts on these topics, I phoned a friend Leigh McCormack, the co-founder and CEO of Platypus, and the former Data Science Lead for BlueCross BlueShield of Tennessee. Here's what she had to say: "Over the past decade, our progress in improving data quality for healthcare AI has been minimal, and we have significantly overlooked the importance of data collaboration. It's important to distinguish that collaboration goes beyond just interoperability. While interoperability focuses on the technical aspects of data sharing, primarily for operational needs, collaboration emphasizes the people and purpose behind utilizing that collective knowledge. As we work to overcome challenges in AI, data quality and interoperability remain crucial, but they can only take us so far. To truly advance, we must also adopt collaborative strategies and mindsets, allowing our foundational knowledge to evolve and enhancing our ability to use these technical tools for the benefit of the entire healthcare ecosystem." What are your thoughts on the evolving landscape of healthcare data, collaboration, and AI? #RegulatedData #DataInteroperability #DataQuality #DataCollaboration
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Mohsin Amin (Jerry)
I think this underscores the crucial need for payer-provider collaboration in healthcare. Aligning incentives and sharing data can significantly improve patient care and operational efficiency. Leveraging AI and big data analytics allows both parties to better manage patient populations and optimize costs. At Medmax Technologies, LLC, we support these efforts by providing advanced solutions that streamline operations and enhance revenue cycle management. By working together, we can overcome traditional barriers and create a more cohesive and effective healthcare system. #HealthcareCollaboration #PayerProviderPartnership #AIinHealthcare #BigDataAnalytics #PatientCare #OperationalEfficiency #MedmaxTechnologies #RevenueCycleManagement #HealthcareInnovation #DataDrivenHealthcare #HealthTech #ValueBasedCare #BetterOutcomes https://lnkd.in/dxd-Tgf8
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Bobby Guelich
There’s a category we believe is getting too little attention when it comes to AI in healthcare: AI Clinical Documentation Integrity (CDI) While AI ambient scribes and autonomous medical coding solutions have gotten most of the headlines, we’d argue AI CDI is equally impactful when it comes to quality care and accurate billing. For those not familiar, CDI ensures that clinical documentation accurately reflects the patient’s medical condition and the provided care. Historically, CDI was a manual slog, with dedicated CDI specialists, nurses, and physicians painstakingly reviewing patient charts to ensure documentation supported the care delivered. Today, AI is reshaping this landscape. While it’s still early days, we’re seeing three primary approaches to applying AI when it comes to CDI: 1️⃣ CDI ambient scribing—an AI ambient scribe and AI CDI assistant operate simultaneously, generating comprehensive notes and surfacing codes for physicians to review at the point of care. (Example: Ambience Healthcare’s AutoCDI) 2️⃣ CDI via real-time diagnosis support—diagnoses are suggested at the point of care based on clinical data in the EHR, with auto-generated documentation and audit trails. (Example: Regard) 3️⃣ CDI via an AI-driven post-coding / pre-billing review—the entire patient record is ingested and analyzed against what is coded, surfacing suggestions for revenue and quality opportunities. (Example: SmarterDx) To date, AI in healthcare has focused primarily on administrative use cases. With the increasing adoption of AI CDI solutions, we’re now taking a step closer to clinical workflows. As clinicians get used to AI-suggested diagnoses in the CDI context, it will be interesting to see if this increases their comfort with AI playing a role in clinical care. Here's our working list of AI CDI vendors. Anyone else we should add? • Ambience Healthcare • Brellium • Iodine Software • Regard • Semantic Health • SmarterDx
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