Why Healthcare Keeps Cycling Between Building In-House and Bringing in Partners скачать в хорошем качестве

Why Healthcare Keeps Cycling Between Building In-House and Bringing in Partners

In this conversation, Mike Moore and Mark Nelson discuss the cyclical nature of technology adoption in healthcare, particularly focusing on AI. Mark shares insights from his extensive career in healthcare, emphasizing the importance of data-driven decision-making and the challenges organizations face in managing risk and accountability. They explore the role of partnerships in navigating these challenges and the innovative work being done at Intelligible to enhance data usability. Mark offers practical advice for healthcare leaders planning their AI strategies for the future. Takeaways Healthcare organizations often cycle between building in-house capabilities and seeking external partnerships. Data-driven decision-making is crucial for improving patient outcomes and operational efficiency. Understanding the complexities of healthcare data can lead to more effective interventions. AI adoption in healthcare is influenced by risk management and accountability concerns. Clarity in goals and outcomes is essential for successful AI initiatives. Modularity in data architecture allows for flexibility and adaptability in technology adoption. The pace of AI innovation is rapid, requiring organizations to stay agile. Partnerships can help healthcare organizations scale their technology efforts effectively. Healthcare leaders should focus on operational outcomes when implementing AI solutions. Intelligible aims to democratize data access for healthcare leaders, enhancing decision-making capabilities. Chapters 00:00 Introduction to Healthcare Cycles and AI 01:30 Mark Nelson's Career Journey in Healthcare 04:01 The Importance of Predictive Analytics 07:58 Improving Length of Stay Metrics 14:20 The Cycle of Technology Adoption in Healthcare 18:07 AI's Unique Position in Healthcare Technology 24:33 Risk Management and Accountability in AI 28:29 Innovations at Intelligible 34:22 Advice for Healthcare Leaders on AI Planning Keywords healthcare, AI, technology adoption, data analytics, risk management, healthcare innovation, operational efficiency, healthcare leadership, predictive analytics, healthcare partnerships