Add Dot - Revolutionizing Healthcare: Discovering How Domain-Driven Design Leads to Improved Patient Outcomes

Revolutionizing Healthcare: Discovering How Domain-Driven Design Leads to Improved Patient Outcomes

05/04/24 • 96 min

Mark Wardle, Chief Clinical Information Officer, and Vaughn Vernon discuss the intersection of healthcare and technology. Mark emphasizes the need for technology to improve patient care and the challenges of integrating digital systems in healthcare.

Mark also highlights the importance of Domain-Driven Design in healthcare, as it allows for a more patient-centered approach and better communication between clinicians and patients. He discusses the limitations of current electronic health records and the need for tools that support continuity of care. Mark believes that technology should be used to enhance the human connection in healthcare and improve patient outcomes.

Mark discusses the application of Domain-Driven Design (DDD) in healthcare and its potential to address the complexity and challenges in the industry. He emphasizes the need to break down healthcare systems into modular components and build them based on a shared understanding of the domain. Wardle highlights the importance of technical standards, interoperability, and the use of common models to decouple systems and improve integration. He also discusses the role of open source in healthcare and the potential for disruptive innovation. Wardle envisions a future where technology enables faster iteration, better orchestration of clinical pathways, and improved decision-making in healthcare.

Takeaways

Technology has the potential to greatly improve patient care in healthcare.
DDD is crucial in healthcare to create a patient-centered approach and improve communication between clinicians and patients.
Current electronic health records are often not user-friendly and do not support continuity of care.
Technology should be used to enhance the human connection in healthcare and improve patient outcomes. Domain-Driven Design can help address the complexity and challenges in healthcare by breaking down systems into modular components and building them based on a shared understanding of the domain.
Technical standards and interoperability are crucial for decoupling systems and improving integration in healthcare.
Open source has the potential to disrupt the healthcare industry by providing foundational building blocks and higher-value tools.
Improving orchestration of clinical pathways and decision-making in healthcare can be achieved through the use of technology and data-driven approaches.
Faster iteration, better integration, and improved decision-making can lead to a learning health and care system that continuously improves patient outcomes.

Mark Wardle

Mark is a Consultant Neurologist and Chief Clinical Information Officer in the UK. He is also a keen software developer, building a range of clinician and patient-facing applications, most recently preferring to work in Clojure and ClojureScript. He thinks digital technologies should play a fundamental role in improving and transforming health and care with Domain-Driven Design playing a key role in unbundling the electronic patient record, and turning what we think of as health applications inside-out.

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Takeaways

Technology has the potential to greatly improve patient care in healthcare.
DDD is crucial in healthcare to create a patient-centered approach and improve communication between clinicians and patients.
Current electronic health records are often not user-friendly and do not support continuity of care.
Technology should be used to enhance the human connection in healthcare and improve patient outcomes. Domain-Driven Design can help address the complexity and challenges in healthcare by breaking down systems into modular components and building them based on a shared understanding of the domain.
Technical standards and interoperability are crucial for decoupling systems and improving integration in healthcare.
Open source has the potential to disrupt the healthcare industry by providing foundational building blocks and higher-value tools.
Improving orchestration of clinical pathways and decision-making in healthcare can be achieved through the use of technology and data-driven approaches.
Faster iteration, better integration, and improved decision-making can lead to a learning health and care system that continuously improves patient outcomes.

Mark Wardle

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Previous Episode

Decentralizing Data: Navigating the Shift to Data Mesh

Summary

In this podcast episode, Vaughn and Mark Planagumà discuss various aspects of data strategies and the implementation of Data Mesh. Mark shares his background in data engineering and his experience in building data platforms for different companies. They explore the use of Domain-Driven Design in data strategies and the role of contracts in data architecture. Mark explains the concept of Data Mesh and how it shifts the focus from centralized data warehouses to domain-driven, decentralized data products. They also discuss the implementation of data governance and automation, the influence of operational software architectures on data strategies, and the design of a semantic layer in a Data Mesh. The conversation explores the maturity in operational and analytical architecture, the influence of Domain-Driven Design on Data Mesh, the tooling required for Data Mesh, the future of analytics, challenges with AI and metadata, and where to learn more about Data Mesh.

Takeaways

Domain-Driven Design can be applied to data strategies to organize data by domains and enable domain owners to take responsibility for their data.
Data Mesh is a paradigm shift that emphasizes decentralized, domain-driven data products instead of centralized data warehouses.
Contracts play a crucial role in data architecture by defining the metadata and governance rules for data products.
Implementing data governance and automation can help ensure the discoverability, accessibility, and reusability of data in a data mesh.
Organizational structure needs to align with the principles of Data Mesh, with domain-driven teams owning and managing their data.
A semantic layer in a Data Mesh helps organize and aggregate data products by domains, making it easier to discover and consume data.
Operational software architectures can influence data strategies by providing the infrastructure and tooling for data products in a Data Mesh. Data is typically behind operational and application maturity, but Data Mesh is emerging to bridge the gap.
Domain-Driven Design plays a significant role in shaping Data Mesh and enabling interoperability between operational and analytical systems.
Existing tools like lake houses and data warehousing can be leveraged to support Data Mesh, focusing on creating interoperable data products.
The future of analytics lies in improving data quality, metadata management, and leveraging AI to interact with data in a more natural and business-focused way.

Chapters

Please note these are approximate locations! We are trying new tools and hope you find this helpful.

00:00 Introduction and Background

05:32 Using Domain-Driven Design with Data Strategies

09:20 Understanding Data Mesh

11:18 The Role of Contracts in Data Architecture

28:21 Influencing Organizational Structure for Data Mesh

34:00 Semantic Layer Design in Data Mesh

37:36 Impact of Operational Software Architectures on Data Strategies

37:52 Maturity in Operational and Analytical Architecture

42:30 Domain-Driven Design and Data Mesh

47:08 Tooling for Data Mesh

53:29 The Future of Analytics

01:01:08 Challenges with AI and Metadata

01:09:36 Learning More about Data Mesh

Marc Planagumà, is a native of Olot (Catalonia) with degrees in Telecommunications from UPC. He is a prominent figure in data engineering and governance.

He serves as the Data Platform & Governance Director at Adevinta Spain, where he has spearheaded the development and implementation of Lakehouse architecture and Data Mesh paradigm, focusing on scalability, autonomy, and effective governance by design.

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Next Episode

Innovating at Scale: Lessons from McDonald’s Tech Evolution

Hemi Trickey, Head of Global Enterprise Architecture at McDonald’s, shares her insights on software architecture and digital transformation. She discusses her background in telecom and digital marketing, as well as her experience with software as a service (SaaS) before it became popular. Hemi emphasizes the importance of architecture patterns, observability, and manageability in large-scale distributed systems. She also highlights the challenges of keeping up with innovation and making decisions on adopting new technologies. Hemi advises on the need for clear communication, context understanding, and change management in modernization and transformation efforts.

Takeaways

Architecture patterns and observability are crucial in large-scale distributed systems.
Keeping up with innovation requires evaluating new technologies and understanding their potential value.
Clear communication and context understanding are essential in modernization and transformation efforts.
Change management is a critical aspect of software modernization and transformation.

Hemi Trickey

Hemi has been architecting and delivering highly critical and complex software and technology solutions for almost 3 decades. She is currently head of the global enterprise architecture team at McDonald’s. Prior to McDonald's, Hemi had successful careers at Publicis Sapient as well as Alcatel-Lucent. At Publicis Sapient, she worked with clients across retail, entertainment, insurance, and financial industries. During her tenure at Alcatel Lucent, Hemi designed and developed an in-house SaaS platform from the ground up, long before SaaS became a well-known concept in the industry.

Hemi holds both B.S. and M.S. degrees in Computer Science. She has published or given talks on diverse topics including microservices, mobile application experience, fine-grained access control, predictive analytics and data warehousing.

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