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The future of AI in home-based care with Daniel Zhu, VP of Product, Data, Analytics, and AI/ML

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Manage episode 441990002 series 2438436
内容由The Post-Acute POV by MatrixCare提供。所有播客内容(包括剧集、图形和播客描述)均由 The Post-Acute POV by MatrixCare 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Introduction 

In the latest episode of the Post-Acute POV podcast, our host, Melissa Polly, Senior Director of Marketing, is joined by Daniel Zhu, VP of Product, Data, Analytics, and AI/ML, and Jessica Rockne, Head of Product Management, to have a conversation on the current applications of artificial intelligence in the world of home-based care and identify key challenges and opportunities associated with the adoption of these groundbreaking technologies. While post-acute care is behind in adopting AI, organizations can no longer ignore the benefits it can bring to their business.

During their discussion, the trio aims to answer the following questions:

  • What is artificial intelligence (AI) and machine learning (ML)?
  • How will these rapidly evolving tools impact the delivery of care in the home?
  • How can these adaptive technologies help organizations tackle the ongoing staffing shortage and operational inefficiencies?

Listen in to discover how these adaptive technologies are innovating our industry and the technology trends that will impact home health and hospice for years to come.

Topics discussed during today’s episode:

  1. [00:35 – 02:25]: Melissa introduces Jessica and Daniel as well as the topic of today’s podcast episode: the future of AI in home-based care.
  2. [02:25 – 04:48]: Daniel kicks off the conversation by offering insights on how we should define AI as it applies to home-based care.
  3. [04:48 – 07:54]: Daniel goes on to explain the importance of large language models and their real-world application.
  4. [07:54 – 11:42]: Jessica joins the conversation to discuss the use cases of AI in care at home models today.
  5. [11:42 – 15:52]: Jessica then describes how machine learning can quickly identify what issues a patient may be facing and present this data in a way that's easy to understand.
  6. [15:52 – 16:56]: Jessica goes on to discuss what the future of artificial intelligence in care at home might look like.
  7. [16:56 – 17:53]: Daniel jumps back in to detail how the modern AI systems already in place can help streamline a variety of tasks in your healthcare operation.
  8. [18:16 – 19:06]: Jessica offers insight on how AI can be adopted to enhance the quality of care for patients with chronic illness.
  9. [19:29 – 20:50]: Next, Daniel outlines the proper way to notify patients and obtain their consent to utilize their data in an AI-based program.
  10. [20:58 – 21:27]: Jessica provides insight on how the commute to see patients in their home can be used as preparation like listening to a podcast or audiobook.
  11. [21:42 – 23:11]: Daniel goes on to explain how these technologies can improve patient safety and reduce hospital readmissions.
  12. [26:12 – 26:38]: Jessica wraps up the conversation detailing how clinicians can help patients feel more comfortable with AI technology.

Resources 

  Disclaimer 

The content in this presentation or materials is for informational purposes only and is provided “as-is.” Information and views expressed herein, may change without notice. We encourage you to seek as appropriate, regulatory and legal advice on any of the matters covered in this presentation or materials.

©2024 by MatrixCare

  continue reading

94集单集

Artwork
icon分享
 
Manage episode 441990002 series 2438436
内容由The Post-Acute POV by MatrixCare提供。所有播客内容(包括剧集、图形和播客描述)均由 The Post-Acute POV by MatrixCare 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Introduction 

In the latest episode of the Post-Acute POV podcast, our host, Melissa Polly, Senior Director of Marketing, is joined by Daniel Zhu, VP of Product, Data, Analytics, and AI/ML, and Jessica Rockne, Head of Product Management, to have a conversation on the current applications of artificial intelligence in the world of home-based care and identify key challenges and opportunities associated with the adoption of these groundbreaking technologies. While post-acute care is behind in adopting AI, organizations can no longer ignore the benefits it can bring to their business.

During their discussion, the trio aims to answer the following questions:

  • What is artificial intelligence (AI) and machine learning (ML)?
  • How will these rapidly evolving tools impact the delivery of care in the home?
  • How can these adaptive technologies help organizations tackle the ongoing staffing shortage and operational inefficiencies?

Listen in to discover how these adaptive technologies are innovating our industry and the technology trends that will impact home health and hospice for years to come.

Topics discussed during today’s episode:

  1. [00:35 – 02:25]: Melissa introduces Jessica and Daniel as well as the topic of today’s podcast episode: the future of AI in home-based care.
  2. [02:25 – 04:48]: Daniel kicks off the conversation by offering insights on how we should define AI as it applies to home-based care.
  3. [04:48 – 07:54]: Daniel goes on to explain the importance of large language models and their real-world application.
  4. [07:54 – 11:42]: Jessica joins the conversation to discuss the use cases of AI in care at home models today.
  5. [11:42 – 15:52]: Jessica then describes how machine learning can quickly identify what issues a patient may be facing and present this data in a way that's easy to understand.
  6. [15:52 – 16:56]: Jessica goes on to discuss what the future of artificial intelligence in care at home might look like.
  7. [16:56 – 17:53]: Daniel jumps back in to detail how the modern AI systems already in place can help streamline a variety of tasks in your healthcare operation.
  8. [18:16 – 19:06]: Jessica offers insight on how AI can be adopted to enhance the quality of care for patients with chronic illness.
  9. [19:29 – 20:50]: Next, Daniel outlines the proper way to notify patients and obtain their consent to utilize their data in an AI-based program.
  10. [20:58 – 21:27]: Jessica provides insight on how the commute to see patients in their home can be used as preparation like listening to a podcast or audiobook.
  11. [21:42 – 23:11]: Daniel goes on to explain how these technologies can improve patient safety and reduce hospital readmissions.
  12. [26:12 – 26:38]: Jessica wraps up the conversation detailing how clinicians can help patients feel more comfortable with AI technology.

Resources 

  Disclaimer 

The content in this presentation or materials is for informational purposes only and is provided “as-is.” Information and views expressed herein, may change without notice. We encourage you to seek as appropriate, regulatory and legal advice on any of the matters covered in this presentation or materials.

©2024 by MatrixCare

  continue reading

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