Data is the key to AI with Keshia Maughn

Biotech Bytes: Conversations with Biotechnology / Pharmaceutical IT Leaders

The intersection of data and artificial intelligence forms the cornerstone of today's healthcare innovation, transforming the way we approach medical advancements.
In this week’s episode, I'm excited to welcome Keshia Maughn from STATinMED, a company carving out its space with a focus on specialized data solutions in biotech. We look at the nuances of data's role in AI, the unique challenges companies face with electronic medical records, and why understanding the lifecycle of a client's needs is crucial.
Keshia brings her deep expertise in navigating the complexities of a saturated market and emphasizes the importance of practicality over flash when it comes to investing in new tech.
To grasp the full spectrum of how data underpins AI in biotech, tune in to our insightful discussion. Remember, clarity in data leads to precision in AI - don't miss this episode.

Specifically, this episode highlights the following themes:

• Customization and strategic application of AI in healthcare
• Navigating challenges in data extraction and quality for AI integration
• The consultative approach to client partnerships in data analytics

Links from this episode:

• Get to know more about Steven Swan: https://www.linkedin.com/in/swangroup
• Get to know more about Keshia Maughn: https://www.linkedin.com/in/keshia-maughn-mph
• Learn more about STATinMED: https://www.linkedin.com/in/keshia-maughn-mph

章

1. Introduction (00:00:00)

2. About ​​Keshia Maughn (00:00:57)

3. Helping clients come together and solve needs. (00:05:23)

4. Providing realistic proposals to avoid shocking clients (00:08:19)

5. EHR: Challenging, fragmented, diverse, and complex data (00:11:19)

6. Approaching people requires asking the right questions (00:17:12)

7. Increasing vendors create challenges for clients' decision-making (00:19:14)

8. IT leaders discussing budget constraints and innovation (00:22:05)

9. Data readiness crucial for success in biotech (00:25:16)

10. Client lacked necessary control data, caused issues (00:27:53)