Summary
Healthcare organizations face unique challenges in managing and leveraging data effectively. In this episode, Jim Farley, Director of Healthcare and Life Sciences at Infoverity, discusses key healthcare data management use cases, the impact of mergers and acquisitions on provider data, and the growing role of AI and analytics in improving patient care and operational efficiency. Learn how hospitals, insurance providers, and pharmaceutical companies can enhance their data strategy to drive better business and patient outcomes. Infoverity provides expert guidance in data governance, master data management, and AI-driven transformation. Listen now to gain insights on modernizing healthcare data management and ensuring long-term success.
Transcript
Jocelyn 00:01:
You’re listening to Infoverity’s Trust Us podcast, where you can gear up for your data management journey with bite-sized discussions on industry trends and thought leadership. On each episode, we feature industry experts to help you navigate your path to mastering your enterprise data.
Jocelyn 00:19:
Today on the podcast, we’ll be talking about all things healthcare in the enterprise data management space, from use cases to trends to how to get started.
Our guest for this episode is Jim Farley, the Director of Healthcare and Life Sciences Practice at Infoverity. Jim, thank you so much for joining us. Would you mind telling the listeners a little bit about yourself?
Jim Farley 00:43:
Sure, thanks, Jocelyn. Happy to be here.
Like you said, my name is Jim. I run our healthcare and life sciences practice at Infoverity. I’ve been with the firm for over ten years, focusing on data management challenges in healthcare. I started working with hospitals and later expanded to medical insurance companies and pharmaceutical organizations. My focus is on how data products and solutions can drive business value and improve customer outcomes.
Jocelyn 01:27:
Awesome, Jim. Let’s go ahead and dig into some key healthcare use cases to help our listeners understand the work that you and your team do. What are some of the biggest use cases for enterprise data management in healthcare?
Jim Farley 01:50:
Sure. First, I want to take a step back to define what we mean by a “use case.” Many organizations implement master data management (MDM) programs without a clear understanding of their purpose. Early in my career, I worked with a children’s hospital that had invested in an expensive MDM solution without a well-defined reason for doing so. It quickly became clear that they lacked a specific business-driven use case.
One of the biggest healthcare use cases we address is provider data accuracy. Many hospitals have gone through mergers and acquisitions over the last decade, leading to provider data spread across multiple systems. Ensuring that provider directories and “Find a Doctor” websites display accurate, up-to-date information is critical for patient experience. Patients need to know that a doctor is actually available at a given location and accepting new patients. If they encounter outdated or incorrect provider information, it damages trust in the healthcare organization. This use case directly impacts patient satisfaction and requires collaboration between IT, marketing, and operational teams.
Jocelyn 04:27:
That’s a great example, Jim. Now that we understand some of the common challenges, what are some of the biggest trends in healthcare data management today?
Jim Farley 04:52:
One of the biggest trends is the retail influence in healthcare. Many retail companies have entered the healthcare space because they see significant opportunities for improvement. People often joke that healthcare is 10 to 20 years behind other industries in terms of technology adoption.
Another major trend is proactive patient engagement. Health insurance companies and hospital networks are focusing on understanding how patients interact with their health data and using this insight to improve preventative care. The goal is to keep patients healthier and avoid costly medical interventions down the road. Hospitals are also working on patient retention strategies, ensuring that patients stay within their network rather than seeking care elsewhere.
Jocelyn 06:12:
That makes a lot of sense. If organizations are looking to invest in better data management, where should they start?
Jim Farley 06:33:
I always recommend following the money when building a business case. Provider, member, and patient location data are some of the most valuable data domains across hospitals, insurance companies, and pharmaceutical firms.
For example, in hospitals, claims data drives revenue. Poor data quality can lead to billing errors and claim denials, costing organizations millions. Understanding where these pain points exist and quantifying their financial impact helps secure leadership buy-in for data initiatives. At Infoverity, we help clients identify high-value opportunities and develop strategies for improving data governance and standardization.
Jocelyn 08:26:
That aligns with what we’ve heard from other experts. If organizations aren’t sure where to begin, what are some tactical steps they can take to prepare for data transformation?
Jim Farley 08:56:
Start by identifying where critical information lives and understanding data pain points across different departments. Network across the organization, ask questions, and document inconsistencies. Many organizations struggle with siloed, inconsistent data that leads to inefficiencies and compliance risks.
Healthcare leaders should focus on small, incremental wins rather than trying to tackle everything at once. For example, improving provider directory accuracy is a manageable, high-impact initiative that benefits both patients and hospital operations. Once this foundation is in place, organizations can expand their efforts into claims management, patient engagement, and AI-driven analytics.
Jocelyn 10:45:
Excellent, Jim. Now that we’ve discussed industry challenges and trends, how does Infoverity help healthcare organizations with data transformation?
Jim Farley 11:06:
We provide end-to-end data solutions, including:
- Data strategy and roadmap development – Helping organizations assess data maturity and define a structured plan.
- Master data management and data governance – Ensuring accurate, well-integrated provider, patient, and claims data.
- AI and analytics enablement – Implementing tools for predictive analytics, anomaly detection, and AI-driven decision-making.
- Operational support and long-term governance – Helping organizations maintain and continuously improve their data systems.
One of the biggest advantages we offer is deep industry expertise. Our healthcare data specialists understand regulatory requirements, operational challenges, and business priorities, ensuring that data initiatives deliver tangible value.
Jocelyn 13:37:
That’s a great breakdown. Before we wrap up, any final thoughts for our listeners?
Jim Farley 15:52:
The biggest takeaway is that every healthcare organization is a data company. Data impacts billing, patient care, regulatory compliance, and operational efficiency. Investing in better data management isn’t just about IT—it’s about ensuring long-term success and better patient outcomes.
Jocelyn 22:39:
That’s a great message to end on. Jim, thank you so much for joining us today.
Jim Farley 23:30:
Thank you! It was great to be here.
Jocelyn 23:51:
For over a decade, Infoverity has been a trusted leader in enterprise data management consulting, with experts worldwide and headquarters in Columbus, Ohio, and Valencia, Spain.
To learn more, visit infoverity.com. Additional contact details are in the show notes.
