By the Numbers: Four Trends from the 2024 Healthcare Data and Analytics Association Conference

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October 3, 2024

By Madison Vinson, MSHI, Data Engineer, and Caroline McLeod, RDH, MS, Value-Based Solutions Manager, CareQuest Institute

Data analytics — the process of converting data into useful insights — may not be on the top of your to-do list every morning. But for the more than 350 people who attended the 2024 Healthcare Data and Analytics Association (HDAA) Annual Conference in Chapel Hill, North Carolina, the topic filled three engaging days of learning in mid-September. A few weeks later, our minds are still racing about how all of it applies to the oral health industry. 

Caroline and Madison at HDAA
Caroline McLeod, RDH, MS, and Madison Vinson, MSHI

The conference brought together health care organizations from across the country to discuss how health data and analytical tools drive high-quality, accessible care at lower costs. We believe dentistry is a crucial part of that conversation. 

Health data is foundational to the practice of dentistry as it: 

  • Gives insight into patient population, practice operations, and care delivery, quality, and cost 
  • Helps determine opportunities for improvement 
  • Informs responsible decision making at the clinical, organizational, and policy levels 
  • Supports health care innovation through research (e.g., clinical trials) 

As a part of the modern, technology-forward health care industry, dentistry must keep up with what's happening in the rapidly evolving field of data analytics. How? In what disciplines? These four areas, along with a lesson from each, stood out to us: 

  1. Data Governance 

    Many presentations demonstrated strategies for wide-scale adoption of data governance, or management of data security, quality, and compliance. Approaches adhered to similar core workflows, including the formation of data governance and compliance teams, extensive documentation of standards and best practices, and gradual rollout of self-service analysis and data visualization capabilities. Our first lesson learned: Many organizations noted that tailored and frequent training opportunities to enhance data literacy were a key to success. 
     
  2. Data Literacy 

    With the use of health data by a wide range of individuals in an organization, it is critical that everyone knows how to responsibly use data. Thus, our second key takeaway: Many organizations are implementing data literacy programs/training aimed at bolstering data skills and compliance and fostering a data-driven culture that drives decision-making and action. These programs included e-learning, in-person training, feedback opportunities, and practice with self-service data tools.
     
  3.  Health Equity 

    Data present a powerful opportunity to identify and improve inequities in health care utilization and practice. The third lesson we left with: Many organizations are using data to take a closer look at what groups of people access care, what needs individuals have beyond clinical care, and how certain operational practices affect workforce capacity. For example, Eskenazi Health in Indianapolis, Indiana, completes patient screenings for food insecurity, provides vouchers for groceries and basic cooking needs at their hospital fresh market, and tracks redemption rate and need for follow-up in their electronic health record. Strong data tracking has supported addressing food insecurity and expansion of access to fresh food in their local communities. 
     
  4. Technology 

    The conference offered a deep dive into the latest trends and innovations in technology to support data usage. Topics included architectural design practices for building robust analytics solutions, signal-detection methods for emerging health care trends, practical use cases featuring synthetic data to simulate real-world scenarios, and leveraging machine learning and cloud computing for scalable solutions. Speakers highlighted the development of data governance plans for generative artificial intelligence (AI) as critical areas of improvement, alongside discussions on the Observational Medical Outcomes Partnership (OMOP) Common Data Model standard and master data management. Our fourth insight: Leveraging technology for data needs supports the development of more personalized care strategies, identifies trends in patient populations, and promotes evidence-based improvements in clinical practices. 

    Dentistry must recognize how health care data, technology, and associated processes shape operational decisions and enhance patient care. Beyond improving outcomes at the practice level, data facilitates a more holistic approach to health care by fostering effective collaboration between health care teams and community-based organizations. Many organizations at the conference shared this sentiment as a key to their success. This collaboration, which often includes dentistry, enables the integration of oral health into overall patient care, ensuring that care is comprehensive and reflective of a patient's full health needs. 

Want to put some of these conference concepts into practice? See our previous blog post where dental practices participating in a CareQuest Institute program in North Carolina share their advice on using data to transform dental practice.

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