Background

Preventable hospitalizations cost the U.S. about $25 billion every year, highlighting the need for earlier intervention.¹ Effective preventive care programs lead to better health outcomes, lower utilization, and improved value‑based care performance. A persistent challenge is access to comprehensive, timely, and accurate insights to act sooner.

Digital Quality Measurement (dQM) can offer a reliable data foundation that makes earlier interventions possible, improving results for providers and payers. Better access to widely collected, standardized data makes it easier to evaluate performance accurately and identify care gaps with far greater precision.

Digital quality measurement has the potential to strengthen preventive care because it delivers the timely clinical data needed to spot care gaps much earlier. Traditional data collection methods are labor-intensive, slow, retrospective, and often inconsistent or incomplete. Digital quality measurement automates data collection, eliminating delays and reduces errors. With easily accessible information, healthcare organizations can move from reactive to proactive care management.

Impact on Providers

Many providers struggle to access complete, longitudinal patient information needed for effective preventive care. Clinical data scattered across EHRs, labs, imaging centers, and external care settings, makes it difficult to detect risks early or coordinate preventive care visits, like cancer screenings, immunizations, or chronic disease management. This fragmentation is especially challenging for organizations with legacy technology, limited resources, or a broad complex system.

Rural Hospitals

Challenge: Rural facilities often operate with small teams that are overwhelmed by manual data collection, audits, and annual quality reporting. With limited staff capacity, these organizations struggle to keep pace with preventive care requirements and lack the time and visibility needed to consistently identify and coordinate care for high‑risk patients.

How dQM helps:

• Automated data capture, significantly reducing administrative burdens of small teams
• Aggregation of more complete patient information across multiple disparate facilities
• More time to identify high-risk patients and conduct preventive care outreach

Large Healthcare Systems

Challenge: Large healthcare systems face data silos across multiple EHRs, service lines, and regions. These inconsistencies hinder visibility into systemwide preventive care performance and complicate efforts to meet value-based care (VBC) requirements. Top preventive care metrics that are tracked include cancer screenings, immunization rates, blood pressure screening and follow‑up, BMI assessment with care plans, and tobacco‑use screening with cessation support.

 How dQM helps:

• Simplified ongoing quality measure performance tracking for preventive care that is system-wide
• Comprehensive, standardized, and formatted data that integrates into analytics platforms and population health management applications
• Deeper insights into trends and metrics, such as screening and care gap closure rates, to improve VBC performance.

Impact on Payers

Effective preventive care depends on complete, longitudinal patient data, yet many health plans still operate with fragmented information spread across legacy systems, claims platforms, and disparate clinical sources. Without a complete view of member health, plans struggle to accurately identify high‑risk members, evaluate care gaps, and implement targeted interventions.

Small‑to‑Midsize Regional Health Plans

Challenge: These plans often rely on manual chart retrieval from provider offices and have limited analytics resources to support frequent performance tracking and preventive care initiatives.

How dQM helps:

• Lower administrative burdens, costs, and delays associated with chart chasing
• Real-time data enabling faster identification of high-risk members and timely outreach
• More reliable quality measurement leading to effective interventions and better preventive care performance

Local and Community‑Based Health Plans

Challenge: Community‑based plans frequently struggle to access complete clinical data from diverse local provider networks, limiting visibility into member health and hindering preventive care coordination.

How dQM helps:

• Better collaboration with local providers by standardizing data and exchange of actionable clinical information
• Ongoing access to complete data for insights, enabling broader identification of at‑risk members and tailored programs
• Stronger competitiveness against larger national plans by enhancing star ratings/quality scores

Final Thoughts

Digital quality measurement strengthens preventive care, delivering shared value for both payers and providers. Ongoing access to unified data enables continuous identification of care gaps across preventive measures such as vaccinations, screenings, and chronic disease management, ensuring that those at‑risk don’t slip through the cracks. Deeper visibility enables targeted patient/member engagement, which increases preventive visit completion.

Improvement in preventive care quality helps lower avoidable ED visits, hospitalizations, and costly treatments. In addition to cost-reduction, healthcare organizations strengthen their value‑based care programs, resulting in higher incentives and better population health outcomes.

Explore how digital quality measurement can strengthen your preventive care program. Connect with our team today.

¹World Economic Forum. “Proactive digital engagement to boost healthcare systems.” (Mar. 2025)