Overcoming Fragmentation to Improve Health Equity and Care Outcomes
By Paulo Pinho, M.D., VP & Medical Director of Innovation, Availity
X: @Availity
X: @pbpmd
The COVID-19 pandemic highlighted the importance of sharing accurate, real-time data across various players in the healthcare ecosystem. Since then, enhanced interconnectedness and collaboration among healthcare stakeholders, such as providers, labs, hospitals, pharmacies, and registries, have become standard in delivering maximum benefits for the larger population. Despite ongoing changes in the regulatory landscape geared towards interoperability, challenges such as data access, accuracy, and silos among healthcare entities have repeatedly hindered identifying population trends and risk factors and providing equitable care.
These issues continue today and significantly impede thorough analysis of the medical and demographic documentation necessary to drive effective public health response, particularly to at-risk populations.
Embracing Semantic Interoperability to Improve Clinical Data Quality
Clinical data sourced from electronic health records (EHRs), labs, and health information exchanges (HIEs) contain unique and timely patient details, such as vital signs, test results, diagnoses, immunizations, and more. However, the non-conformant coding, absence of standardization, unstructured and inconsistent documentation in workflows, and poor data interoperability have obscured a real-time, data-driven, longitudinal view of population health. Lack of interoperability has been devastating for at-risk populations, and data show that infection, hospitalization, complications, and mortality varies significantly by race and ethnicity.
To address this, healthcare organizations can use semantic interoperability solutions to bridge gaps between disparate healthcare systems and data sources. Semantic normalization enables a more comprehensive understanding of patient populations critical to making the informed decisions required to drive public health interventions. A semantically normalized record aligned with national data quality standards and accessible across providers and care sites can help level the playing field and reduce care gaps and poor data quality that regretfully promotes care inequities for marginalized communities.
Realizing the Potential of High-Quality Clinical Data
Healthcare data consumers can start by investing in an integrated technology infrastructure that promotes seamless data sharing and interoperability. For public health, this infrastructure should facilitate the collection, analysis, and interoperability of high-quality data from various sources, including vaccine registries, labs, and provider-generated medical charts.
With the implementation of Availity Fusion™, our API-based technology, clients and partners have effectively integrated robust clinical data tailored to their specific needs. Availity Fusion’s comprehensive five-step process, known as Upcycling Data™ transforms raw healthcare data — from EHRs, aggregators and health information exchanges, health plans, providers, health systems and labs — and automatically delivers a consistent, structured, standards-based data asset in real time.
5 Steps to Upcycling Data
- Normalization of data to industry standard technologies. Creating a common language for data exchange and achieve semantic interoperability.
- Enrichment of data with standard metadata and classifications. Ensuring efficient analytic queries and optimize data for the most effective downstream use.
- Reorganization of data to appropriate clinical documentation sections. Creating a complete, updated view of patient history for appropriate outreach and care delivery.
- Deduplication of data across disparate inbound sources. Eliminating duplicates to accurately report volumetric data and trends over time.
- Summarization of data into complete digital patient records. Building a summarized record to effectively trend health and clinical improvement over time.
Parting Words
Prioritizing improved data quality and strengthening population health is essential for advancing the healthcare system. By leveraging high-quality, semantically interoperable data, healthcare organizations can overcome challenges, promote health equity, and make more informed decisions. Upcycled data not only enhances the delivery of healthcare services but also enables a more informed, proactive, and timely response as the world continues to face emerging health challenges.
By continuously striving for better data quality and fostering stronger population health, we can create a future where healthcare systems are equipped to address evolving needs effectively and equitably, strengthening our country’s public health reporting infrastructure and improving the well-being of individuals and communities.
This article was originally published on the Availity blog and is republished here with permission.