The COVID-19 pandemic has uncovered the need for greater transparency and interoperability of clinical data to drive increasingly complicated public health initiatives
Challenges with data quality, standard adherence, and communication gaps caused by silos at both the state and national level limit the ability to gain real-time population insights on critical vaccination data, COVID-19 test results, and medical and demographic documentation from providers and hospital settings.
Over the last two years, Availity has been collaborating with the California Department of Public Health (CDPH) to identify and improve issues related to data quality, timeliness, and accuracy. For COVID-19 lab reporting we found:
To solve this challenge, Availity Fusion normalizes these variations into a single standards-based code and display name using national standards like LOINC and SNOMED. This uniformity enables downstream analytical capabilities to be more streamlined, intentional and actionable.
As shown in the chart above, generated from a recent data quality analysis performed across 14 different EMRs, only about 49% of data across eight major clinical domains was validated and confirmed usable on the inbound, compared to 83% of data being usable after being upcycled by Availity Fusion.
Breaking down clinical data silos is essential for healthcare organizations to improve care coordination, reduce care gaps, and provide better patient care. To achieve this, 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 interoperable sharing of high-quality data from various sources, including vaccine registries, labs, and provider generated medical charts
When analytics are performed within silos, they only provide a limited glimpse into the patient’s health status and history. However, when data is shared and integrated across silos, insights are more comprehensive and longitudinal with respect to actual care evolution