Clinical Intelligence/Clinical Efficiency

Apervita Uses Carta Healthcare’s AI-Driven Clinical Data Abstraction

Addition of technology to save clinicians hours manually documenting quality measurement data

Apervita, the trusted platform for healthcare collaboration, today announced that it has added Carta Healthcare’s artificial intelligence (AI)-powered data abstraction technology to the Apervita VitalTM Platform’s robust interoperability layer, which allows providers, payers and registries to more effectively utilize data generated in the course of patient care. This new feature will enhance Apervita’s quality measurement and clinical intelligence solutions.

Research suggests that 80% of data in electronic health records (EHRs) is unstructured, and often not utilized. This unstructured data, such as notes from physicians, radiologists and nurses, can affect the accuracy of quality scores and, ultimately, reimbursement. As a result, many organizations invest millions of dollars into manual chart abstraction.

The combination of Carta Healthcare and Apervita’s technologies will greatly reduce the time it takes to manually gather data for quality registries, reportable quality measurements and customer quality measures. These cloud-based tools can also help make digital quality measurement more accurate. For conditions like sepsis, automated analysis of words in clinical notes can detect indicators such as “yellow wound” and its variations.

Data abstraction—taking information from the clinical record, often stored in free-text fields such as notes—is a manual process that robs physicians and nurses of time they could otherwise spend with patients. One study estimated that physicians spend an average of nearly three hours per week entering information related to quality measures, while the average staff member spends over 10 hours. Researchers projected that quality measurement documentation across only four specialties costs U.S. healthcare $15.4 billion annually. Data abstraction from charts represents a significant share of that total.

Apervita’s comprehensive data abstraction capabilities, powered by Carta Healthcare’s Atlas solution, use a combination of technology, people and processes to analyze patient records for quality reporting and clinical insights. AI-enabled natural language processing (NLP) pulls data from medical records, which are then validated by experienced nurse data abstraction professionals. This unique technology drastically reduces the amount of time needed for abstraction (upwards of a 50% reduction), allowing it to be reallocated to patient care. Additionally, the winning combination of AI technology and expert nurse validators allows for an increase in chart abstraction accuracy. Together, the technology and data abstractors unify structured and unstructured clinical data.

“Abstracting clinical content from unstructured fields in the EHR allows Apervita greater access to data to accurately measure and improve quality,” said Rick Howard, Apervita Chief Product Officer. “We selected Carta Healthcare as a partner because we believe its technology is unique, will increase data accuracy and save documentation costs for providers. These capabilities further support Apervita’s mission to enable the Learning Health System.”

Apervita is committed to helping enable the Learning Health System—a framework of continuous learning and improvement to drive better outcomes and cost efficiencies. The Apervita Vital Platform, purpose-built for healthcare, powers Apervita’s core solutions, including quality measurement and clinical intelligence. It enables the transparency and collaboration required to solve the industry’s most challenging issues.

“Carta Healthcare and Apervita are aligned to empower health systems to use their data and enable better patient care,” said Matt Hollingsworth, Carta Healthcare CEO. “Carta Healthcare’s AI technology and data collection processes—along with Apervita’s next-generation quality measurement and clinical insights across healthcare stakeholders—will ensure that the correct data solves real issues in healthcare.”

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