Results reveal familiarity with potential workflow benefits, although concerns about human oversight and quality remain
The vast majority of clinical data abstractors believe AI would save them time, effort and cost, but concerns about data quality without human oversight remain, according to survey results from Carta Healthcare®, whose mission is to ignite healthcare improvement by unlocking the power of clinical data.
This is the third round of results from a national online survey of clinical data abstractors, who answered questions about pressing issues facing their roles and the industry. Previously released results found that clinical data abstractors were neutral to very dissatisfied with the highly manual nature of their job, which involves harvesting data from EHRs and other systems and entering data into clinical registry forms. They cautioned that data quality may suffer because of these inefficiencies.
The latest survey results reveal that abstractors are excited about the potential of AI in their position. The vast majority (85%) agree that automation would save time, effort, and costs. Likewise, nearly as many abstractors (83%) agreed that AI would reduce clinicians’ administrative workload, 75% believed it would speed up the abstraction process, and 50% agreed that it would improve data quality.
“The manual clinical data abstraction process is long overdue for transformation, and no one understands that better than the trusted experts who perform these duties day in and day out,” said Carta Healthcare CEO Brent Dover. “These survey results, especially when viewed in the context of our other two rounds of findings, clearly demonstrate that these clinicians are eager for new, safe and effective methods to do their jobs. They want to eliminate the manual effort associated with abstraction, significantly reduce the enormous time and costs, and ensure that the highest-quality data is captured and shared with the healthcare community.”
Access and Acceptance Obstacles Remain
While clinical data abstractors applaud AI tools to automate their manual tasks, the majority (61%) of survey respondents reported that their health system employer does not offer such solutions. Regardless, over half (53%) of abstractors agreed they would like their employer to adopt such tools—only 7% were opposed.
Despite this enthusiasm, 61% of survey respondents stated that AI could not yet fully replace a human in their role. 69% reported concern about the quality of AI-generated data, and just as many said they were worried about the lack of human oversight in the process. However, at the same time, 54% of respondents reported being very optimistic or somewhat positive about using AI, 28% were neutral, and only 15% reported negative sentiments.
Fortunately, Carta Healthcare can help ease adoption concerns by combining the power of AI technology with expert human abstractors to abstract data and insights that act as catalysts for healthcare transformation. Health systems and hospitals using the Carta Healthcare platform can lower their data abstraction costs by more than 50%, reduce per-case abstraction time by two-thirds, and achieve an average of 98% to 99% Inter-Rater Reliability (IRR), a data abstraction consistency and dependability measure.
“AI innovation and development is constantly evolving and improving, so it is understandable that clinical data abstractors might be apprehensive or uncertain about this game-changing technology,” Dover said. “However, the safety, accuracy and efficacy of Carta Healthcare’s AI-powered clinical data abstraction platform have been demonstrated in health systems and the recipient of several prestigious industry awards, including a Merit Award, a Pinnacle Award, and a BIG Innovation Award. Most importantly, we have discovered that as abstractors learn more about Carta Healthcare, they understand how it can significantly improve their jobs and patients’ health by ensuring complete, up-to-date registry data.”
Survey methodology: In November 2024, a national online survey was conducted by Reaction Data, a market research firm focused on the healthcare information technology industry. Relevant respondents opted-in to an online survey, based on their role and subject matter expertise. If a potential respondent did not match the appropriate criteria, respondents opted-out. As such, only qualified responses to the survey were received.
