Survey Reveals Healthcare AI Users Desire Enhanced Tools for Unstructured Data Insights
In an era where the integration of artificial intelligence in healthcare is gaining momentum, a recent survey conducted by emtelligent sheds light on the challenges faced by AI users in this sector. The survey, which gathered insights from nearly 250 leaders within healthcare organizations, reveals that while there is a recognition of the potential benefits of utilizing unstructured data for innovation and predictive modeling, a significant portion of users report dissatisfaction with their existing tools directed at unstructured data tasks.
According to the results, 55% of responding organizations have been engaging with AI or natural language processing (NLP) technologies for a duration of less than two years, highlighting a relatively nascent stage in the adoption of these pivotal tools. The urgency to efficiently extract and organize unstructured clinical data cannot be overstated, given that it constitutes approximately 80% of the healthcare data landscape—often found in forms such as clinician notes, PDFs, and faxes.
Despite this overwhelming amount of data, less than 40% of respondents believe they have an ideal solution for deriving insights from unstructured data, reducing operational costs, or driving new product development using this data. Specifically, the figures stand at 38% for having a perfect extraction solution, 37% for using such insights to lower costs, and 39% for product and service innovation.
The survey additionally uncovers the varying priorities among healthcare organizations based on their sub-sector. For example, health systems prioritize patient summaries, care management, and quality enhancement as the top applications for unstructured data. Conversely, pharmaceutical companies and clinical research organizations seek to streamline data entry processes and augment clinical trial efficiencies. In contrast, payers are keen on leveraging unstructured data to refine quality ratings, engage in risk assessments, and gather real-world evidence.
Moreover, the survey highlights that healthcare organizations universally aim to harness unstructured data to improve patient outcomes and heighten customer service experiences. However, the journey towards this goal is riddled with complications. A staggering 83% of users have opted to collaborate with third-party experts to navigate the complexities associated with transforming unstructured data into a usable format. Only 14% of organizations depend solely on internally developed tools.
Barriers to the successful implementation of AI in healthcare were also evident from the survey responses. The most significant challenges include data privacy and security concerns, along with organizational skepticism about the benefits and tangible outcomes of such technologies. Despite these obstacles, there is a palpable optimism among participants, with 95% expressing expectations of measurable improvements from their AI-driven unstructured data initiatives within the next two years, and 52% anticipating results within just one year.
In reflecting on these findings, Dr. Tim O'Connell, CEO and co-founder of emtelligent, emphasized the critical role unstructured clinical data plays in propelling healthcare innovation. "The insights derived from this survey underscore the immense potential of unstructured clinical data in enhancing healthcare operations and patient outcomes. This is why we see a pronounced interest in partnerships with specialized vendors to optimally leverage these insights moving forward,” he stated.
For additional information on emtelligent and their ongoing commitment to transforming healthcare through AI, visit their website at emtelligent.com. The study was conducted between August 26 and September 3, 2024, targeting executives at healthcare provider and payer organizations with awareness of NLP or large language model solutions pertinent to their duties. Only those involved with deploying or planning to deploy AI tools for extracting unstructured clinical insights participated in the study.
In conclusion, as healthcare organizations navigate the complexities of unstructured data, it is clear that enhancing existing tools and fostering collaborations will be pivotal in unlocking the true potential of AI-driven insights in the industry.
According to the results, 55% of responding organizations have been engaging with AI or natural language processing (NLP) technologies for a duration of less than two years, highlighting a relatively nascent stage in the adoption of these pivotal tools. The urgency to efficiently extract and organize unstructured clinical data cannot be overstated, given that it constitutes approximately 80% of the healthcare data landscape—often found in forms such as clinician notes, PDFs, and faxes.
Despite this overwhelming amount of data, less than 40% of respondents believe they have an ideal solution for deriving insights from unstructured data, reducing operational costs, or driving new product development using this data. Specifically, the figures stand at 38% for having a perfect extraction solution, 37% for using such insights to lower costs, and 39% for product and service innovation.
The survey additionally uncovers the varying priorities among healthcare organizations based on their sub-sector. For example, health systems prioritize patient summaries, care management, and quality enhancement as the top applications for unstructured data. Conversely, pharmaceutical companies and clinical research organizations seek to streamline data entry processes and augment clinical trial efficiencies. In contrast, payers are keen on leveraging unstructured data to refine quality ratings, engage in risk assessments, and gather real-world evidence.
Moreover, the survey highlights that healthcare organizations universally aim to harness unstructured data to improve patient outcomes and heighten customer service experiences. However, the journey towards this goal is riddled with complications. A staggering 83% of users have opted to collaborate with third-party experts to navigate the complexities associated with transforming unstructured data into a usable format. Only 14% of organizations depend solely on internally developed tools.
Barriers to the successful implementation of AI in healthcare were also evident from the survey responses. The most significant challenges include data privacy and security concerns, along with organizational skepticism about the benefits and tangible outcomes of such technologies. Despite these obstacles, there is a palpable optimism among participants, with 95% expressing expectations of measurable improvements from their AI-driven unstructured data initiatives within the next two years, and 52% anticipating results within just one year.
In reflecting on these findings, Dr. Tim O'Connell, CEO and co-founder of emtelligent, emphasized the critical role unstructured clinical data plays in propelling healthcare innovation. "The insights derived from this survey underscore the immense potential of unstructured clinical data in enhancing healthcare operations and patient outcomes. This is why we see a pronounced interest in partnerships with specialized vendors to optimally leverage these insights moving forward,” he stated.
For additional information on emtelligent and their ongoing commitment to transforming healthcare through AI, visit their website at emtelligent.com. The study was conducted between August 26 and September 3, 2024, targeting executives at healthcare provider and payer organizations with awareness of NLP or large language model solutions pertinent to their duties. Only those involved with deploying or planning to deploy AI tools for extracting unstructured clinical insights participated in the study.
In conclusion, as healthcare organizations navigate the complexities of unstructured data, it is clear that enhancing existing tools and fostering collaborations will be pivotal in unlocking the true potential of AI-driven insights in the industry.
Topics Health）
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