How Iodine Software is Increasing CDI Accuracy Through AI and Machine Learning
In an era where data is as vital as Breathable air, its interpretation and application within the healthcare industry have taken center stage. Medical informatics, particularly Clinical Document Improvement (CDI), has experienced significant advancements thanks to innovations like Artificial Intelligence (AI) and Machine Learning (ML). These technologies promise to revolutionize CDI, thereby augmenting patient care and outcomes. Studies suggest machine utilizing AI and ML for increasing CDI accuracy and CDI team productivity, ultimately leads to better patient treatment and healthcare delivery.
With such technological advancements, how do organizations harness AI and ML to improve CDI, enhancing healthcare services? How can these technologies revolutionize the management and interpretation of clinical data to ensure more effective patient treatment?
Welcome to this enlightening episode of Iodine Intelligence hosted by Hillary Kennedy. Kennedy’s guest, Lance Eason, Chief Data Scientist at Iodine Software provided her with a deep-dive how Iodine Software, provided her with a deep-dive into how Iodine Software leverages AI and ML to improve the accuracy of Iodine’s CDI solutions, setting the company as a market leader in the AI/ML technology space.
During their conversation, Kennedy and Eason discuss the following:
- The significance of AI and ML in increasing CDI accuracy and its impact on patient care.
- The evolution and iterative improvement of Iodine Software’s models over the years.
- The comparison between Iodine Software’s approach and their competitors in the AI/ML landscape.
Lance Eason, an industry expert with a decade of experience at Iodine Software, has made noteworthy contributions to data science applications in healthcare. Known for his dedication to using software to solve complex problems that yield tangible business value, Eason’s work at Iodine Software has helped position the company at the forefront of AI and ML applications in healthcare. His innovative approach and industry acumen have played a pivotal role in developing Iodine Software’s advanced CDI solutions.
With a wealth of knowledge and practical insights, Eason discusses how Iodine Software has applied different AI and ML models to increase prediction accuracy for various disease conditions, from electrolyte imbalances to complex diseases like sepsis. Through numerous iterations over seven years, Iodine’s models have seen drastic improvements in performance and accuracy. Eason also compares Iodine Software’s approach and that of their competitors, elaborating on how the former has emerged as an industry leader in the AI/ML space.
