Using AI Models to Holistically Care For Patients: Data Quality and Challenges
Digital Scientists is a technology strategy and development firm based in Alpharetta, Georgia that works with healthcare clients across acute and post-acute care spaces. The company is dedicated to creating innovative and digital health transformation solutions that range from strategy to design, to development, to transfer. Digital Scientists is implementing the latest technologies in healthcare, including telehealth, AI, ML, and getting devices connected. In this article, we will discuss the challenges of using AI models in healthcare due to the quality and availability of data, potential biases in the models, and the limitations of ChatGPT in medical record keeping.
Data Quality Challenges
Data quality is one of the biggest challenges facing the application of AI models in healthcare. Although a lot of data has been digitized, the quality of the data may not be sufficient to feed into an AI model to get good high-quality information and insights. This is because there are issues with the availability of real-world data that is quality data coming out of our systems. All of these models are basically just a theoretical model until we get to a point where they can be tested on real-world data with good sensitivity and specificity.
Potential Biases
Another challenge faced by AI models is the potential biases in their development and implementation. For instance, a model developed based on a population set in Boston may not work when shifted to Florida. As such, it is essential to develop responsible AI by ensuring that these models meet certain thresholds. Companies must take honest steps to eliminate any biases in their AI models.
Comprehensive Patient Profiles
In the future, comprehensive patient profiles that include genomic and ancestral histories will be necessary. A holistic view of a patient record is essential to manage that patient holistically, irrespective of the care setting. Digital Scientists is excited to include new technologies such as telehealth and AI in their innovation and digital health transformation solutions to address these challenges.
Limitations of ChatGPT
ChatGPT is being used for potential use cases in medicine and wellness. The natural language processing model can be used to provide real-time evidence-based recommendations to healthcare providers to improve patient outcomes. However, the limitations of ChatGPT in medical record keeping must be addressed to ensure patient safety.
In conclusion, while using AI models for holistic patient care presents its challenges, Digital Scientists is at the forefront of implementing these technologies to improve patient outcomes. The availability of good quality data, elimination of biases in model development and implementation, and the development of comprehensive patient profiles are all essential in the development of responsible AI. ChatGPT holds much promise in providing real-time recommendations to healthcare providers, but its limitations must be addressed.
