Chief Medical Officer at Intelligent Medical Objects
Dr. Andrew Kanter joined IMO in 1995 and now serves as the Chief Medical Officer. He provides thought leadership on IMO’s clinical roadmap and helps guide the company in addressing key challenges within the industry. He has also held the roles of Chief Operating Officer and President at IMO. Andrew is an Assistant Professor of Clinical Biomedical Informatics and Clinical Epidemiology at Columbia University and has served as the former Director of Health Information Systems/Medical Informatics for the Millennium Villages Project at the Earth Institute. He is a Fellow of the American College of Medical Informatics and the American Medical Informatics Association.
Session: The importance and challenges of health data standardization
In healthcare, the volume and diversity of healthcare data has grown exponentially in recent decades due to a variety of regulatory and market factors, like the shift from paper to electronic health records (EHR), the proliferation of new sources of patient data, and the recent 21st Century Cures Act. While there is great potential inherent in this torrent of data, its promise cannot be fully realized without effective, accurate, and scalable normalization – a process that reduces redundancy, improves data integrity, and establishes a common understanding of healthcare information.
A complete and accurate data set is the foundation for a variety of use cases, such as a hospital’s quality improvement initiatives; alerts facilitated by a health information exchange; or the identification of ideal patients for clinical trials. IMO will discuss the challenging process of getting to a complete and accurate data set. This crucial step – which is essential to enabling any meaningful data analysis – often takes longer than anticipated due to the extensive manual mapping of standardized codes and terms and the need for human review.
Intelligent Medical Objects (IMO), Chief Medical Officer, Andrew S. Kanter, will discuss how the COVID-19 crisis has highlighted the importance of normalization related to patient data aggregation for care, research and surveillance. The pandemic has demonstrated an urgent need to report cases, understand the severity of illness, and what sorts of treatments are working and not working. However, data is often represented in multiple ways; frequently includes only free text or local codes; and can be compromised by other data entry issues. Putting technologies in place to quickly normalize and standardize this data, transform it and share it will prepare health systems for similar crises in the future.
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