Keith Dreyer, Chief Data Science Officer, Mass General Brigham
Keith J. Dreyer, DO, PhD, FACR, FSIIM, is Chief Data Science Officer and Vice President for Enterprise Medical Imaging for Partners Healthcare. He also holds the positions of Vice Chairman of Radiology at Massachusetts General Hospital, Chief Data Science and Information Officer for the Departments of Radiology at Massachusetts General Hospital and Brigham and Women’s Hospital, and Associate Professor of Radiology at the Harvard Medical School.
In addition to serving as vice chairman of radiology and informatics at Massachusetts General Hospital, Brigham and Women’s Hospital, and Mass General Brigham Data Science Office Imaging AI Governance Committee, Dr. Keith Dreyer is the chief data scientist and chief imaging information officer for the organization. In support of Mass General Brigham’s strategic ambitions, Dr. Dreyer leads the global DSO team as chief data science officer, developing and scaling sophisticated analytic capabilities. He collaborates with senior leadership at Mass General Brigham as well as executive leadership from the public and commercial sectors to promote the transformation of health care through advanced data science, machine learning, and artificial intelligence. In addition, Dr. Dreyer teaches radiography as an associate professor at Harvard Medical School. With a bachelor’s degree in mathematics, a master’s degree in image processing, and a doctorate in computer science, he is ABR board certified in diagnostic radiology. Furthermore, Dr. Dreyer received medical fellowships from Harvard University at Mass General Hospital in both magnetic resonance imaging and imaging informatics.
In addition to serving in a variety of advisory, committee, and board capacities with the American College of Radiology, Radiological Society of North America, Society of Imaging Informatics in Medicine, and other international healthcare organizations, Dr. Dreyer is the chief science officer of the Data Science Institute at the American College of Radiology. In addition to giving lectures all over the world on clinical data science, cognitive computing, clinical decision support, clinical language understudying, digital imaging standards, and the effects of technology on health care quality and payment reform initiatives, he is the author of hundreds of scientific papers, presentations, chapters, articles, and books.
2023
Mass General Brigham released its financial statistics for the fiscal year that concluded on September 30, 2023. These numbers show that the healthcare industry is still facing issues with capacity and manpower. The system generated an operating loss of $48 million (-0.3%), including losses from provider activity of $45 million (-0.3%) and insurance activity of $3 million (-0.2%), excluding one-time revenues primarily related to federal transfers linked to the COVID-19 pandemic.
The pressures on labor and supplier costs that escalated in 2022 have lessened, but they still have an effect on how well the system operates. In order to address these persistent issues, Mass General Brigham is concentrating on lowering its long-term spending trend, streamlining systemwide capacity management, and pursuing clinical integration initiatives that facilitate patients’ easier access to care at the appropriate location and time.
Due to certain government reimbursements that do not fully cover the cost of providing care to Medicare, low-income, and uninsured patients, the system absorbed $2.4 billion in Medicare, Medicaid, and Health Safety Net shortfalls in 2023. This represents an increase of $112 million (5%) over the shortfall absorbed in 2022.
In 2023, the system recorded a $1.2 billion gain overall, of which $1.1 billion came from nonoperating activities. Nonoperating activity include charitable giving and profits and losses on investments and interest rate swaps, which can differ greatly from year to year because of financial market volatility. The system had a $2.3 billion loss in 2022, of which $1.8 billion was a nonoperating loss.
Pharmaceutical companies like Amgen, Bayer, and Novartis are using AI to accelerate patient recruitment for clinical trials and reduce testing costs. AI systems scan extensive healthcare data to identify trial candidates, potentially halving the time needed to enroll patients. This approach has saved millions of dollars in drug development. Microsoft’s DeepSpeed4Science initiative aims to apply deep learning in natural sciences, including drug development and renewable energy. Nvidia’s venture capital arm, NVentures, supports startups advancing drug discovery with generative AI, such as Generate:Biomedicines, which uses machine learning to create clinical protein complexes and enzymes.
