- Austin Group, Dell Medical School Team on Healthcare Blockchain
The NLST was a randomized controlled trial to determine whether screening for lung cancer with low-dose helical computed tomography (CT) reduces mortality from lung cancer in high-risk individuals relative to screening with chest radiography. Around 54,000 participants were enrolled between August 2002 and April 2004.
The NLST datasets include data on participant characteristics, screening exam results, diagnostic procedures, lung cancer, and mortality. Images from over 75,000 CT screening exams are available, and more than 1,200 pathology images from a subset of NLST lung cancer patients may be viewed.
The Rensselaer researchers explained that currently clinical data is stored and managed in a fragmented way, which creates problems for information exchange at the point of care and inhibits large-scale research using AI/ML.
“Failure in timely access to health information could impede effective treatment decision-making, which will adversely affect patient health, and also incur unnecessary costs such as duplicated tests,” the researchers noted.
“While the explosion in the number and capability of tools eases the process of data collection, data retrieval and information analysis have been slow and complicated in the field of medicine, which has become a global challenge faced by both the developed and developing countries,” they added.
The researchers propose to develop blockchain-based technology that can help address obstacle to sharing medical images in the following three areas: improving security and privacy protection, maintaining flexibility, and enforcing data sovereignty.
The researchers explained that medical imaging is a central part of diagnostics in the current healthcare environment. Medical imaging databases and platforms lend themselves to big data initiatives and the application of AI/ML technology. At the same time, the integration of quality data becomes increasingly challenging in streamlining workflow and improving patient care.
The Rensselaer project seeks to develop a distributed information system prototype that helps to address these issues in image data transfer and provide a prototype for health information management in a broader context.
More specifically, the aims of the project are to:
- Develop a prototype system in IBM Hyperledger for image data sharing between entities from data acquisition, storage, and transportation between health care providers, patients, and the research community
- Work on privacy-preserving techniques for safeguarding the identity of the patients when acquiring the image data
- Write novel algorithms for storing and retrieving image data facilitated by the blockchain
- Conduct a cost-effectiveness analysis on the prototype system, accounting for costs and outcomes such as changes in provider workflow and healthcare quality
The Rensselaer research team includes Jianjing Lin in the Department of Economics, Ge Wang in the Department of Biomedical Engineering, Lirong Xia in the Department of Computer Science, and Oshani W. Seneviratne at the Institute for Data Exploration and Applications.
According to a recent Accenture survey, two-thirds of healthcare executives predicted that the combination of blockchain, artificial intelligence, virtual reality, and quantum computing will have a “transformational” impact on their organization over the next three years.
These four technologies are “poised to become the foundation for next-generation products and services. Healthcare leaders in the … future will be prepared to combine and exploit those competencies as the technologies reach enterprise-level maturity,” the report observed.
Eighty-nine percent of healthcare execs are currently experimenting with one or more these technologies.
These “technologies are, or will be, powerful on their own. But as they advance, they will push each other forward further. Already, early pairings reveal game-changing combinatorial effects for healthcare,” the report related.