Li Xiong, Emory University

Transcription

1 Healthcare Industry Skills Innovation Award Proposal Hippocratic Database Technology Li Xiong, Emory University I propose to design and develop a course focused on the values and principles of the Hippocratic Database Technology for managing disclosure of private healthcare data and incorporate it into current Computer Science and Biomedical Informatics curriculum at Emory University and the broad healthcare IT community. Motivation and Goal The effective use of information technology is of utmost importance to improve care quality and reduce costs by making the right health information available to the right people at the right time. This requires the capture, storage and flow of electronic health record (EHR) information across a wide range of individuals and organizations. However, disclosure of sensitive health information can have serious personal, professional, and social consequences on individuals. Health care consumers must trust that their sensitive health information will be adequately managed and protected. The HIPAA Privacy Rule regulates the use and disclosure of Protected Health Information (PHI) and establishes standards for individuals privacy rights to understand and control how their health information is used. Many state laws on protection of PHI require security of social security number, driver s license information and credit card data, many of which are often part of health care demographic or billing information. The goal of this project is to design and develop a course focused on the values and principles of the Hippocratic Database Technology for managing disclosure of private healthcare data. The course will be incorporated into current Computer Science and Biomedical Informatics curriculum at Emory University and the course materials will be made available for the broad community to train next generation healthcare IT professionals. Hippocratic Database Technology The Hippocratic Database (HDB) 1 is a set of solutions that can be used to manage disclosure of electronic health records in compliance with data protection laws without impeding the legitimate flow of information. The technology sets include: Active Enforcement (AE) is a disclosure management component that limits disclosure of personal health information at a fine-grained level. It resides in a layer above the database, rewriting user queries in strict accordance with organization policies, legal regulations, and individual patient choices. HDB policy controls are more fine-grained than conventional role-based access controls, as they enforce disclosure policies down to the cell-level in the database, and account for the purpose of access, the intended recipient of the information, and patient consent rights, in addition to the user s access privileges. 1

2 Compliance Auditing (CA) is an auditing system that tracks past disclosures of information and verify whether they complied with applicable laws and policies. Using an audit application over existing database infrastructure, it records all queries and changes to the database and uses this information to construct detailed audit trails that specify the user, recipient, purpose, time, and exact (cell-level) information disclosed for any particular database query. Sovereign Information Integration (SII) enables two or more autonomous organizations to share information about intersections between data sets without compromising the privacy or security of the remaining data. It is a scalable software solution that can be integrated into existing data environments without the need for a trusted third party. Privacy-Preserving Data Mining (PPDM) allows accurate data mining at the aggregate level while preserving privacy at the individual patient level. It uses a randomizing function to perturb sensitive values in a patient s record such that they cannot be estimated with reasonable precision. The original data distribution can be reconstructed from the randomized data to allow data mining at the aggregate level. Order Preserving Encryption enables database systems to execute queries over encrypted data without incurring significant performance hit or unnecessary cryptographic calls and still being able to utilize the existing database functionality. This allows a healthcare provider to securely outsource its sensitive data in an encrypted form to a third party while still supporting queries over the encrypted data. Anonymization enables de-identification of sensitive data that protects the privacy of individual patients, but maintains the value of the data for research purposes. The optimal k-anonymization algorithm finds optimal k-anonymizations that are resistant to data linkage attacks. Other anonymization principles and algorithms have also been developed by the research community to protect against other types of attacks. Approach The course will be focused on the values and principles of the above solutions. The lectures will cover the key algorithms and techniques for each of the above solution components as well as complementary techniques developed by the research community. The design of the course will also feature the following: Case-driven curriculum. Emory University is home to large academic medical centers with substantial investments in information systems technology supporting use of clinical data in healthcare, quality improvement and biomedical research. An Analytical Information Warehouse (AIW) that is currently under development at Emory will form the basis for motivating, studying and evaluating the HDB technology in the contexts of patient care and secondary use of clinical data. Test-bed and dataset development for hands-on learning. In order to demonstrate the concepts and allow students to understand and evaluate the HDB technologies and

3 methods, we will develop a test bed based on AIW. It will implement an application emulation layer consisting of synthetic datasets and parameterized workloads. The synthetic datasets will be developed using real database schemas and synthetic data generated based on the statistical characteristics of the real data. The workloads will consist of parameterized queries and data access requests, and will be developed by working closely with clinicians and clinical research groups at Emory to model their high-level queries and data requests and by monitoring and modeling queries against real databases. It will allow the students to develop use cases, implement policy profiles describing access to the data sets according to attributes assigned to a user, validate and evaluate HDB solutions such as Active Enforcement and Compliance Auditing with scaling of synthetic datasets and workloads for scalability testing and different use cases for usability testing. Multiple instances of the test bed databases hosting different or overlapping data subsets will be hosted on separate networked servers in order to provide a testing environment for HDB solutions such as Sovereign Information Sharing. Skills-driven assignments. A variety of assignments will be designed to build towards the combination of business + IT skills. Reading assignments with written reviews and in-class presentations will build towards creative and critical thinking, analysis and synthesis, and communication skills. Case studies will be designed in collaboration with the clinical research groups at Emory to build towards Healthcare IT best practices, business case development and analysis, as well as critical thinking skills. For example, the students can be provided with some synthetic datasets and play "data detectives" and acquire knowledge from these datasets by identifying individual patients from seemingly anonymous or innocent data. A substantial group project will be designed to build the skills on leadership, collaboration, and teaming, creative and critical thinking, business project management, solution service strategy, design and modeling, and management. Project deliverables will include project proposal, in-class project presentation, project report, and implementation. Benefit Informatics is a discipline that solves problems through the application of computing or computation, in the context of the domain of the problem. 2 The proposed curriculum will equip next generation leaders in the field of biomedical informatics or healthcare IT professionals with the combination of industry and technical skills on the state-of-the-art HDB technology for managing private healthcare data and help realize the healthcare transformation. Resources and Institution Environment Emory University is home to large academic medical centers with substantial investments in information systems technology supporting use of clinical data in healthcare, quality improvement and biomedical research. Concurrently, a number of synergistic events have occurred across campus. The Center for Comprehensive Informatics (CCI) has been established to foster collaborative projects between software system researchers and scientific research groups in clinical and translational research and biomedical 2 D.P. Groth and J.K. MacKie-Mason, Why an Informatics Degree?, Communications of the ACM, February 2010

4 informatics. The Biomedical Informatics Department within the School of Medicine has been proposed and is in planning for training leaders in the field of biomedical informatics. Meanwhile, the new concentration in Biomedical Informatics has been developed and approved within the Ph.D. program of Computer Science and Informatics. This is an unprecedented opportunity for incorporating the HDB and healthcare IT solutions into the Computer Science and Bioinformatics curriculum at Emory in training the next generation of bioinformatics and biomedical informatics researchers and Health IT professionals. Outline Plan and Milestones The proposed curriculum will be designed and fine tuned over a 9 month period and offered in Fall Month 1-3. Develop lecture notes, presentation slides, and reading assignments. Month 4-6. Develop test-bed with synthetic datasets and parameterized workloads, design case studies and group projects. Month 7-9. Fine tune and prepare the course materials including lecture notes, slides, datasets, case studies, and assignments for public releases. Month 10 (Fall 2011). I expect to offer the course as a core elective for the new Biomedical Informatics track within the PhD program in Computer Science & Informatics at Emory and the course modules to be used in part to train Health IT professionals at Emory. Lecturer Bio Dr Li Xiong ( is an Assistant Professor of Computer Science at Emory University and directs the Assured Information Management and Sharing (AIMS) research group ( She is also an affiliated faculty at the Center for Comprehensive Informatics and the Department of Biomedical Informatics currently under planning at Emory. Dr Xiong has a unique combination of background and skills in data privacy and security and health informatics to successfully develop the proposed curriculum. Dr Xiong and her group have substantial research experience in developing models and techniques aimed at enhancing privacy, confidentiality, trust, interoperability, and scalability of distributed information systems in various domains with a particular focus in health information systems. She also has substantial experiences in both developing and teaching undergraduate and graduate courses on database systems, data mining, and data security. Notably, she has developed and offered a course on Data Privacy and Security previously at Emory which covers some of the HDB technologies (the course materials are available online at Dr. Xiong holds a PhD from Georgia Institute of Technology and an MS from Johns Hopkins, both in Computer Science. She worked as a software engineer in IT industry including IBM Internet Security Systems for several years prior to pursuing her doctorate. She has recently been recognized with the prestigious Career Enhancement Fellowship by the Woodrow Wilson Foundation for her academic achievement and potential.

5 Collaborators and Endorsements I will work closely with Dr. Tyrone Grandison at IBM or assigned IBM liaison for the proposed curriculum development. Dr. Grandison leads the Intelligent Information Systems (IIS) team at the IBM Almaden Research Center which pioneered the research on HDB technology and is an expert in how to apply the HDB technology in the Healthcare industry. The close partnership with IBM will ensure the proposed curriculum clearly introduces, defines, and demonstrates the solutions for smarter healthcare and builds towards the combination of business + IT skills needed for next generation leaders in biomedical informatics and Healthcare IT professionals. I will also work closely with Dr. Andrew Post at Emory for developing the test-bed and case studies for introducing and demonstrating HDB solutions. Dr. Post is the Clinical Informatics Architect at the Center for Comprehensive Informatics at Emory and Assistant Professor in the Department of Biomedical Engineering at Emory and Georgia Tech. Dr. Post is faculty lead of the AIW project which forms the basis of the proposed curriculum and is deeply involved in health system and clinical trials information system planning. Working closely with domain experts at Emory will ensure the real impact of the proposed curriculum in demonstrating the HDB solutions for smarter healthcare. The proposed project is endorsed by Dr. Vaidy Sunderam, Professor and Chair of the Department of Mathematics and Computer Science, and Dr. Joel H. Saltz, Director of the Center for Comprehensive Informatics, Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at Emory University, and Chief Medical Information Officer at Emory Healthcare. Thank you.