(In addition to this page, you might also be interested in my Harvard Catalyst profile.)
The big picture: Healthcare Informatics is a collision of fields that interact in a beautifully complex way, revealing a Mandelbrot of computer science, economics, and psychology. In information technology, there are three stable operating systems used successfully by millions across the world, with portable document formats and data exchange. In healthcare, EHRs are failing, they are making clinicans less productive, and hospitals are uninstalling them. Data interchange "standards" like HL7 are incompatible across different providers' systems, the V3 RIM is not being adopted, and only the barest usage of CDA is apparent.
- What part is technological? Experts say that health information is several orders of magnitude more complex than bank data. How can we technologists simplify this added complexity?
- What part of this is social? Injecting technological artifacts into the "adaptive complex system" of healthcare will create power struggles, trust issues, and automation bias, as well as changing physician workflow.
- What part is due to regulation? Does having external bodies enforcing technology standards on software developers help clinicians, or harm them? Or are we just enforcing the wrong standards? Are government projects like NHIN encouraging feasible innovation, or is it just a pipe dream?
My particular interests:
I believe that technology can and should have the same positive impact in the medical world it has in the consumer world, and that the nation's massive investment in Health Information Technology should translate into accelerated innovation and discovery and improved quality, efficiency, and safety of healthcare. I feel that computers are a paradigm shift in medicine, rather than an evolution of paper-based processes. To that end, I am interested in fundamentally new ways of using medical data that were not possible in paper records.
- How can we learn from the mass of EMR data, and what can we learn from it to help clinicians perform their work more accurately and efficiently? In the world-wide-web, we believe the crowd. We trust them to help us select movies (Netflix), to shop (Amazon), and to filter our spam (Gmail). In healthcare, 'meaningful use' regulations will increasingly cause huge warehouses of data to be amassed in our EMRs. However, clinical decision support systems and health standards are generally developed by experts carefully studying small cohorts of patients. In healthcare, how much is the crowd (of highly trained physicians) to be trusted? How can we leverage data mining techniques developed over the last decade to extract crowd wisdom from the masses of data?
- How can we effectively, safely, and efficiently share medical data to improve population health? The Office of the National Coordinator For Health Information Technology has sponsored an initiative called Query Health to develop standards and a platform to “send questions to the data” for population health measurement. This distributed-query approach avoids many of the data-sharing issues present in other approaches to health information exchange. It might therefore provide the foundation for population health surveillance. However, the speed of such an approach is sometimes called into question, and it does not handle duplication of patients across sites.
- How can we revolutionize the EMR through web-like interfaces and automatic summarization? Services like Google use a single interface to perform search, calculations, and many other functions. EMRs, on the other hand, are often rigid point-and-click interfaces prevalent before the web. Many clinicans find the amount of clicking and the awkward drop-down-menus to be very aggravating, which is unacceptable in a time-constrained environment. Additionally, EMRs need to display very complex historical and anatomical data in easy-to-digest ways. How can we summarize complex data in a rapidly digestable format?
- What is needed to make PHRs viable? Personal Health Records (PHRs) have appeared over the last several years with the promise of helping people manage their health information more easily. Yet most existing PHRs are only slightly more useful than an unstructured collaborative document. Few have adopted PHRs, except for those with massive information-cataloging needs (e.g., caregivers of elderly adults). However, there may be a use-case for the PHR. Patients are aggravated they have no access to their health information. Physicians, also, express frustration at having limited access to patient-gathered information (e.g., blood glucose logs). Patient portals have been successful in providing secure communication and some medical information exchange between patients and single hospital systems. Services such as PatientsLikeMe and CureTogether have been successful in using collective patient information to build community and collaborative disease profiles. A useful PHR must integrate these features. Essentially, the PHR should be part of the social web, allowing us to share medical information (in a controlled way) in the same vein that we share our activities with Facebook friends. It is not a disconnected application, but a tool in our increasingly information-hungry society. Of course, this raises many issues of security, privacy, liability, and data ownership.
Design and implementation by Jeff Klann in HTML/CSS/PHP, except the
tooltip script and tooltip stylesheet,
which are under copyright by The Nucleus Group.
Thanks also to Nucleus CMS for inspiring this site's look-and-feel.