New Media Medicine

The doctor-patient relationship is deteriorating. CollaboRhythm implements new paradigms in doctor-patient interaction to improve health outcomes and the patient experience. It uses ubiquitous connectivity, collaborative decision-making, and compelling interfaces to educate patients, improve treatment adherence, and deliver care seamlessly at any point in time or space. The foundation is a speech- and touch-controlled hub for the office where doctor and patient make shared decisions and where patients are encouraged to actively engage with their data. Patients also own their data: everything they see in the doctor’s office is available at home, when they visit another doctor, change jobs, or move across the world. Patients can contribute data that are important to their health and lifestyles—information that today is invisible to the doctor. By making patients active, informed participants in their own care, we believe we can reduce health-care costs, increase quality, and improve health outcomes.

The choices we make about diet, environment, medications, or alternative therapies constitute a massive collection of "everyday experiments." These data are largely unrecorded and underutilized by the traditional research establishment. Collective Discovery aims to leverage the intuition and insight of patient communities to capture and mine information about everyday experiences. Moving the community discourse from anecdotes to data will lead to better decision-making, stronger self-advocacy, identification of novel therapies, and inspiration of better hypotheses in traditional research, accelerating the search for new drugs and treatments. The unique characteristic of our Collective Discovery model is the use of knowledge representation and natural language processing to mediate communal hypothesis generation and to compensate for methodological errors and self-reporting bias. This model is being deployed in a real-world context as part of a partnership with the LAM Treatment Alliance and the greater LAM community.

Currently only 50% of patients with chronic diseases take their medications. The problem is not simple forgetfulness; it is a complex combination of lack of understanding, poor self-reflection, limited social support, and almost non-existent communication between provider and patient. ForgetAboutIT? is a system to support medication adherence which presupposes that patients engaged in tight, collaborative communication with their providers through interactive interfaces would think it preposterous not to take their medications. Technically, it is an awareness system that employs ubiquitous connectivity on the patient side through cell phones, televisions, and other interactive devices and a multi-modal collaborative workstation on the provider side.

HealthMap is a multilingual, real-time disease outbreak tracking and visualization system. Launched in fall 2006, the Web site collects over 300 reports per day in seven languages, from both general news media and public health sources around the world. Updated hourly, the system filters these reports to determine relevance, disease, location, and duplication clustering by means of a series of custom-designed, automated, text-processing algorithms. Relevant reports are then aggregated and displayed on a freely available dashboard where users can tailor the view according to date, disease, location, and source. HealthMap provides an overview of real-time information on emerging infectious diseases, and has particular interest for public health officials and international travelers.

With HealthMap's Outbreaks Near Me application, you have all of HealthMap's latest real-time disease outbreak information at your fingertips. Open the app and see all current outbreaks in your neighborhood, including news about H1N1 influenza ("swine flu"). Search and browse outbreak reports on the interactive map, and set up the app to alert you with a notice automatically whenever an outbreak is occurring in your area. If you know of an outbreak not yet on the map, be the first to report it using the app's unique outbreak reporting feature. You will be credited and your report will be featured on the Website. With this iPhone app, we are launching an exploration of crowd-sourced, user-generated, people-powered disease outbreak tracking and collaboration.

Increasing understanding of how to categorize patient symptoms for efficient diagnosis has led to structured patient interviews and diagnostic flowcharts that can provide diagnostic accuracy and save valuable physician time. But the rigidity of predefined questions and controlled vocabulary for answers can leave patients feeling over-constrained, as if the doctor (or computer system) is not really attending to them. I’m Listening is a system for automatically conducting patient pre-visit interviews. It does not replace a human doctor, but can be used before an office visit to prepare the patient, deliver educational materials or triage care, and preorder appropriate tests, making better use of both doctor and patient time. It uses an on-screen avatar and natural language processing to (partially) understand the patient's response. Key is a common-sense reasoning system that lets patients express themselves in unconstrained natural language, even using metaphor, and that maps the language to medically relevant categories.

LAMsight is a practical experiment in creating new models for collaboration between researchers, clinicians, and patients. We are working with a rare-disease advocacy organization to identify and implement collaboration modes that help accelerate research on the rare disease LAM (Lymphangioleiomyomatosis), a multi-system, fatal disease that typically strikes women in their child-bearing years.

Five billion of the world's six some billion people live in developing countries, where many have no access to basic medical treatments and preventive care. Moca, or "Mobile Care," is cell-phone-based telemedicine system specifically for use in developing countries. The system allows semi-skilled community health workers to go into the field carrying a smartphone, collect diagnostic information, transmit it to a central medical records system for expert review, and receive real-time decision support. The project is build on open platforms: the Android smartphone platform and the OpenMRS medical record system. OpenMRS is designed for use in developing countries and is deployed in a dozen countries. Members of the Moca team traveled to the Philippines in March to explore a pilot deployment in Capiz; we are also developing partnerships with other organizations around the world.