This year’s Health 2.0 codeathon was markedly different from last year’s because the global competition judging was up first ’ the first ever Developers World Cup. Teams from as far away as Fukushima and Stockholm had flown in for this final judging. My fellow judges include Sastry Nanduri, Gretchen Wustrack, Forrest King from Novartis, Michelle Snyder, and Unity Stoakes. Many people have been here since Sunday morning.
Indu Subaiya (CEO of Health 2.0) remarked on how far things have come since the very first codeathon on the Google campus. The room was full of milling stress. People sat, then stood, then twitched as they waited for their mere 5 minutes to explain all the work, and heart and sleepless creativity they’d shoved into a brand new piece of life-changing technology.
The ideas were all innovative, and the judges were impressed with the quality of the developed tools. Third place went to the Stockholm team with the smart-phone spirometry device. Second place went to New Delhi and first place went to the New York for a system to track warning signs of suicide through Twitter posts. A special honorable mention went to the Fukushima team.
Global Solutions Competition
Boston: Joel and Guy Schechter. Their work is around ’health tokens’. There are so many people offering products and sources of information in this area of changing behavior that people often don’t know where to go. They chose to focus on ’Pre-contemplation’ stage of behavior change. Their purpose to ’to provide meaningful bursts of information to patients at a time when they are most receptive using social media. They are creating a ’healthy tokens engine’ and aggregating information from social media and looking at information that people are posting about their behavior. Their first campaign is around emergency room visits. People tweet about a visit and then they send the patient info about ways to be better informed. Preventing unnecessary ER visits could save billions of dollar a year.
Fukushima: The team from Fukushima began by displaying the numbers of victims from both the San Francisco earthquake, and the Fukushima nuclear meltdown after the tsunami. The first 72 hours are crucial. Their challenge was to address this issue by developing iTriage. If someone is a medical provider, they can register and share their expertise. The reports that it generates (SOS reports), allow maps, reporting of situations, and who the reporter is. Currently the information is peer-to-peer, but could be moved to cloud. Asked if the application was for just the local area, or for the world to see ’ the developers said it was meant to be internationally available. In terms of how the aggregation of data actually helps deliver care directly to the most needed site, the developer said that its usefulness begins even in the first moments, when reports about how bad a situation might be were inconsistent.
New Delhi: Their product is called ’stasis’ and ’fall-proof.’ It takes an alert system and transforms it to a monitoring jacket. They took off-the-shelf market electronics and adapted them ’ they can be stitched into a person’s own clothes. The goal is that patients may be able to live independently longer. The information is pushed to the electronic medical record by pushing first to a data cloud. It is a wearable health platform and includes location tracking, health monitoring, critical alerts, e-pill box, health record and improved doctor-patient links. Alerts can be sent to caregivers, hospitals and providers, as well as local emergency services.
NYC: The team from New York presented MedTuner. The project asks people to follow MedTuner on Twitter. Suicide now kills more Americans than traffic accidents, and many of those suicidal messages are posted on Twitter. Their four design principles included 1) making at easy as possible for the person, 2) make a difference with the information that is available, 3) to be able to store and follow information that exists but can’t be watched at all times, and 4) to ’not be Kim Kardashian!’ The goal is to get ahead of that moment when someone has to recognize what’s going on and make an appointment with their doctor. The idea is that we have to go to meet patients where they are, rather than waiting for them to come to us. The examples they gave for its uses include Suicide, travel, post-partum depression and rare disease clinical trials and adverse drug reporting.
Shanghai: This project is about prevention and early detection. Early detection, in particular, is a problem, with large differences in services available to groups of people, based mostly on the ’size of their wallet.’ Any person can go onto this project, my health planner, enter as a certain person with an age, and get a summary of an international group’s health screening recommendations. You get an overall listing of every country’s recommendation, and their level of strength. It also presents a plan for each patient, as well as the costs. The system is designed to be a module for a health portal. The developers also pointed out the cultural differences in countries’ approaches to early detection and screening ’ that patients are often not screened at all.
Stockholm: The Stockholm team is a company called Line, whose mission is to ’get healthcare connected.’ They have already built a tool called Piddle, which tracks urinalysis results ’ it is a diagnostic medical device. They are doing a pilot project in Uganda. Asthma and COPD was their target illness for this competition. They developed a smart-phone based spirometer called ’Blow.’ Public data on air pollution can be presented to the user because they know the user’s GPS location. Data is entered into the app in order to calculate their spirometry values. Simple information is collected at the time of the spirometry (such as whether or not an inhaler was used prior to using the spirometer). Could also be used to detect worsening COPD, and with rehab. The tube for using it is cardboard, and disposable and people can loan it (after changing tubes) to a family member. They envision an ecosystem built around respiratory health and data.
Washington, DC: This project was to ’fix’ the FDA’s adverse reaction database. They have a giant list of products, patients and reactions. The data is ’dirty’ and they began with the FDAs data and connected it to the publicly available crowd-sourcing of information (such as all the variations on company names). They developed an algorithm for all possible sources in Wikipedia to verify. 22,000 drugs were reduced to 3500. It is semantic database technology. People were then used to classify reactions. For each drug, they created an email address so that reactions could be sent to that drug! The database is now organized so that a person can drill down and see what the fine detail is. They did not give background rates of adverse reactions, or normalize them against a standard. But they did include combinations of drugs, as well as specificity about gender and size and age. Also they include which reports patients who died, and serious events. The system can look at 161 million combinations of 3 drug reactions, with a 1-3 second response time. There is also a format for entering data for patients.