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Datapalooza Day 1 Recap

Posted by on June 5th, 2012 Posted in: News from NLM, Technology


Health Data Initiative Forum III: The Health Datapalooza got underway today with a morning plenary session delivered to a sold out crowd in Washington DC, and was broadcast to others via a live webcast. Today’s keynote address was delivered by Todd Park, U.S. Chief Technology Officer, who kicked off the event by speaking enthusiastically on the great potential created by the government opening more data sets to the public.  From this increase in access to data he believes we  will see awesome innovations and partnerships between public and private enterprises formed that can lead to tools and services created with the potential to improve health outcomes.

A panel of patients, providers and community judges selected the best applications and technologies to be featured at Datapalooza from a pool of submissions based on criteria including the extent to which the tool harnesses health data (whether government or otherwise), is directed at a specific health-related problem and the likelihood that it would actually be used. Those applications that are selected are showcased at the Datapalooza. Here is a highlight tour of some of the apps on display this morning (in order of appearance), with brief description and a link out when I was able to locate one.

Healthy Communities Network (Healthy Communities Institute): This system provides access to health information at a community level.  They demonstrated the type of data, or “actionable content” as they put it, included in the network by looking at the Miami Matters site.  There is a lot going on here, and the content is of value to a wide audience, including community health workers and individuals.  The Community Dashboard is an especially appealing feature, with a range of variables (demographic, socio-economic, health) with community level values paired with national comparators.  Appearing on each variable page is the URL of the source and data, time period for the figures, plus technical notes.

Community Indicators Data Portal (HealthLandscape): This is a mapping tool that allows users to zoom in at a microlevel (from county to individual practitioners) to overlay and examine health outcomes, demographics, health care facilites and local health care policies.

Health Insights in Real-Time (University of Rochester): This is a tool being developed at the University of Rochester Computer Science department.  It utilizes natural language processing to parse tweets and determine a “health” level of an individual.  Given the time stamps and often GPS data attached to posts, this allows the program to create a real-time heat map of sickness and health.

County Health Rankings & Roadmaps ( University of Wisconsin Population Health Institute):  This is a really cool mapping tool that brings together mortality, morbidity, health behaviors, socio-economic factors, and physical environment variables to rank the health of individual counties.  It is surprisingly easy to use considering the wealth of data it pulls together.  Check out the factors that lead King County to be ranked sixth in terms of health outcomes in Washington state.

Castlight Health: Castlight is a health care cost comparison service that requires an account to access and try out. The premise of the product is to empower the individual to be aware of the potential (range) of health care costs associated with a specific service, before that service is rendered.  It allows the user to shop around in that way, making a decision both on anticipated cost, quality and connivence of service.

iBlueButton (Humetrix): This is an iOS platform app that allows Veterans to request and download their patient records to their device instantly.  From here they can “push” their record to a provider’s device via bluetooth, so that during a clinic visit the provider can have instant access to records from a different facility.  The provider can also then send back to the patient a visit summary and other health information that the patient would then have stored on their iOS device.

Flornce (mHealthCoach):  This is a tool that attempts to reduce patient readmission rates by facilitating communication, providing support to clinicians during discharge procedures, and also “guiding” the patient by engaging them in their care plan.  There was a lot going on with this application demonstration and I couldn’t catch all of it – such as where the data used in the application originates.

MyDrugCosts: This is a mobile optimized web-based tool that allows individuals who sign up for a premium account to look up the cost a prescription – given the information they have provided about their health care coverage – in real-time so that they can discuss less expensive alternatives with their provider.

ScanAvert: This is a barcode scanning app available for both the iOS and Android platforms.  With this app users can create a personal profile about their dietary restrictions, personal situation (pregnant/nursing), current medications and then when scanning product bar codes receive compatibility information about that product, with detailed information supporting the reasons why the app found it compatible or not for the individual.

Symcat: Symcat is a symptom checking tool that was built by two medical students / software engineers.  Their aim is to provide users with an alternative to Dr. Google.  The app pulls data from the CDC and uses an algorithm to develop follow-up questions and analyze symptoms entered to determine the most likely ailment behind the symptoms.  The probability of each cause is displayed in percent form and updates in real-time with each additional bit of information received.  At the end of questioning, Symcat displays recommendations ranging from “go to the ER” or “schedule an appointment with a primary care provider”.   Additionally, users can learn more about the potential causes of their symptoms, with data that is pulled in directly from MedlinePlus.

More tomorrow, from Datapalooza Day 2!

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Developed resources reported in this program are supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012343 with the University of Washington.

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