Excellent healthcare treats each person as a unique individual; but the best way to learn the most effective treatment for each unique situation is through analysis of massive amounts of data – data about many individuals’ treatment – which improves our healthcare system on the whole.
Among this year’s collection of innovative Hive companies are three using data to craft a better future for individuals everywhere. Their tools support frustrated parents seeking treatment for developmentally disabled children, provide potentially life-saving insights to doctors on the front lines of critical care, and deliver valuable performance metrics to sharpen the efficacy of public health programs a world away.
The problem: Time is of the essence for a parent who suspects a child may have autism, a developmental delay, or some other type of neurological challenge – yet most face enormous obstacles getting the “system” to respond to their concerns. While the effectiveness of early intervention has been widely demonstrated, valuable time is often lost waiting for a diagnosis and interventions.
The solution: Cognoa has created a mobile app that uses machine learning to help parents evaluate whether their child’s social, language and communication development is on track – and to get the right help as soon as possible when it isn’t. Using the Cognoa platform, a parent answers questions and uploads videos of the child’s behavior. The app identifies if the child is at risk for development delay and/or autism and delivers a personalized report that parents can share with their doctor, identifying areas where the child is doing well and others where intervention is needed.
The breakthrough: “Cognoa originated from deep investigations into how the current healthcare system detects, diagnoses, and treats developmental delay in children,” explains Dennis Wall, scientific founder and developer of Cognoa’s proprietary child behavior assessments and data science. Citing 18-month long waiting lists, the fact that some children don’t receive a diagnosis of autism until they are almost five, and that many families must “endure self-managed navigation through an overly complex healthcare ecosystem,” Dennis says it isn’t acceptable to let children go “without therapeutic intervention during the time windows [when] they need it most.”
Cognoa was built to use the “lens of machine learning to create algorithms that can cut through the complexity and mobilize the exchange of information between parents and clinicians,” Dennis says, noting that the concept coalesced when it became clear that “these algorithms place the power of knowledge into the hands of the caregivers and enable action that helps them help their child in minutes instead of months.”
The problem: Medical Informatics Corp (MIC) saw a need to “radically rethink” the way that patients are monitored within critical care environments. The current system places each ICU patient on a physiologic monitor, which – says Craig Rusin, co-founder and CTO at Medical Informatics – “is a dedicated piece of hardware that measures vital signs such as ECG, blood pressure, heart rate, etc.” This model of patient innovation typically requires the development and sales of new hardware. “That’s like buying a separate computer for every program that you want to run,” Craig says, adding that “it’s expensive, un-scalable, and it’s driving up health care costs.”
The solution: Seeing “a huge untapped potential in the data that is being collected by existing medical equipment,” MIC transforms existing clinical data streams into patient-specific analytics in real time. “Each monitoring application addresses a specific clinical question and can be enabled on a patient-by-patient basis,” Craig explains. The software-based applications can be developed five times faster and for just 10% of the cost of hardware-based solutions, creating what he calls a “fundamental shift in the economics of patient monitoring applications.”
The breakthrough: Algorithms that may not be economically feasible as a single hardware-based monitor become economically viable as a software-based virtual monitor. Considered a thought leader and architect of change in predictive and prescriptive clinical analytics, Craig and his colleagues are laying a foundation for real-time clinical decision support applications within Hospital IT infrastructure.
“At MIC, our people are quirky, passionate, and over-qualified,” Craig shares. “These traits enable us to navigate the often-tricky world of healthcare technology innovation. Everyone on our team shares the same goal: building software to empower health care teams to save lives.”
The problem: According to BroadReach founding partner John Sargent, there has long been a “profound divide between the application of big data in developed markets—where some believe governments and companies know too much—and in developing countries where all agree they know too little to provide life-enhancing services.” Fragmented and incomplete, the available data often overlooked the impacts of key metrics, including the social determinants of health.
The solution: BroadReach provides a powerful analytic platform with predictive modeling and data visualization tools that can be used to craft healthcare policy and programs based on performance, sustainability and accountability. Combining real-time data collection; powerful and accessible tools for data integration, analysis and visualization; and strategic consulting and operational support, BroadReach analytics drive programming that improves outcomes quickly and effectively.
The breakthrough: The “pragmatic visionaries” at BroadReach Analytics now work closely with governments, multinational health organizations, major donors and life science companies worldwide to integrate social, economic and health data for insights to maximize impact by improving access to quality healthcare in a sustainable way.