Payam Etminani

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Accelerating Identification and Tracking of Pandemic Disease Outbreaks

A national biosurveillance program requires the collaboration of multiple federal, state and local agencies to provide a comprehensive view of a health-related event. Bitscopic's Praedico™ biosurveillance platform breaks down the data barriers among organizations with an extensible architecture that can incorporate any kind of data. The platform also delivers high performance by incorporating the latest technologies such as big data, NoSQL databases, and machine learning. Read More »

Bitscopic

Bitscopic is a healthcare analytics and workflow platform empowering organizations to gain unique insights from ever increasing data, and achieve better healthcare outcomes through data driven decisions to optimize care. The company was founded in 2012 by two tech industry veterans who were inspired by the opportunity to use advanced software technology to initially mitigate the spread of infectious diseases. The company is headquartered in Silicon Valley and has development offices in Seattle, WA.

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Joel Mewton

Joel Mewton is the Chief Technology Officer (CTO) of Bitscopic, a healthcare-focused data, analytics and product company. Joel manages Bitscopic’s infrastructure, charts the company’s technological roadmap, and generally just takes care of what needs to be done.
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Payam Etminani

Payam Etminani is the CEO and Co-Founder of Bitscopic. Etminani co-founded Bitscopic after a colleague, friend and mentor at the U.S. Department of Veterans Affairs (VA), John Lopez, contracted a hospital acquired infection at a VA hospital. Read More »

Transforming Health Care Through A 360-Degree View Of Data

How medical care can be substantially improved through a full spectrum view of all factors that affect health was the topic of Payam Etminani's presentation at the 2019 IDGA Veterans Benefits Conference in Washington D.C. Etminani, the CEO of Bitscopic, argued that the ability to view all health data including social, environmental and genomic information in addition to the traditional clinical measures (vital signs, blood work, history of illness etc), would lead to significant improvement in care. Etminani described how recent advances in Big Data and Artificial Intelligence (AI) make combining and using these large and widely varied sets of information possible. Read More »

Using the Latest Advances in Data Science to Fight Infectious Diseases

One of the most dramatic shifts in recent years that is empowering epidemiologists to be more effective at their jobs is occurring due to improvements in data technologies. In the past, the old "relational" data model dictated that data had to be highly structured, and as a result treated in distinct silos. This made it difficult, if not impossible, to analyze data from multiple sources to find correlations. Epidemiologists would spend many minutes or even hours on each query they ran to get results back, which is unacceptable when you need to test dozens of hypotheses to try to understand and contain a fast-moving outbreak. (Imagine how you would feel if each one of your Google searches took 45 minutes to return!) By contrast, using newer technologies, the same queries on the same hardware can run in seconds. Read More »

VA Selects Bitscopic's Praedico for Public Health Surveillance

Press Release | Bitscopic | March 20, 2015

Bitscopic Inc., a leading provider of health analytics tools, announced today that the U.S. Department of Veterans Affairs (VA) has selected its Praedico platform to detect and monitor infectious disease outbreaks across the country. In addition, the VA is going to pilot Bitscopic's advanced analytics software for the early detection and management of hospital acquired infections (HAI) and other clinical informatics applications. Bitscopic's Praedico scans data from electronic health records (EHRs), laboratories, pharmacies, and other sources in seconds. It has been used to analyze infectious disease data including influenza, dengue, Hepatitis C (HCV), etc. Praedico is a modular, highly configurable, and customizable platform. It can detect and monitor large-scale events such as antibiotic resistance trends and potential major disease outbreaks. In addition, it monitors more localized events and tools, such as patient monitoring devices, and surgical site infections. Read More »