U.S. Department of Veterans Affairs Selects Bitscopic’s Praedico for Public Health Surveillance.
March 20, 2015 – Palo Alto CA.– 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.
Some use cases of Praedico include:
1. Syndromic Surveillance. Praedico continuously surveys data and automatically alerts epidemiologists to potential outbreaks of infectious diseases and dangerous micro-organisms such as Francisella Tularensis, Elizabethkingia, Burkholderia Cepacia. Praedico has also been used for the monitoring of West Nile Virus infections, Seasonal Influenza virus, and Listeria and Salmonella infections. Praedico also generates automated system alerts for clusters of infections suggestive of bioterrorism.
2. FDA Safety Alerts. Praedico can be used to identify patients exposed to contaminated medical equipment. For example, it was used for the identification of patients exposed to a contaminated coronary heater-cooler medical device used to warm and cool a patient’s blood during cardiopulmonary bypass. In order to identify the impacted VA population, an epidemiologist used Praedico to pull procedure data for a specific time range (12 months), identifying all patients with a specified procedure code. Using Praedico the epidemiologist then cross-referenced with occurrences of Mycobacteria and, within seconds, isolated the impacted population.
3. Monitoring of Medical Equipment. Praedico has been used for the early detection and alerting of potentially contaminated equipment, including endoscopes, colonoscopes, ENT-scopes and contaminated dental equipment.
Advanced Analytics Capability
What makes the Praedico platform unique among public health analytics tools is that it combines statistical analysis and machine learning methods to detect abnormal patterns in inpatient and outpatient data collected from medical facilities.
Praedico provides a wide range of built-in and programmable system alerts that identify potential anomalies that could merit further investigation. In addition, it combines signals and patterns from multiple data sources to evaluate the general status of healthcare facilities. By using a weighted scoring system for assigning severity scores to facilities, it guides users into prioritizing evaluation and intervention in facilities with higher risk. The scoring assigns different weights to alerts, depending on their type, count, and severity. The scores are updated on a daily basis to reflect the latest status of a facility.
System alerting and facility scoring utilizes the following types of data in its analysis:
1. Microbiology Laboratory. Organisms found in positive lab microbiology tests are evaluated for both statistical anomalies and for matching to a short list of highly infectious and dangerous organisms (such as Anthrax, for example).
2. Inpatient and Outpatient Visits. Patient visits to healthcare facilities are evaluated for anomalies in factors such as disease clusters, location of patients with symptoms, age group distribution, and the number and location of emergency department visits.
3. Unusual Pharmacy Prescription Patterns. Prescriptions for both outpatient and inpatient visits are analyzed for anomalies. Both monthly and weekly aggregate values of drugs are compared to historical values. If any unusual pattern is observed, an alert is generated.
Payam Etminani, CEO of Bitscopic, said: “We are very excited to be partnering with the VA, the largest integrated hospital system in the United States. The potential in terms of lives and dollars saved by leveraging the latest machine learning and big data technologies for healthcare is enormous.” Etminani added that “We look forward to an exciting partnership initially for public health surveillance and also in many other areas such as infection prevention, clinical surveillance, and genomics.”
Bitscopic’s Praedico platform is built on open standard software components and can be run on clusters of commodity hardware using virtual machines for fast distributed processing, load balancing, high availability and failover support. Bitscopic has a proven team composed of talented scientists and engineers with the necessary expertise to install, configure, support and customize a solution.
More details on the Praedico platform can be found in an extensive White Paper that can be downloaded here.
Bitscopic is a Silicon Valley-based company formed in 2012 to significantly improve healthcare outcomes by combining advances in Big Data technologies by augmenting the capabilities of the VA’s Electronic Health System (VistA). Bitscopic’s Praedico platform integrates electronic health data from the VA’s 170+ hospitals with 9 unique million patient records in near-real time, and translates this data into actionable insights and alerts. The company’s solutions have enabled hospitals to anticipate and prevent infectious disease outbreaks and to reduce the time needed to produce reports from days to minutes, saving many lives and dollars.
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