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Research >> NSF Research Center

VERC Research

Our Approach

Our team is nationally known for their methods research in several fundamental areas directly relevant to healthcare engineering improvement and important VA issues, including:

  1. Statistical methods for quality, patient safety, and risk-benefit analysis;

  2. Data envelopment analysis models to identify best healthcare practices;

  3. Network-wide models for optimizing care processes for traumatic brain injury (TBI);

  4. Effectiveness and improvement readiness assessment methods; and

  5. Informatics, natural language processing, and data mining/extraction.

The statistical measurement work at NU has been supported by 3 National Science Foundation (NSF) grants and produced seminal papers in several statistical methods to accelerate process improvement – including quality control methods for rare events, sequential probability ratio tests for risk-adjusted outcomes, statistical methods for monitoring evidence base compliance, and novel risk-benefit methods that address fundamental problems with Quality Adjusted Life Year (QALY) type measures.  Our WPI and MIT partners are well-known for their lean organizational readiness and implementation evaluation methods, and our MAVERIC informatics colleagues work in natural language processing AI methods for extracting information from free-form text, particularly useful for identifying cases within medical records.  MIT and NU are exploring partnering on research thrust 3, with the latter actively working with the National Academy of Engineering (NAE), Institute of Medicine (IOM), and Department of Defence (DoD) on the TBI systems engineering research agenda.  Towards the secondary objective identified in the VERC Request for Proposals to advance methodological research in a few key areas central to both the core team’s expertise and VA interests

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