- Associate Professor
Institution of Highest Degree:
NYU School of Medicine
University of Pittsburgh
Dr. Wagner’s research focuses on real-time methods for detecting and characterizing disease outbreaks, including the development and testing of operational biosurveillance systems. In his role as director of the RODS Laboratory, Dr. Wagner led the development and implementation of two widely used biosurveillance systems: the RODS system and the National Retail Data Monitor (NRDM).
Biosurveillance is a systematic process that detects and characterizes disease outbreaks. The process involves data collection, analysis, and decision making. The purpose of biosurveillance is to determine whether an outbreak exists, and if so, to identify the biological agent, source, route of transmission, geographic extent, and other characteristics that influence decisions about antibiotics, vaccines, quarantine, and other responses.
At present, Dr. Wagner is developing a third system called BioEcon. BioEcon is a decision analytic tool for use by analysts working in health departments. BioEcon is a logical extension of Dr. Wagner’s research in biosurveillance. BioEcon addresses the problem of what is the optimal action to take in response to incoming biosurveillance data.
The success of Dr. Wagner’s research into methods to collect and analyze biosurveillance data have now produced a situation in which health departments have an abundance of biosurveillance data and face decisions about how to react to anomalies in those data.
Ye Y, Wagner MM, Cooper GF, Ferraro JP, Su H, Gesteland PH, Haug PJ, Millett NE, Aronis JM, Nowalk AJ, Ruiz VM, López Pineda A, Shi L, Van Bree R, Ginter T, Tsui F. A study of the transferability of influenza case detection systems between two large healthcare systems. PLoS One (2017) Apr 5;12(4):e0174970. doi: 10.1371/journal.pone.0174970. eCollection 2017. PMID: 28380048 PMCID: PMC5381795
Cooper, G. F., Villamarin, R., Tsui, F.-C. (Rich), Millett, N., Espino, J. U., & Wagner, M. M. (2015). A Method for Detecting and Characterizing Outbreaks of Infectious Disease from Clinical Reports. Journal of Biomedical Informatics, 53, 15–26. http://doi.org/10.1016/j.jbi.2014.08.011 PMID: 25181466 PMCID: PMC4441330
Cooper GF, Villamarin R, Tsui FC, Millett N, Espino J, Wagner MM. A method for detecting and characterizing outbreaks of infectious disease from clinical reports. Journal of Biomedical Informatics (2014). Aug 30. pii: S1532-0464(14)00192-0. doi: 10.1016/j.jbi.2014.08.011. [Epub ahead of print] PMID:25181466 PMC4441330
Ye Y, Tsui FR, Wagner M, Espino JU, Li Q. Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers. J Am Med Inform Assoc. 2014 Sept:21(5):815-823. (2014 Jan 9. doi: 10.1136/amiajnl-2013-001934. Epub ahead of print. PubMed PMID: 24406261. PMCID:PMC in Process: Available on 09/01/2015.
Villamarín R, Cooper G, Wagner M, Tsui FC, Espino JU. A method for estimating from thermometer sales the incidence of diseases that are symptomatically similar to influenza. Journal of Biomedical Informatics. 2013 Jun;46(3):444-57. PMID: 23501015 PMCID: PMC4609543
Wagner MM, Levander JD, Brown S, Hogan WR, Millett N, Hanna J. Apollo: Giving application developers a single point of access to public health models using structured vocabularies and Web services. AMIA Annu Symp Proc. 2013:1415-24. PubMed PMID: 24551417. PMCID:PMC3900155.
Construction of Decision-Theoretic Reminder Systems
Computer-Assisted Medical Decision Making
Data Accuracy in Computer-Based Medical Records