@article{Law_Burkom_Bronstein_Schier_2015, title={Assessment of National Poison Data System Algorithms to identify Public Health Events}, volume={7}, url={https://ojphi.org/ojs/index.php/ojphi/article/view/5700}, DOI={10.5210/ojphi.v7i1.5700}, abstractNote={<p class="p1">This presentation compares surveillance algorithms used in the National Poison Data System to identify incidents of public health significance with recently expanded filtering capabilities and with methods beyond the NPDS generalized historical limits model. Collected data series from 55 poison centers over 7 years include hourly counts of general call volumes and of substance-specific (e.g. CO exposure) calls. By applying current, modified, and novel methods to known and simulated clusters among these data, the authors will present the most efficient algorithms for identifying incidents of public health significance.</p>}, number={1}, journal={Online Journal of Public Health Informatics}, author={Law, Royal K. and Burkom, Howard and Bronstein, Alvin and Schier, Josh}, year={2015}, month={Feb.} }