  Opioid related deaths are increasing dramatically in recent years, and opioid
epidemic is worsening in the United States. Combating opioid epidemic becomes a
high priority for both the U.S. government and local governments such as New
York State. Analyzing patient level opioid related hospital visits provides a
data driven approach to discover both spatial and temporal patterns and
identity potential causes of opioid related deaths, which provides essential
knowledge for governments on decision making. In this paper, we analyzed opioid
poisoning related hospital visits using New York State SPARCS data, which
provides diagnoses of patients in hospital visits. We identified all patients
with primary diagnosis as opioid poisoning from 2010-2014 for our main studies,
and from 2003-2014 for temporal trend studies. We performed demographical based
studies, and summarized the historical trends of opioid poisoning. We used
frequent item mining to find co-occurrences of diagnoses for possible causes of
poisoning or effects from poisoning. We provided zip code level spatial
analysis to detect local spatial clusters, and studied potential correlations
between opioid poisoning and demographic and social-economic factors.
