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Rural-Urban Trends in Opioid Overdose Discharges in Missouri Emergency Departments, 2012–2016
  • Published Date:
    April 25 2019
  • Source:
    J Rural Health.
  • Language:
    English


Public Access Version Available on: October 25, 2020, 12:00 AM information icon
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Details:
  • Alternative Title:
    J Rural Health
  • Description:
    Purpose:

    Opioid overdose death rates rose 36% from 2015 to 2016 in Missouri, indicating a worsening of the opioid overdose epidemic. To better understand urban and rural differences in nonfatal opioid overdoses treated in Missouri emergency departments, this paper analyzed hospital billing data from emergency departments due to opioid overdose from 2012 to 2016.

    Methods:

    Emergency department records meeting the opioid overdose case definition were aggregated into 6 progressively rural groups using the National Center for Health Statistics (NCHS) urban-rural county classification from 2013. These data were analyzed to determine significant trends amongst and between the geographic groups.

    Findings:

    Generally, the magnitude of opioid overdose morbidity decreased as levels of rurality increased, using annual percentage change as the metric of change. Over the study period, Missouri’s most urban counties had significantly higher rates of opioid overdose and saw larger percentage increases in rates compared to more rural areas. Statewide, all rural-urban classifications experienced increases in heroin overdose morbidity; however, there was extreme variation in the trajectory of those increases. Heroin overdose rates were much higher in urban areas than rural areas. Conversely, rural and urban areas saw relatively similar patterns for non-heroin opioid overdoses, though overall magnitude of these increases was more modest across all geographic groups.

    Conclusions:

    The results from this analysis can help inform prioritization of strategies and resources to implement activities addressing the opioid overdose epidemic. Using a rich hospital discharge database could allow for further analysis of subpopulations to enhance personalization and customization of care.

  • Pubmed ID:
    31022309
  • Pubmed Central ID:
    PMC6920583
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