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Activity Number: 165 - SLDS CSpeed 2
Type: Contributed
Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #319148
Title: Adapting the Difference-in-Difference Technique to Study Change in Opioid Overdoses During the COVID-19 Pandemic
Author(s): Alexander Preiss* and Dalia Khoury
Companies: RTI International and RTI International
Keywords: COVID-19; Difference in difference; Study design; Bootstrapping; Time series
Abstract:

Researchers are studying the degree to which many outcomes of interest have changed during the COVID-19 pandemic. Our team was interested in whether Emergency Medical Services in Guilford County, NC administered more doses of naloxone (a life-saving opioid overdose reversal drug) during the first 29 weeks of the pandemic than in the past. Such a change can be quantified simply as a growth rate relative to a comparison period. However, a growth rate cannot convey whether the observed change is historically anomalous. A large change may not be noteworthy if changes of similar magnitude occurred often in the past. Therefore, we adapted the difference-in-difference (DID) technique to generate a quasi-control group of past changes. Using a rolling time window, we calculated the growth rate for every 29-week period in the available historical data (2014-20). This produced a quasi-control group of 270 past changes. We found that the growth rate of naloxone administrations during the pandemic was > 91 percent of past periods. This adaptation of DID can be applied to any outcome for which researchers want to understand the degree of change during a specific period relative to the past.


Authors who are presenting talks have a * after their name.

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