TY - JOUR
T1 - Co-prescription network reveals social dynamics of opioid doctor shopping
AU - Perry, Brea L.
AU - Yang, Kai Cheng
AU - Kaminski, Patrick
AU - Odabas, Meltem
AU - Park, Jaehyuk
AU - Martel, Michelle
AU - Oser, Carrie B.
AU - Freeman, Patricia R.
AU - Ahn, Yong Yeol
AU - Talbert, Jeffery
N1 - Publisher Copyright:
© 2019 Perry et al.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - This paper examines network prominence in a co-prescription network as an indicator of opioid doctor shopping (i.e., fraudulent solicitation of opioids from multiple prescribers). Using longitudinal data from a large commercially insured population, we construct a network where a tie between patients is weighted by the number of shared opioid prescribers. Given prior research suggesting that doctor shopping may be a social process, we hypothesize that active doctor shoppers will occupy central structural positions in this network. We show that network prominence, operationalized using PageRank, is associated with more opioid prescriptions, higher predicted risk for dangerous morphine dosage, opioid overdose, and opioid use disorder, controlling for number of prescribers and other variables. Moreover, as a patient's prominence increases over time, so does their risk for these outcomes, compared to their own average level of risk. Results highlight the importance of co-prescription networks in characterizing high-risk social dynamics.
AB - This paper examines network prominence in a co-prescription network as an indicator of opioid doctor shopping (i.e., fraudulent solicitation of opioids from multiple prescribers). Using longitudinal data from a large commercially insured population, we construct a network where a tie between patients is weighted by the number of shared opioid prescribers. Given prior research suggesting that doctor shopping may be a social process, we hypothesize that active doctor shoppers will occupy central structural positions in this network. We show that network prominence, operationalized using PageRank, is associated with more opioid prescriptions, higher predicted risk for dangerous morphine dosage, opioid overdose, and opioid use disorder, controlling for number of prescribers and other variables. Moreover, as a patient's prominence increases over time, so does their risk for these outcomes, compared to their own average level of risk. Results highlight the importance of co-prescription networks in characterizing high-risk social dynamics.
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U2 - 10.1371/journal.pone.0223849
DO - 10.1371/journal.pone.0223849
M3 - Article
C2 - 31652266
AN - SCOPUS:85074178277
SN - 1932-6203
VL - 14
JO - PLoS ONE
JF - PLoS ONE
IS - 10
M1 - e0223849
ER -