Details

Autor(en) / Beteiligte

• Hinami, Keiki
• Ray, Michael J.
• Doshi, Kruti
• Torres, Maria
• Aks, Steven
• Shannon, John J.
• Trick, William E.

Titel

Prescribing Associated with High-Risk Opioid Exposures Among Non-cancer Chronic Users of Opioid Analgesics: a Social Network Analysis

Ist Teil von

• Journal of general internal medicine : JGIM, 2019-11, Vol.34 (11), p.2443-2450

Ort / Verlag

New York: Springer US

Erscheinungsjahr

2019

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Background The continued rise in fatalities from opioid analgesics despite a steady decline in the number of individual prescriptions directing ≥ 90 morphine milligram equivalents (MME)/day may be explained by patient exposures to redundant prescriptions from multiple prescribers. Objectives We evaluated prescribers’ specialty and social network characteristics associated with high-risk opioid exposures resulting from single-prescriber high-daily dose prescriptions or multi-prescriber discoordination. Design Retrospective cohort study. Participants A cohort of prescribers with opioid analgesic prescription claims for non-cancer chronic opioid users in an Illinois Medicaid managed care program in 2015–2016. Main Measures Per prescriber rates of single-prescriber high-daily-dose prescriptions or multi-prescriber discoordination. Key Results For 2280 beneficiaries, 36,798 opioid prescription claims were submitted by 3532 prescribers. Compared to 3% of prescriptions (involving 6% of prescribers and 7% of beneficiaries) that directed ≥ 90 MME/day, discoordination accounted for a greater share of high-risk exposures—13% of prescriptions (involving 23% of prescribers and 24% of beneficiaries). The following specialties were at highest risk of discoordinated prescribing compared to internal medicine: dental (incident rate ratio (95% confidence interval) 5.9 (4.6, 7.5)), emergency medicine (4.7 (3.8, 5.8)), and surgical subspecialties (4.2 (3.0, 5.8)). Social network analysis identified 2 small interconnected prescriber communities of high-volume pain management specialists, and 3 sparsely connected groups of predominantly low-volume primary care or emergency medicine clinicians. Using multivariate models, we found that the sparsely connected sociometric positions were a risk factor for high-risk exposures. Conclusion Low-volume prescribers in the social network’s periphery were at greater risk of intended or discoordinated prescribing than interconnected high-volume prescribers. Interventions addressing discoordination among low-volume opioid prescribers in non-integrated practices should be a priority. Demands for enhanced functionality and integration of Prescription Drug Monitoring Programs or referrals to specialized multidisciplinary pain management centers are potential policy implications.