Sustainability planning in the US response to the opioid crisis: An examination using expert and text mining approaches

Carlos Gallo*, Karen Abram, Nanette Hannah, Lauren Caton, Barbara Cimaglio, Mark McGovern, C. Hendricks Brown

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Between January 2016 and June 2020, the Substance Abuse and Mental Health Services Administration rapidly distributed $7.5 billion in response to the U.S. opioid crisis. These funds are designed to increase access to medications for addiction treatment, reduce unmet treatment need, reduce overdose death rates, and provide and sustain effective prevention, treatment and recovery activities. It is unclear whether or not the services developed using these funds will be sustained beyond the start-up period. Based on 34 (64%) State Opioid Response (SOR) applications, we assessed the states’ sustainability plans focusing on potential funding sources, policies, and quality monitoring. We found variable commitment to sustainability across response plans with less than half the states adequately describing sustainability plans. States with higher proportions of opioid prescribing, opioid misuse, and poverty had somewhat higher scores on sustainment. A text mining/ machine learning approach automatically rated sustainability in SOR applications with an 82% accuracy compared to human ratings. Because life saving evidence-based programs and services may be lost, intentional commitment to sustainment beyond the bolus of startup funding is essential.

Original languageEnglish (US)
Article numbere0245920
JournalPloS one
Volume16
Issue number1 January
DOIs
StatePublished - Jan 2021

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

Fingerprint Dive into the research topics of 'Sustainability planning in the US response to the opioid crisis: An examination using expert and text mining approaches'. Together they form a unique fingerprint.

Cite this