Predictors of US states’ adoption of naloxone access laws, 2001–2017

Bohler, Robert; Hodgkin, Dominic; Kreiner, Peter; Green, Traci C.

doi:10.1016/j.drugalcdep.2021.108772

Cited by 7 publications

(3 citation statements)

References 57 publications

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“…Key informants discussed themes around the intersection of rurality and stigma. KIs described rural areas of their state that were conservative and as a result less accepting of opioid use and treatment ( Bohler et al, 2023 , Des Jarlais et al, 2015 , Green et al, 2020 , Bohler et al, 2021 ). They also described the lack of privacy available in pharmacies in areas where resources come from a common source (such as groceries and medications in one store) and describe this as a concern across other health conditions.…”

Section: Discussionmentioning

confidence: 99%

Policies, adaptations, and ongoing challenges to naloxone, buprenorphine and nonprescription syringe access across four-states: Findings from an environmental scan and key informant interviews

Floyd,

Silcox,

Strickler

et al. 2024

Drug and Alcohol Dependence Reports

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Section: Discussionmentioning

confidence: 99%

Policies, adaptations, and ongoing challenges to naloxone, buprenorphine and nonprescription syringe access across four-states: Findings from an environmental scan and key informant interviews

Floyd,

Silcox,

Strickler

et al. 2024

Drug and Alcohol Dependence Reports

Self Cite

View full text Add to dashboard Cite

“…Given that the impacts of legalization on the social acceptability of treatment-seeking behaviors are still poorly understood [46], it is difficult to surmise whether changes in the legal status of cannabis across states and over the duration of the study may have had a distorting impact on the results. Another key policy area is the state adoption of naloxone access laws (NAL), which increased rapidly from 2013 onward [47]. By 2020, all 50 states and the District of Columbia had some form of NAL in place, although the laws varied significantly across states [48].…”

Section: Limitationsmentioning

confidence: 99%

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

Patton¹,

Abramovitz²,

Johnson³

et al. 2022

J Med Internet Res

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Background There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information. Objective This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change. Methods We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database. Results Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05). Conclusions This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders.

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“…While these laws vary by state, they typically include one or more of the following provisions: (1) allowing for non-patient-specific prescriptions through a standing or protocol order; (2) granting prescriptive authority to pharmacists; (3) permitting third-party prescribing that authorizes the prescribing and dispensing of naloxone to people who are not at-risk of overdose themselves, but are likely to witness an overdose and administer naloxone to others; (4) mandatory co-prescribing to persons at high risk for overdose, such as those dispensed high doses of prescription opioids or with a history of substance use disorder; or 5) removal of professional, civil, and/or criminal liability for persons administering, prescribing, or dispensing naloxone ( Davis and Carr, 2015 , 2017 ). All 50 states had implemented NALs as of 2017, with rapid adoption beginning in 2013 ( Bohler et al, 2021 ). There is rigorous evidence suggesting NALs increase naloxone availability in communities with mixed evidence of their impact on opioid-related mortality ( Mauri et al, 2020 ; Smart et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Predictors of US states’ adoption of naloxone access laws, 2001–2017

Cited by 7 publications

References 57 publications

Policies, adaptations, and ongoing challenges to naloxone, buprenorphine and nonprescription syringe access across four-states: Findings from an environmental scan and key informant interviews

Policies, adaptations, and ongoing challenges to naloxone, buprenorphine and nonprescription syringe access across four-states: Findings from an environmental scan and key informant interviews

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

The policy landscape for naloxone distribution in four states highly impacted by fatal opioid overdoses

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