{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:57:30Z","timestamp":1762005450835,"version":"3.44.0"},"reference-count":48,"publisher":"BMJ","issue":"1","funder":[{"DOI":"10.13039\/100005217","name":"National Center for Injury Prevention and Control","doi-asserted-by":"publisher","award":["5R49CE003090"],"award-info":[{"award-number":["5R49CE003090"]}],"id":[{"id":"10.13039\/100005217","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Inj Prev"],"accepted":{"date-parts":[[2024,4,12]]},"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>State opioid prescribing cap laws, mandatory prescription drug monitoring programme query or enrolment laws and pill mill laws have been implemented across US states to curb high-risk opioid prescribing. Previous studies have measured the impact of these laws on opioid use and overdose death, but no prior work has measured the impact of these laws on fatal crashes in a multistate analysis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>To study the association between state opioid prescribing laws and fatal crashes, 13 treatment states that implemented a single law of interest in a 4-year period were identified, together with unique groups of control states for each treatment state. Augmented synthetic control analyses were used to estimate the association between each state law and the overall rate of fatal crashes, and the rate of opioid-involved fatal crashes, per 100\u2009000 licensed drivers in the state. Fatal crash data came from the Fatality Analysis Reporting System.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Results of augmented synthetic control analyses showed small-in-magnitude, non-statistically significant changes in all fatal crash outcomes attributable to the 13 state opioid prescribing laws. While non-statistically significant, results attributable to the laws varied in either direction\u2014from an increase of 0.14 (95% CI, \u22120.32 to 0.60) fatal crashes per 100\u2009000 licensed drivers attributable to Ohio\u2019s opioid prescribing cap law, to a decrease of 0.30 (95% CI, \u22121.17 to 0.57) fatal crashes\/100 000 licensed drivers attributable to Mississippi\u2019s pill mill law.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>These findings suggest that state-level opioid prescribing laws are insufficient to help address rising rates of fatally injured drivers who test positive for opioids. Other options will be needed to address this continuing injury problem.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/ip-2023-045159","type":"journal-article","created":{"date-parts":[[2024,5,6]],"date-time":"2024-05-06T13:20:28Z","timestamp":1715001628000},"page":"21-27","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Effects of state opioid prescribing laws on rates of fatal crashes in the USA"],"prefix":"10.1136","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1373-1809","authenticated-orcid":false,"given":"Sarah A","family":"White","sequence":"first","affiliation":[{"name":"Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma E","family":"McGinty","sequence":"additional","affiliation":[{"name":"Division of Health Policy and Economics, Weill Cornell Medical College, New York, New York, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandra N","family":"Origenes","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jon S","family":"Vernick","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2024,5,6]]},"reference":[{"key":"2025092502030076000_31.1.21.1","unstructured":"National Vital Statistics System . 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