{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T14:34:26Z","timestamp":1783780466049,"version":"3.55.0"},"reference-count":51,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Substance Abuse"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Prescription drug monitoring programs (PDMPs) are tools that states can use to fight prescription opioid misuse within their jurisdiction. However, because PDMPs make prescription opioids more difficult to access, these programs may have the unintended consequence of increasing deaths related to illicit opioids.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study uses fixed effects models to estimate how PDMP regulatory strength is associated with both prescription opioid- and heroin-related deaths between 1999 and 2016. PDMP regulatory strength is measured by creating a score using multiple correspondence analysis (MCA). Additional models replace the MCA score with a binary indicator for the presence of one particular regulation requiring physicians to access the system before writing opioid prescriptions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Results show that continuous measures of PDMP strength are not generally associated with prescription opioid- or heroin-related death rates. Yet, one model does show that PDMP scores are positively associated with the heroin-related death rate. The models using the binary mandatory access variable show a strong positive association with both prescription opioid and heroin deaths.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study supports the theory that more stringent state PDMPs are associated with higher rates of heroin-related deaths, potentially due to decreases in prescription opioid availability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1080\/08897077.2019.1695707","type":"journal-article","created":{"date-parts":[[2019,12,10]],"date-time":"2019-12-10T10:40:36Z","timestamp":1575974436000},"page":"65-75","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":19,"title":["Do Prescription Drug Monitoring Programs Encourage Prescription \u2013 or Illicit \u2013 Opioid Abuse?"],"prefix":"10.1177","volume":"42","author":[{"given":"Devon","family":"Meadowcroft","sequence":"first","affiliation":[{"name":"Department of Agricultural Economics, Oklahoma State University, Stil, Oklahoma, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Whitacre","sequence":"additional","affiliation":[{"name":"Department of Agricultural Economics, Oklahoma State University, Stil, Oklahoma, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2021,1,1]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"St. Louis County Prescription Drug Monitoring Program. 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