Framework for Advancing Epidemiological Criminology Research on Prescription Drug Monitoring Programs
Prescription Drug Monitoring Programs (PDMPs) document the dispensing of prescription medications that are designated as controlled substances by federal and state authorities. Previous research using state-operated PDMPs have typically evaluated epidemiological and/or health-related outcomes associ...
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| Medienart: | Elektronisch Aufsatz |
| Sprache: | Englisch |
| Veröffentlicht: |
2021
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| In: |
American journal of criminal justice
Jahr: 2021, Band: 46, Heft: 4, Seiten: 665-681 |
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| Zusammenfassung: | Prescription Drug Monitoring Programs (PDMPs) document the dispensing of prescription medications that are designated as controlled substances by federal and state authorities. Previous research using state-operated PDMPs have typically evaluated epidemiological and/or health-related outcomes associated with use of controlled substances; however, PDMPs are accessed, used and impact on a variety of law enforcement applications. As such, there is potential for PDMPs as a research vehicle for the evaluation of programs and policies to capture controlled substance trends and outcomes that are more relevant for criminology. We propose extensions of the epidemiological-criminology framework to identify and classify potential PDMP research opportunities into five non-mutually exclusive categories: 1) effects on public health and safety outcomes, 2) data use for evaluation of criminology-explicit outcomes, 3) data use for emerging epidemiological-criminology applications, 4) data triangulation and integration, and 5) surveillance of “ecosystem” interactions. Applications and a review of relevant published literature are discussed for each of these categories in the context of highlighting opportunities for criminologists to increase research on PDMPs. Multi-disciplinary research partnerships are recommended to develop more robust study designs and to rigorously interpret and apply findings as reported from studies that use PDMP data. |
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| ISSN: | 1936-1351 |
| DOI: | 10.1007/s12103-021-09632-x |