{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:08:01Z","timestamp":1740136081662,"version":"3.37.3"},"reference-count":106,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T00:00:00Z","timestamp":1671753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,2,16]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objectives<\/jats:title><jats:p>While opioid addiction, treatment, and recovery are receiving attention, not much has been done on adaptive interventions to prevent opioid use disorder (OUD). To address this, we identify opioid prescription and opioid consumption as promising targets for adaptive interventions and present a design framework.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>Using the framework, we designed Smart Prescription Management (SPM) and Smart Consumption Monitoring (SCM) interventions. The interventions are evaluated using analytical modeling and secondary data on doctor shopping, opioid overdose, prescription quality, and cost components.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>SPM was most effective (30\u201390% improvement, for example, prescriptions reduced from 18 to 1.8 per patient) for extensive doctor shopping and reduced overdose events and mortality. Opioid adherence was improved and the likelihood of addiction declined (10\u201330%) as the response rate to SCM was increased. There is the potential for significant incentives ($2267\u2013$3237) to be offered for addressing severe OUD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>The framework and designed interventions adapt to changing needs and conditions of the patients to become an important part of global efforts in preventing OUD. To the best of our knowledge, this is the first paper on adaptive interventions for preventing OUD by addressing both prescription and consumption.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>SPM and SCM improved opioid prescription and consumption while reducing the risk of opioid addiction. These interventions will assist in better prescription decisions and in managing opioid consumption leading to desirable outcomes. The interventions can be extended to other substance use disorders and to study complex scenarios of prescription and nonprescription opioids in clinical studies.<\/jats:p><\/jats:sec>","DOI":"10.1093\/jamia\/ocac253","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T14:22:00Z","timestamp":1671805320000},"page":"511-528","source":"Crossref","is-referenced-by-count":4,"title":["Adaptive interventions for opioid prescription management and consumption monitoring"],"prefix":"10.1093","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1127-1274","authenticated-orcid":false,"given":"Neetu","family":"Singh","sequence":"first","affiliation":[{"name":"Department of Management Information Systems, University of Illinois Springfield , Springfield, Illinois, USA"}]},{"given":"Upkar","family":"Varshney","sequence":"additional","affiliation":[{"name":"Department of Computer Information Systems, Georgia State University , Atlanta, Georgia, 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