Literature DB >> 33482961

Demographic, Clinical, and Prescribing Characteristics Associated with Future Opioid Use in an Opioid-Naive Population in an Integrated Health System.

David M Mosen1, A Gabriela Rosales1, Rajasekhara Mummadi2, Weiming Hu1, Neon Brooks1.   

Abstract

INTRODUCTION: Health systems and prescribers need additional tools to reduce the risk of opioid dependence, abuse, and overdose. Identifying opioid-naive individuals who are at risk of opioid dependence could allow for the development of needed interventions.
METHODS: We conducted a retrospective cohort analysis of 23,804 adults in an integrated health system who had received a first opioid prescription between 2010 and 2015. We compared the demographic, clinical, and prescribing characteristics of individuals who later received a third opioid dispense at least 27 days later, indicating long-term opioid use, with those who did not.
RESULTS: The strongest predictors of continued opioid use were an initial prescription dosage of 90 morphine milligram equivalence or more; prescription of extended-release opioids, rather than short-release; and being prescribed outside of a hospital setting. Patients with a third prescription were also more likely to be older than 45 years, white, and non-Hispanic and to have physical comorbidities or prior substance abuse or mental health diagnoses. DISCUSSION: Our findings are largely consistent with prior research but provide new insight into differences in continued opioid use by opioid type, prescribing location, ethnicity, and comorbidities. Together with previous research, our data support a pattern of higher opioid use among older adults but higher rates of diagnosed opioid abuse among younger adults.
CONCLUSIONS: By identifying population characteristics associated with continued opioid use following a first prescription, our data pave the way for quality improvement interventions that target individuals who are at higher risk of opioid dependence.
Copyright © 2020 The Permanente Press. All rights reserved.

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Year:  2020        PMID: 33482961      PMCID: PMC7849307          DOI: 10.7812/TPP/19.236

Source DB:  PubMed          Journal:  Perm J        ISSN: 1552-5767


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2.  Factors Influencing Long-Term Opioid Use Among Opioid Naive Patients: An Examination of Initial Prescription Characteristics and Pain Etiologies.

Authors:  Anuj Shah; Corey J Hayes; Bradley C Martin
Journal:  J Pain       Date:  2017-07-13       Impact factor: 5.820

3.  Non-medical use, abuse and dependence on prescription opioids among U.S. adults: psychiatric, medical and substance use correlates.

Authors:  William C Becker; Lynn E Sullivan; Jeanette M Tetrault; Rani A Desai; David A Fiellin
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4.  Risk factors for clinically recognized opioid abuse and dependence among veterans using opioids for chronic non-cancer pain.

Authors:  Mark J Edlund; Diane Steffick; Teresa Hudson; Katherine M Harris; Mark Sullivan
Journal:  Pain       Date:  2007-04-20       Impact factor: 6.961

5.  CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016.

Authors:  Deborah Dowell; Tamara M Haegerich; Roger Chou
Journal:  MMWR Recomm Rep       Date:  2016-03-18

6.  Factors predicting development of opioid use disorders among individuals who receive an initial opioid prescription: mathematical modeling using a database of commercially-insured individuals.

Authors:  Bryan N Cochran; Annesa Flentje; Nicholas C Heck; Jill Van Den Bos; Dan Perlman; Jorge Torres; Robert Valuck; Jean Carter
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7.  Association of Lowering Default Pill Counts in Electronic Medical Record Systems With Postoperative Opioid Prescribing.

Authors:  Alexander S Chiu; Raymond A Jean; Jessica R Hoag; Mollie Freedman-Weiss; James M Healy; Kevin Y Pei
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Review 8.  Dynamic risk factors in the misuse of opioid analgesics.

Authors:  Joseph V Pergolizzi; Christopher Gharibo; Steven Passik; Sumedha Labhsetwar; Robert Taylor; Jason S Pergolizzi; Gerhard Müller-Schwefe
Journal:  J Psychosom Res       Date:  2012-04-05       Impact factor: 3.006

9.  Risk factors for serious prescription opioid-related toxicity or overdose among Veterans Health Administration patients.

Authors:  Barbara Zedler; Lin Xie; Li Wang; Andrew Joyce; Catherine Vick; Furaha Kariburyo; Pradeep Rajan; Onur Baser; Lenn Murrelle
Journal:  Pain Med       Date:  2014-06-14       Impact factor: 3.750

10.  Opioid prescription fill rates after emergency department discharge.

Authors:  Howard S Kim; Kennon J Heard; Susan Heard; Jason A Hoppe
Journal:  Am J Health Syst Pharm       Date:  2016-06-15       Impact factor: 2.637

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  1 in total

1.  Linkage of public health and all payer claims data for population-level opioid research.

Authors:  Sara E Hallvik; Nazanin Dameshghi; Sanae El Ibrahimi; Michelle A Hendricks; Christi Hildebran; Carissa J Bishop; Scott G Weiner
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  1 in total

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