17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Factors associated with opioid overdose: a 10-year retrospective study of patients in a large integrated health care system

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          Opioid overdoses (ODs) have been increasing, and harm reduction efforts are a priority. The success of these efforts will be dependent on the identification of at-risk patients and improved access to the antidote naloxone. Therefore, to identify access to naloxone and factors associated with negative health outcomes, we conducted a retrospective study of patients with OD to identify those at highest risk of adverse outcomes and to assess the use of naloxone.

          Methods

          We conducted a study of electronic health records for patients admitted to the largest multihospital system in the region – the Geisinger Health System (GHS) for ODs – from April 2005 through March 2015. ODs were defined by International Classification of Diseases-9 codes (age range: 10–95 years). Bivariate analyses and multiple logistic regressions were conducted to identify pre-OD factors associated with adverse health outcomes post-OD.

          Results

          We identified 2,039 patients with one or more ODs, of whom 9.4% were deceased within 12 months. Patient demographics suggest that patients with OD had a mean age of 52 years, were not married (64%), and were unemployed (78%). Common comorbidities among patients with OD include cardiovascular disease (22%), diabetes (14%), cancer (13%), and the presence of one or more mental health disorders (35%). Few patients had a prescription order for naloxone (9%) after their OD. The majority of patients with OD were in proximity to GHS health care facilities, with 87% having a GHS primary care provider. In multiple logistic regressions, common predictors of adverse outcomes, including death, repeated ODs, frequent service use, and high service cost, were higher prescription opioid use, comorbid medical conditions, comorbid mental disorders, and concurrent use of other psychotropic medications.

          Conclusion

          This study suggests opportunities for improving OD outcomes. Those who receive higher quantities of prescription opioids concurrent with other psychotropic medicines may need closer monitoring to avoid death, repeated OD events, higher service use, and higher service costs. Other opportunities for improving OD outcomes include the use of electronic health records to notify physicians of high-risk patients and updating of guidelines/operation manuals focused on the distribution of naloxone to those in highest need.

          Related collections

          Most cited references29

          • Record: found
          • Abstract: not found
          • Article: not found

          Diagnostic and statistical manual of mental disorders.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system.

            Our study sought to assess the prevalence of and risk factors for opioid drug dependence among out-patients on long-term opioid therapy in a large health-care system. Using electronic health records, we identified out-patients receiving 4+ physician orders for opioid therapy in the past 12 months for non-cancer pain within a large US health-care system. We completed diagnostic interviews with 705 of these patients to identify opioid use disorders and assess risk factors. Preliminary analyses suggested that current opioid dependence might be as high as 26% [95% confidence interval (CI) = 22.0-29.9] among the patients studied. Logistic regressions indicated that current dependence was associated with variables often in the medical record, including age <65 [odds ratio (OR) = 2.33, P = 0.001], opioid abuse history (OR = 3.81, P < 0.001), high dependence severity (OR = 1.85, P = 0.001), major depression (OR = 1.29, P = 0.022) and psychotropic medication use (OR = 1.73, P = 0.006). Four variables combined (age, depression, psychotropic medications and pain impairment) predicted increased risk for current dependence, compared to those without these factors (OR = 8.01, P < 0.001). Knowing that the patient also had a history of severe dependence and opioid abuse increased this risk substantially (OR = 56.36, P < 0.001). Opioid misuse and dependence among prescription opioid patients in the United States may be higher than expected. A small number of factors, many documented in the medical record, predicted opioid dependence among the out-patients studied. These preliminary findings should be useful in future research efforts. © 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Predictors of opioid misuse in patients with chronic pain: a prospective cohort study

              Background Opioid misuse can complicate chronic pain management, and the non-medical use of opioids is a growing public health problem. The incidence and risk factors for opioid misuse in patients with chronic pain, however, have not been well characterized. We conducted a prospective cohort study to determine the one-year incidence and predictors of opioid misuse among patients enrolled in a chronic pain disease management program within an academic internal medicine practice. Methods One-hundred and ninety-six opioid-treated patients with chronic, non-cancer pain of at least three months duration were monitored for opioid misuse at pre-defined intervals. Opioid misuse was defined as: 1. Negative urine toxicological screen (UTS) for prescribed opioids; 2. UTS positive for opioids or controlled substances not prescribed by our practice; 3. Evidence of procurement of opioids from multiple providers; 4. Diversion of opioids; 5. Prescription forgery; or 6. Stimulants (cocaine or amphetamines) on UTS. Results The mean patient age was 52 years, 55% were male, and 75% were white. Sixty-two of 196 (32%) patients committed opioid misuse. Detection of cocaine or amphetamines on UTS was the most common form of misuse (40.3% of misusers). In bivariate analysis, misusers were more likely than non-misusers to be younger (48 years vs 54 years, p < 0.001), male (59.6% vs. 38%; p = 0.023), have past alcohol abuse (44% vs 23%; p = 0.004), past cocaine abuse (68% vs 21%; p < 0.001), or have a previous drug or DUI conviction (40% vs 11%; p < 0.001%). In multivariate analyses, age, past cocaine abuse (OR, 4.3), drug or DUI conviction (OR, 2.6), and a past alcohol abuse (OR, 2.6) persisted as predictors of misuse. Race, income, education, depression score, disability score, pain score, and literacy were not associated with misuse. No relationship between pain scores and misuse emerged. Conclusion Opioid misuse occurred frequently in chronic pain patients in a pain management program within an academic primary care practice. Patients with a history of alcohol or cocaine abuse and alcohol or drug related convictions should be carefully evaluated and followed for signs of misuse if opioids are prescribed. Structured monitoring for opioid misuse can potentially ensure the appropriate use of opioids in chronic pain management and mitigate adverse public health effects of diversion.
                Bookmark

                Author and article information

                Journal
                Subst Abuse Rehabil
                Subst Abuse Rehabil
                Substance Abuse and Rehabilitation
                Substance Abuse and Rehabilitation
                Dove Medical Press
                1179-8467
                2016
                16 September 2016
                : 7
                : 131-141
                Affiliations
                [1 ]Center for Health Research
                [2 ]Biomedical and Translational Informatics, Geisinger Clinic, Danville, PA
                [3 ]Indivior Inc., Richmond, VA
                [4 ]Emergency Medicine Service Line, Central Division, Geisinger Clinic, Danville
                [5 ]Geisinger Interventional Pain Center, Danville, PA, USA
                Author notes
                Correspondence: Joseph A Boscarino, Center for Health Research, Geisinger Clinic, 100 North Academy Avenue, MC 44-00, Danville, PA 17822, USA, Tel +1 570 214 9622, Email jaboscarino@ 123456geisinger.edu
                Article
                sar-7-131
                10.2147/SAR.S108302
                5033108
                27695382
                6f432741-0ff5-494e-bdff-03e2826a488a
                © 2016 Boscarino et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                History
                Categories
                Original Research

                opioids,overdose antidote,naloxone,health care access,health care costs,services utilization,prescription drugs

                Comments

                Comment on this article