Screener And Opioid Assessment For Patients With Pain Research Articles

Team approach for nonmedical opioid use

Team approach for nonmedical opioid use

Frequency of and Factors Associated With Nonmedical Opioid Use Behavior Among Patients With Cancer Receiving Opioids for Cancer Pain

One of the main aims of research on nonmedical opioid use (NMOU) is to reduce the frequency of NMOU behaviors through interventions such as universal screening, reduced opioid exposure, and more intense follow-up of patients with elevated risk. The absence of data on the frequency of NMOU behavior is the major barrier to conducting research on NMOU. To determine the overall frequency of and the independent predictors for NMOU behavior. In this prognostic study, 3615 patients with cancer were referred to the supportive care center at MD Anderson Cancer Center from March 18, 2016, to June 6, 2018. Patients were eligible for inclusion if they had cancer and were taking opioids for cancer pain for at least 1 week. Patients were excluded if they had no follow-up within 3 months of initial consultation, did not complete the appropriate questionnaire, or did not have scheduled opioid treatments. After exclusion, a total of 1554 consecutive patients were assessed for NMOU behavior using established diagnostic criteria. All patients were assessed using the Edmonton Symptom Assessment Scale, the Screener and Opioid Assessment for Patients with Pain (SOAPP), and the Cut Down, Annoyed, Guilty, Eye Opener-Adapted to Include Drugs (CAGE-AID) survey. Data were analyzed from January 6 to September 25, 2020. A total of 1554 patients (median [interquartile range (IQR)] age, 61 [IQR, 52-69] years; 816 women [52.5%]; 1124 White patients [72.3%]) were evaluable for the study, and 299 patients (19.2%) had 1 or more NMOU behaviors. The median (IQR) number of NMOU behaviors per patient was 1 (IQR, 1-3). A total of 576 of 745 NMOU behaviors (77%) occurred by the first 2 follow-up visits. The most frequent NMOU behavior was unscheduled clinic visits for inappropriate refills (218 of 745 [29%]). Eighty-eight of 299 patients (29.4%) scored 7 or higher on SOAPP, and 48 (16.6%) scored at least 2 out of 4 points on the CAGE-AID survey. Results from the multivariate model suggest that marital status (single, hazard ratio [HR], 1.58; 95% CI, 1.15-2.18; P = .005; divorced, HR, 1.43; 95% CI, 1.01-2.03; P = .04), SOAPP score (positive vs negative, HR, 1.35; 95% CI, 1.04-1.74; P = .02), morphine equivalent daily dose (MEDD) (HR, 1.003; 95% CI, 1.002-1.004; P < .001), and Edmonton Symptom Assessment Scale pain level (HR, 1.11; 95% CI, 1.06-1.16; P < .001) were independently associated with the presence of NMOU behavior. In recursive partition analysis, single marital status, MEDD greater than 50 mg, and SOAPP scores greater than 7 were associated with a higher risk (56%) for the presence of NMOU behavior. This prognostic study of patients with cancer taking opioids for cancer pain found that 19% of patients developed NMOU behavior within a median duration of 8 weeks after initial supportive care clinic consultation. Marital status (single or divorced), SOAPP score greater than 7, higher levels of pain severity, and MEDD level were independently associated with NMOU behavior. This information will assist clinicians and investigators designing clinical and research programs in this important field.

Aberrant opioid use behaviour in advanced cancer

ObjectivesTo evaluate the presence of aberrant behaviour in a consecutive sample of patients with advanced cancer treated with opioids in a country like Italy, with its peculiar attitudes towards the...

Tools for Community-Based Pharmacist Patient Care Services to Support Optimal Opioid Use

Tools for Community-Based Pharmacist Patient Care Services to Support Optimal Opioid Use

Mental health and opioid addiction comorbidities among chronic pain patients

ObjectiveAssessing mental health and opioid addiction comorbidities among chronic pain patients using a large longitudinal clinical, operational, and laboratory data set.IntroductionThe National Institute for Drug Abuse Report, Common Comorbidities with Substance Use Disorders, states there are “many individuals who develop substance use disorders (SUD) are also diagnosed with mental disorders, and vice versa.”(1) Prescription opioids are amongst the most commonly used drugs that lead to illicit drug use.(2)Much of the data about the starting point of the prescription opioid addiction is in the patient health history and is recorded within the provider electronic health record and administrative systems.DescriptionThere are a variety of addiction and misuse risk screening tools available and selecting appropriate tools screening can be confusing for providers. Examples of common screening tools: Opioid Abuse Risk Screener (OARS), Opioid Risk Tool (ORT), Screener and Opioid Assessment for Patients with Pain (SOAPP), Current Opioid Misuse Measure (COMM), Diagnosis, Intractability, Risk, and Efficacy (DIRE). These opioid risk screening tools are interview based and vary in how they survey for psychosocial factors. The screening tools are useful, but are meant only to alert the provider to conduct further investigation.(3)Understanding how the comorbidities recorded in the patient’s clinical interactions may help improve risk assessment investigations and ongoing monitoring programs. Studying the chronic pain patients’ longitudinal clinical, operational, and laboratory records provides the basis for better study controls than those using population based on emergency department admission and mortality events.MethodsThe analysis leverages IBM's Explorys electronic health record (EHR) data, a large integrated source of real world clinical, operational and lab data across 39 large integrated delivery networks that span the continuum of care. In addition to demographic characteristics of drug abusers, we will describe common comorbidities of selected mental health diagnoses, examine coding-related issues, distinguish chronic and episodic addiction and look for regional differences due to state/local level prescribing training and provider addiction awareness.How the Moderator Intends to Engage the Audience in Discussions on the TopicPromote the event through interatction with the @ISDS twitter account and #ISDS19 hashtag.Solicit question for presenters-panelists through social media before the briefing, and meet with presenters before the event to tune the presenations to areas of interest.Conduct a demographic poll of the audience to get them engaged. Ask audience to stand to show their organization-role. e.g. state-local public health, provider, vendor. This helps the presenters adapt to the audience profile.After each panelist speaks, have the panelist ask a question to the audience about a lingering question that arose during the research. Limit the audience to ~1 minute to answer. Allow panelists to ask a few more questions if the process is working, but limit to overall event time schedule.Finish with Q&amp;A from the audience.

Psychological Dependence and Prescription Opioid Misuse and Abuse

There has been notable concern regarding the rising prevalence of prescription opioid misuse, abuse, and fatal overdoses. A great deal of scholarly activity has been devoted to identifying risk factors for opioid misuse/abuse and less effort on discovering modifiable factors to mitigate risk. In this issue of Pain Medicine , Elander and colleagues [1] conducted an online survey of 112 individuals in the general population who had pain and had used over-the-counter (OTC) and prescription analgesics in the last month. They assessed typical pain factors (frequency, intensity, pain type, and etiology), opioid abuse risk based on a validated risk assessment measure, the Screener and Opioid Assessment for Patients with Pain (SOAPP), mood and anxiety disorders, and frequency and use of OTC and prescription analgesics. In addition, they collected a number of psychological measures, some very novel (alexithymia, mindfulness, self-compassion), along with known possible pain and substance abuse mediators (pain catastrophizing, pain acceptance, pain self-efficacy). Statistical analysis of the relationship between analgesic dependence (based on a modified Leeds Dependence Questionnaire) and the measures of pain, mood, and aberrant drug-related behavior (ADRB) (SOAPP) and other psychological factors revealed that the best single predictor of analgesic dependence was the SOAPP. Other independent factors predictive of dependence were the frequency of analgesic use and the …

Distinguishing Features of Cancer Patients Who Smoke: Pain, Symptom Burden, and Risk for Opioid Misuse

Although many cancer patients who have pain are smokers, the extent of their symptom burden and risk for opioid misuse are not well understood. In this study we analyzed records of patients being treated for cancer pain, 94 of whom were smokers and 392 of whom were nonsmokers, to determine smoking status group differences. Smokers had significantly higher pain intensity, fatigue, depression, and anxiety than nonsmokers (independent samples t-tests P < .002). Smokers were at higher risk for opioid misuse based on the short form of the Screener and Opioid Assessment for Patients with Pain (SOAPP). Specifically, smokers had more frequent problems with mood swings, taking medications other than how they are prescribed, a history of illegal drug use, and a history of legal problems (chi-square tests P ≤ .002). Changes in pain and opioid use were examined in a subset of patients (146 nonsmokers and 46 smokers) who were receiving opioid therapy on at least 2 of the 3 data time points (consult, follow-up 1 month after consult, follow-up 6 to 9 months after consult). Results based on multilevel linear modeling showed that over a period of approximately 6 months, smokers continued to report significantly higher pain than nonsmokers. Both smokers and nonsmokers reported a significant decline in pain across the 6-month period; the rate of decline did not differ across smokers and nonsmokers. No significant difference over time was found in opioid use between smokers and nonsmokers. These findings will guide subsequent studies and inform clinical practice, particularly the relevancy of smoking cessation. PerspectiveThis article describes pain, symptom burden, and risk for opioid misuse among cancer patients with pain across smoking status. Smoking appears to be a potential mechanism for having an increased pain and symptom burden and risk for opioid misuse. This improved understanding of cancer pain will inform clinical practice.

Opioid Dependence: Managing the High Cost of Treatment Failure

BackgrOunD: The use of opioids for chronic noncancer pain increased 222% from 1992 to 2002. Opioid dependence has also increased significantly, leading to a burden on patients, employers, insurers, society, and the entire health care system. It is imperative that opioid dependence is addressed and treated properly, in order to return patients to being productive participants in the workplace and society. OBjecTIve: To provide an overview of addiction, abuse, and dependence and identify risk factors for addiction. Summary: Studies have shown that intensive use of opioids is associated with increased utilization of costly health care services, prolonged disability, and continued use of opioids, leading to abuse and dependence in many patients. While identifying patients at risk for developing opioid dependence is difficult, there are many risk stratification tools now available to practitioners, including the Opioid risk Tool (OrT) or Screener and Opioid assessment for Patients with Pain (SOaPP). understanding the differences between dependence, addiction, and tolerance is essential to managing patients on opioids. cOncLuSIOn: It is imperative that patients be properly managed when being treated for pain. Physicians and employers have to be able to identify patients at risk for opioid abuse or exhibiting symptoms of opioid abuse and know how to address their needs. J Manag Care Pharm. 2010;16(1-b):S4-S8 copyright © 2010, academy of managed care Pharmacy. all rights reserved. SAIRA A. JAN, MS, PharmD, is Clinical Director, Blue Cross Blue Shield of New Jersey, and Associate Professor at the Ernest Mario School of Pharmacy of Rutgers, the State University of New Jersey. AUTHOR CORRESPONDENCE: Saira A. Jan, MS, PharmD, Director of Clinical Pharmacy Management, Horizon Blue Cross Blue Shield of New Jersey, Newark, NJ 07105-2200. Tel.: 973.466.6192; Fax: 973.466.4665. E-mail: Saira_ Jan@horizon-bcbsnj.com. Author Drug abuse and dependence are on the rise. The widespread use of opioid analgesics for the treatment of chronic noncancer pain and for acute pain management began in the late 1980s. Between 1980 and 2000, there was an increase from 8% to 16% in the number of patients receiving opioids for chronic musculoskeletal pain and an increase in use from 8% to 11% for acute musculoskeletal pain.1,2 In 2002, reports show a 222% increase in the absolute number or prescriptions for opioid narcotics over the previous 10-year period.1,3 Today, the most common method for treating chronic pain is with the use of prescription analgesics, including opioids.4 In the 1970s, chronic pain patients were encouraged by society to avoid opioids due to concerns that taking opioids invariably led to addiction.5 In the early 1980s, the pendulum shifted to widespread use of opioids, based on results of a small study (n = 20) showing chronic pain patients could benefit from pain control using opioids with little risk of developing dependence.6,7,8,9 Additionally, in the 1990s, a review article of several studies showed patients with neuropathic pain experienced relief from opioids.6,8,9 Unfortunately, many patients continue to take opioids despite inadequate pain control. Patients on chronic narcotic pain medications generate higher costs of health care, have higher surgery rates, a greater level of disability, and higher rates of late opioid use.10 Late opioid use is defined as receiving ≥ 5 opioid prescriptions between 30 and 730 days after onset of pain, a quantity of prescriptions that is generally beyond what is considered appropriate use for symptom control for an acute pain exacerbation.1 In a retrospective cohort study of 8,443 workers’ compensation claims for acute disabling lower back pain, looking at claims from January 1, 2002, and December 31, 2003, intensive use of opioids early in treatment was associated with worse long-term outcomes, increased use of costly medical services (including surgery), prolonged disability, and continued use of opioids.1 One dilemma that arises with using opioids long term is that hyperalgesia (increased pain sensitivity), decreased libido and other hormonal effects, and depression may occur, as well as tolerance. Statistics have shown that at least 1 of these effects is experienced by 51% of all patients taking oral opioids.2 Another concern is the risk of dependence and addiction. For most of the twentieth century, opioid dependence has been problematic.11 A review of 24 studies (2,507 chronic pain patients) have shown that there is a 3.3% risk of developing addiction.6 While this percentage is low, it represents a large population that is hard to manage. Evaluating and re-evaluating patients who are at higher risk of developing addiction is something that all clinicians treating chronic pain patients treated with opioids should be performing on an ongoing basis.6

Introduction: landscape of opioid dependence.

The use of opioids for chronic noncancer pain increased 222% from 1992 to 2002. Opioid dependence has also increased significantly, leading to a burden on patients, employers, insurers, society, and the entire health care system. It is imperative that opioid dependence is addressed and treated properly, in order to return patients to being productive participants in the workplace and society. To provide an overview of addiction, abuse, and dependence and identify risk factors for addiction. Studies have shown that intensive use of opioids is associated with increased utilization of costly health care services, prolonged disability, and continued use of opioids, leading to abuse and dependence in many patients. While identifying patients at risk for developing opioid dependence is difficult, there are many risk stratification tools now available to practitioners, including the Opioid Risk Tool (ORT) or Screener and Opioid Assessment for Patients with Pain (SOAPP). Understanding the differences between dependence, addiction, and tolerance is essential to managing patients on opioids. It is imperative that patients be properly managed when being treated for pain. Physicians and employers have to be able to identify patients at risk for opioid abuse or exhibiting symptoms of opioid abuse and know how to address their needs.

A Comparison of Common Screening Methods for Predicting Aberrant Drug-Related Behavior among Patients Receiving Opioids for Chronic Pain Management

The ability to predict risk for violating opioid medication policies, known as aberrant drug-related behavior, is critical for providing optimal treatment. Many pain management centers measure risk using one of several partially validated measures: the Screener and Opioid Assessment for Patients with Pain (SOAPP), the Diagnosis, Intractability, Risk, and Efficacy inventory (DIRE), and/or the Opioid Risk Tool (ORT). However, little is known about how these measures compare with each other in predicting aberrant drug-related behavior and discontinuance of opioid pain medications. The current study aimed to address this research question. Participants were 48 patients who attended a pain management center in Tennessee but were later discontinued from opioids for aberrant drug-related behavior. Patients referred for opioid medication for pain management participated in a semi-structured clinical interview with the staff psychologist and completed the aforementioned measures. Patients generally returned to the pain clinic on a monthly basis for medication management. Results. Analyses compared the sensitivity of each self-report measure and the clinical interview in predicting discontinuance for aberrant drug-related behavior. showed the highest sensitivity for the clinical interview (0.77) and the SOAPP (0.72), followed by the ORT (0.45) and the DIRE (0.17). Combining the clinical interview with the SOAPP increased sensitivity to 0.90. Among patients who were discontinued from opioids for aberrant drug-related behaviors, the clinical interview and the SOAPP were most effective at predicting risk at baseline. Implications for future research and clinical practice are discussed.

Opioids for Chronic Noncancer Pain: Prediction and Identification of Aberrant Drug-Related Behaviors: A Review of the Evidence for an American Pain Society and American Academy of Pain Medicine Clinical Practice Guideline

Optimal methods to predict risk of aberrant drug-related behaviors before initiation of opioids for chronic noncancer pain and to identify aberrant behaviors after therapy is initiated are uncertain. We systematically reviewed published literature identified through searches of Ovid MEDLINE and the Cochrane databases through July 2008. Diagnostic test characteristics and accompanying confidence intervals were calculated with data extracted from the studies. Four prospective studies evaluated diagnostic accuracy of risk prediction instruments. Two higher-quality derivation studies found that high scores on the Screener and Opioid Assessment for Patients with Pain (SOAPP) Version 1 and the Revised SOAPP (SOAPP-R) instruments weakly increased the likelihood for future aberrant drug-related behaviors (positive likelihood ratios [PLR], 2.90 [95% CI, 1.91 to 4.39] and 2.50 [95% CI, 1.93 to 3.24], respectively). Low scores on the SOAPP Version 1 moderately decreased the likelihood for aberrant drug-related behaviors (negative likelihood ratio [NLR], 0.13 [95% CI, 0.05 to 0.34]) and low scores on the SOAPP-R weakly decreased the likelihood (NLR, 0.29 [95% CI, 0.18 to 0.46]), but estimates are too imprecise to determine if there is a difference between these instruments. One lower-quality study found that categorization as high risk using the Opioid Risk Tool strongly increased the likelihood for future aberrant drug-related behaviors (PLR, 14.3 [95% CI, 5.35 to 38.4]) and classification as low risk strongly decreased the likelihood (PLR, 0.08 [95% CI, 0.01 to 0.62]). Nine studies evaluated monitoring instruments for identification of aberrant drug-related behaviors in patients on opioid therapy. One higher-quality derivation study found higher scores on the Current Opioid Misuse Measure (COMM) weakly increased the likelihood of current aberrant drug-related behaviors (PLR, 2.77 [95% CI, 2.06 to 3.72]) and lower scores weakly decreased the likelihood (NLR, 0.35 [95% CI, 0.24 to 0.52]). In 8 studies of other monitoring instruments, diagnostic accuracy was poor, results were difficult to interpret due to methodological shortcomings, or standard diagnostic test characteristics were not reported. Definitions for aberrant drug-related behaviors were not standardized across studies and did not account for seriousness of identified behaviors. No reliable evidence exists on accuracy of urine drug screening, pill counts, or prescription drug monitoring programs; or clinical outcomes associated with different assessment or monitoring strategies. Evidence on prediction and identification of aberrant drug-related behaviors is limited. Although several screening instruments may be useful, evidence is sparse and primarily based on derivation studies, and methodological shortcomings exist in all studies. Research that performs external validation, uses standardized definitions for clinically relevant aberrant drug-related behaviors, and evaluates clinical outcomes associated with different assessment and monitoring strategies is needed.

The interface between pain and drug abuse and the evolution of strategies to optimize pain management while minimizing drug abuse.

Pain management is facing continued undertreatment of pain despite a growing problem with prescription opioid abuse. This has created a tension among prescribers and feelings of helplessness with regards to what constitutes appropriate practice. This article provides a review of pain management efforts and focuses on two key areas of potential interest. First, the emergence of prescreening tools for identifying appropriate candidates for opioid therapy are introduced and discussed, including the Opioid Risk Tool (ORT), the Screener and Opioid Assessment for Patients with Pain (SOAPP), and the Pain Assessment and Documentation Tool (PADT). In addition to these screening efforts, a novel concept of "in and out of the box" prescribing is presented, focusing on five areas of concern for judging whether one's prescribing patterns are matching peer prescribing patterns. While more work needs to be done, the discussion of these areas should offer some questions for self analysis by physicians regarding their prescribing patterns. Overall, the authors must embrace the concept of rational pain management and assess patients for risk both before writing the first opioid prescription for them and thereafter. In addition, we must remember that good pain management should lead to some decreases in pain perception for the patient combined with a corresponding increase in ability to function. By reviewing these tools and proposed novel guidelines for in/out of the box prescribing and adopting them into practice as appropriate, the physician will take a significant step in providing effective pain management while minimizing risk of opioid misuse.

Validation of the revised Screener and Opioid Assessment for Patients with Pain (SOAPP-R).

The original Screener and Opioid Assessment for Patients with Pain (SOAPP) is a conceptually derived self-report questionnaire designed to predict aberrant medication-related behaviors among chronic pain patients considered for long-term opioid therapy. The purpose of this study was to develop and validate an empirically derived version of the SOAPP (SOAPP-R) that addresses some limitations of the original SOAPP. In successive steps, items were reduced from an initial pool of 142 to a 97-item beta version. The beta version was administered to 283 chronic pain patients receiving long-term opioid therapy. Items were evaluated based on data collected at follow-up, including correlation with the Aberrant Drug Behavior Index (ADBI), derived from interview data, physician ratings, and urine toxicology screens. Twenty-four items were retained and comprise the final SOAPP-R. Coefficient alpha was .88, and receiver operating characteristics curve analysis yielded an area under the curve of .81 (P < .001). A cutoff score of 18 showed adequate sensitivity (.81) and specificity (.68). The obtained psychometrics, along with the use of a predictive criterion that goes beyond self-report, suggest that the SOAPP-R is an improvement over the original version in screening risk potential for aberrant medication-related behavior among persons with chronic pain. There is a need for a screener for abuse risk in patients prescribed opioids for pain. This study presents a revised version of the SOAPP-R that is empirically derived with good reliability and validity but is less susceptible to overt deception than the original SOAPP version 1.

Validation and Clinical Application of the Screener and Opioid Assessment for Patients with Pain (SOAPP)

The Screener and Opioid Assessment for Patients with Pain (SOAPP) is a brief, self-administered screening instrument used to assess suitability of long-term opioid therapy for chronic pain patients. This study presents preliminary data to examine the reliability and validity of the SOAPP as a measure of risk of opioid abuse for patients on opioid medication. Patients taking opioids for noncancer pain ( n = 396) from two pain centers completed the SOAPP prior to being placed on opioids for pain. Demographic data, SOAPP scores, and results of urine toxicology screens from the patients' medical records were examined. Patients were divided into two groups of high and low risk of opioid abuse potential based on cutoff scores of 8 and higher on the SOAPP. Results showed that patients in the high-risk group were younger, more likely to be asked to give a urine screen, and had more abnormal urine screens compared with those in the low-risk group ( P < 0.05). A combined factor analysis of the SOAPP revealed five factors labeled 1) history of substance abuse, 2) legal problems, 3) craving medication, 4) heavy smoking, and 5) mood swings. Preliminary support was found for the internal reliability and predictive validity of the SOAPP. Current limitations of the SOAPP and future directions for change are discussed.

Validation and comparison of the SOAPP (Screener and Opioid Assessment for Patients with Pain) in two pain centers

Validation and comparison of the SOAPP (Screener and Opioid Assessment for Patients with Pain) in two pain centers