ORIGINAL ARTICLE
What Do Patients Do With Unused Opioid Medications? Eleanor T. Lewis, PhD,* Michael A. Cucciare, PhD,wz and Jodie A. Trafton, PhD*y
Objectives: The volume of opioid medications being prescribed in the United States is increasing rapidly. Problems associated with the misuse of opioid medications are also increasing, in part because of medication diversion from legitimate prescriptions. However, little is known about what patients do with any unused opioid medications. This paper uses a qualitative analysis of patients’ self-report of medication storage and retention habits to begin to address this gap. Methods: We analyzed responses to the Prescription Drug Use Questionnaire in conjunction with other data on prescription opioid use in a sample of 191 Veteran patients (83% of whom had a preexisting factor associated with higher rates of opioid misuse) who received one or more opioid prescriptions in the previous 12 months. Results: Only 6.3% of participants disposed of extra medications and 24.1% reported having no extra opioids. A total of 65.4% of participants reported retaining some or all opioids even if they ceased taking the medication, and some participants accumulated large amounts of medication. A total of 34.0% of participants described engaging in sharing or diversion of opioids at least once, most often receiving them from a family member or a friend. Discussion: A majority of patients retain unused opioids, and medication sharing is common. Interventions to improve monitoring of patient experience with opioid medication, educate patients about the dangers of opioid use by nonprescribed others, and increase information about medication disposal options could decrease the supply of opioid medications available for misuse. Key Words: pain, medication adherence, qualitative research, patient preferences
(Clin J Pain 2014;30:654–662)
T
he volume of opioid medications prescribed, sold, and consumed in the United States has been increasing rapidly for years.1 By 2010 opioid medication sales were 4
Received for publication February 13, 2013; revised October 9, 2013; accepted August 13, 2013. From the *Center for Innovation to Implementation, Veterans Affairs—Palo Alto Health Care System, Menlo Park; yDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA; wCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Healthcare System; and zDepartment of Psychiatry and Behavioral Sciences, University of Arkansas for Medical Sciences, Little Rock, AR. Funded by RRP 07-316, “Validation of computerized risk assessment for prescription opioid abuse,” a grant awarded by the Department of Veterans’ Affairs (VA) Health Services Research and Development program (HSR&D) and the Quality Enhancement Research Initiative, Washington, DC. Additional support came from Grant # TRX 04-402 and Grant # IMA 04-156 from VA HSR&D, and by a Career Development Award-2 (CDA 08-004) to M.A.C. awarded by the VA HSR&D. The views expressed are those of the authors and not of the Department of Veterans Affairs. The authors declare no conflict of interest. Reprints: Eleanor T. Lewis, PhD, Center for Innovation to Implementation, Veterans Affairs—Palo Alto Health Care System, 795 Willow Road (152-MPD) Menlo Park, CA 94025 (e-mail: [email protected]). Copyright r 2013 by Lippincott Williams & Wilkins
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times the sales in 1999.2 In 2009 there were approximately 257 million prescriptions for opioids dispensed3 and in 2010 the most common medication prescribed in the United States was hydrocodone (131.2 million prescriptions).4 Increased prescription of opioid medications to treat pain has been paralleled by a large and well-documented increase in prescription opioid-related problems, including misuse, abuse, accidental poisoning, fatal and nonfatal overdoses, emergency department visits, and litigation against physicians.5–8 Opioid analgesics are now the most commonly misused prescription medications in the United States.9 Existing evidence suggests that a primary source of pain medications for people who misuse and abuse them is legitimate prescriptions.10 In the 2011 National Survey on Drug Use and Health,9 70.8% of those who used a prescription medication nonmedically obtained the medication from a friend or relative (with or without their knowledge), and an additional 18.1% received the medication from a single provider. Surveys of college-age students found that among those who used prescription opioids for nonmedical reasons a third reported their source for the opioid was a friend, and only slightly fewer reported the source was a parent.11 Similarly, a survey of people who abuse street drugs found that 37% reported family members or friends were sources of opioids.12 In a Veteran population with pain, 16.3% reported sharing pain medications.13 The National Community Pharmacists Association estimates that up to 40% of medications prescribed in the United States go unused,14 and unused prescription medications are rarely either stored safely or securely or disposed of properly.15–17 Although patients prescribed opioids may have legitimate reasons for choosing not to take their medication,18,19 the choice to keep but not to take the medication creates a potential source for diversion. This is especially concerning as large percentages of patients prescribed opioids do not take all the medications they receive,20,21 and medications for pain are among the most common medications borrowed from others or shared with them.22,23 Although other studies have looked at the source of opioids from the perspective of the person who is using the medication nonmedically, almost no research has examined the attitudes and behaviors of those who receive opioids legitimately regarding the use and disposal of unused opioid medications.24 This paper presents a qualitative analysis of the responses of a sample of Veterans who received an opioid prescription to questions about what they did with any remaining medication.
METHODS Participants The current study uses existing data collected as part of a study to identify risk factors for misuse of opioid Clin J Pain
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medications. Participants were 191 US Veterans receiving care at the Veterans Affairs Palo Alto Health Care System (VAPAHCS). Inclusion criteria for the study were receipt and use of an opioid prescription in the 12 months before recruitment and ability to provide written informed consent. Exclusion criteria were a diagnosis of metastatic cancer or failure to use the prescribed opioid medication. Participants were recruited through primary care providers at several locations within the VAPAHCS including Palo Alto, Menlo Park, Livermore, San Jose, Monterey, Modesto, Stockton, and Sonora.
Procedure Data from the VA regional Corporate Data Warehouse identified approximately 9000 eligible patients. The procedures for identifying and recruiting patients for this study and for conducting study assessments have been published in detail elsewhere.18 In brief, primary care providers chose to invite 1359 eligible patients by sending them letters informing them of their eligibility to participate in the study. We prioritized recruiting patients from the eligible population of approximately 9000 patients who had the following known risk criteria for problematic opioid use in the prior 12 months: (1) a VAPAHCS emergency room visit, (2) a diagnosis of a mental health condition or (3) substance use disorder (SUD) assigned at a clinical encounter, or (4) at least 1 visit to the VAPAHCS pain clinic. Some patients met more than one of these criteria. Each of these risk criteria were identified from the electronic medical record (EMR). Mental health conditions and SUDs in this sample were defined for the study by the International Classification of Diseases, 9th Revision Clinical Modification (ICD-9-CM), code range 290-311.25 For purposes of identifying eligible patients, these risk criteria were identified in the EMR for potential participants for the 12 months before the data pull. For purposes of analysis of actual participants, these risk criteria were all identified in the EMR as present at clinical encounters in the 12 months before the participant’s study participation. Diagnosis codes indicated that participants had the following mental health conditions: anxiety, bipolar disorder, depression, drug induced mental disorders, panic disorder, personality disorder, posttraumatic stress disorder, psychosis, schizophrenia, and suicidality. Participants had the following SUDs: alcohol dependence, alcohol abuse, amphetamine abuse, barbituate dependence, cannabis abuse, cannabis dependence, cocaine abuse, cocaine dependence, opioid abuse, tobacco use, other specific drug dependence, combinations of drug dependence excluding opioids, and unspecified drug dependence. Participants were assigned an average of 5 ICD-9 codes for mental health and/or SUDs at encounters over the 12 months before study participation compared with 3 assigned to the eligible population over the 12 months before the data pull for sample identification (the same general condition, such as depression, may have been coded multiple times). Eighteen percent of the 1359 invited patients responded to the letter (n = 227) and a total of 191 participants completed the study. Out of 191 participants, 83% met one or more of the known risk criteria listed above. The first author and an experienced research assistant completed 169 and 22 of the clinical interviews, respectively, and information was also extracted from the patients’ medical record about the type and timing of prescriptions r
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and refills. Participants had a higher average number of prescriptions in the 12 months before sample identification compared with the eligible population (7.9 vs. 6.5). Study participation consisted of a 1-time, B1.5-hour telephone or in-person interview and participants were compensated with a gift certificate. All participants completed IRB-approved consent forms and HIPAA authorization forms. This study and all recruitment materials were approved by the Stanford University Institutional Review Board and the VA Palo Alto Research and Development Committee. A Certificate of Confidentiality was obtained from the National Institute on Drug Abuse.
Measures Data for this paper are primarily from responses to questions on the Prescription Drug Use Questionnaire (PDUQ), a 42-item structured interview developed to guide clinician assessments of prescription medication misuse risk.26 The interview takes approximately 20 to 30 minutes to administer and asks participants a series of questions related to their pain condition(s), patterns of opioid use, social and family factors, family history of pain and substance abuse, and patient substance abuse and psychiatric history. The interviewer-scored PDUQ item that provides our primary data on unused opioids is “Does the patient save/hoard unused medication or have partially unused bottles of medication at home?” Other questions on the PDUQ elicited discussion of issues relevant to diversion and sharing, such as has the patient ever obtained opioids from nonlegal sources, had access to opioids through family or friends, or taken medications prescribed for someone else. Interviewers took detailed notes on participant responses to PDUQ questions that allowed subsequent review of ambiguous responses or responses where the interpretation was context dependent. To ensure consistent PDUQ administration and interpretation, the 2 interviewers met periodically throughout data collection. Interpretation of information from the PDUQ was supplemented by information from the Pain Outcomes Questionnaire, a screening tool primarily for identifying functional impairment due to pain.27 The Pain Outcomes Questionnaire includes questions about patients’ selfreported pain scores and acceptable pain levels and questions about duration of their pain, duration of opioid use, and frequency of opioid use (eg, last period of daily use, length of daily use).
Qualitative Data Analysis All PDUQ notes were reviewed by the first author for the answer to the save/hoard question. When the answer recorded was unclear or unresponsive, other sections of the PDUQ notes were reviewed for relevant information. In the few cases where relevant information was unavailable in the PDUQ notes, information was identified in the EMR about frequency of refills and consistency of the prescription provider. Following accepted qualitative analysis methods,28,29 the first and third author grouped statements into numerous potential categories related to what the participant said he or she did with the medication. After discussion, the initial larger set of categories was collapsed into 4 categories that reflect clinically meaningful types of opioid management and have high relevance for identifying the extent of opioids available for diversion or misuse: no opioid supply because of (1) disposal or (2) running out of the medication, (3) a small supply in the context of an www.clinicalpain.com |
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ongoing prescription, and (4) some supply of unknown quantity. The first and second author coded the data using these 4 categories (8 participants were unable to be coded). After initial training using data from 11 participants, the second author coded the remaining 180 participants in 3 phases each with an increasing number of participants, discussing disagreements with the first author after each phase. For these 180 participants, the coders achieved an initial percent agreement of 75.5% and a Cohen k coefficient of 65.8%. Cohen k coefficient is a conservative measure of interrater agreement for coding of categorical items that takes into account the probability of agreement occurring by chance. Of the 45 disagreements, 30 represented a systematically different interpretation of 2 coding categories. Excluding these 30 cases, the percent agreement was 90% and a Cohen k of 86.3%. Once this systematic difference was clarified, the remaining 15 cases of disagreement were resolved by discussion. Data from the PDUQ about diversion and sharing was similarly analyzed by the third author and a PhD clinical psychologist who extracted all statements from the PDUQ notes about diversion or sharing, broadly defined as any reported use of the participant’s prescribed opioid by another person and any use of a nonprescribed opioid by the participant. The use could be between family members and friends, or with an unknown other, and be an exchange based on emotional ties or for financial reasons. Patients’ self-reported behaviors were coded in 4 nonexclusive categories: (1) the patient illegally diverted his/her opioid to others, (2) the patient’s opioid was stolen, (3) the patient shared his/her opioid with family or friends, and (4) the patient received opioids from family or friends. The distinction between engaging in knowingly illegal activities and sharing medications with known others (which is also illegal) was meaningful to the participants. After jointly coding 10% of the sample (n = 19), coding categories were finalized, and an additional 10% were jointly coded with a percent agreement of 92.1%. Disagreements were resolved by discussion and the clinical psychologist coded the remaining data.
Statistical Analysis We used independent sample t tests and Pearson w2 tests to examine whether there was a significant variation on the 5 demographic factors between those with no opioid medications and those who maintained or saved some opioid medications, and between subjects who did or did not report diversion or sharing of opioid medications (the 8 participants with unclear answers were excluded). The demographic factors were age, ethnicity, sex, being partnered, and years of education. The same tests were conducted to examine whether there was significant variation on the 4 risk criteria for opioid misuse between patients who did or did not maintain or save their opioid medication and between patients who did or did not report engaging in any sharing or diversion.
RESULTS Demographic and Clinical Characteristics of the Sample Participants were 92% male, on average 62.5 years old, and predominantly white (73%). Participants reported pain conditions that ranged from extremely severe and
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chronic (eg, shrapnel throughout the body), to severe but short term (eg, kidney stones), to moderate and chronic (eg, arthritis, neuropathy from diabetes). The length of time that the participants reported experiencing their painful conditions ranged from a few days to >60 years. Sixteen percent of the sample reported pain lasting for 90 consecutive days. Participants received the following opioids: tramadol, codeine, hydrocodone, oxycodone (short-acting and extended release), morphine (short-acting and extended release), methadone, fentanyl, and hydromorphone.
Patterns of Opioid Management A total of 65.4% (n = 125) of patients reported maintaining or saving opioid medication even if they were no longer actively using it to treat a pain problem (Table 1). Only 30.4% (n = 58) of patients reported that they used all of their opioids or that they disposed of extra opioids promptly. Patients who reported that they had an ongoing prescription and always had a small supply received the highest average number of prescriptions in the prior 12 months (11.2). The following are excerpts from PDUQ interview notes in response to the save/hoard question. They are not direct quotes from patients unless placed in quotation marks. Patients who maintain or save some supply from their opioid prescriptions reported several patterns of behavior that are potentially problematic. Example 1: No extras (24.1%; n = 46) [He] doesn’t have any at all. If he has pain he talks to his doctor. This patient (56 y, male) received 2 prescriptions in the prior year, both for 40 tablets of a hydrocodone/ acetaminophen combination. He reported that he used them for 2 months after a painful foot operation and experienced good pain relief. The patient feels comfortable that if he returned to his physician for additional pain relief that he would be accommodated.
TABLE 1. Types of Opioid Management
No opioid medications No extras Dispose of extras Maintain or save opioid medications Small supply, ongoing prescription Some supply, unknown quantity Unclear: type of opioid management could not be determined
r
N = 191 (n [%])
Average Prescriptions (Range, SD)
58 46 12 125
(30.4) (24.1) (6.3) (65.4)
7.1 7.3 (1-30, 6.5) 6.7 (1-15, 5.1) 7.0
41 (21.5)
11.2 (3-30, 7.1)
84 (44.0)
5.0 (1-24, 5.4)
8 (4.2)
10.7 (1-31, 9.1)
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TABLE 2. Patient Demographic Characteristics by Types of Opioid Management
Opioid Management Type (n = 183)
Average age (SD) Non-white (N [%]) Female (N [%]) Married/partnered (N [%]) Average years of education (SD)
No Extras (46)
Dispose of Extras (12)
58.3 14 5 23
63.8 2 0 7
(9.3) (26.9) (33.3) (25.6)
2.5 (14.9)
Small Supply, Ongoing Prescription (41)
(13.4) (3.8) (0) (7.8)
2.3 (14.0)
64.0 15 3 19
2.8 (14.5)
Example 2: Dispose of extras (6.3%; n = 12) No extras. If there are extras he throws them away, he doesn’t mess around with it. This participant (52 y, male) received 13 prescriptions in the prior year, each for 60 tablets of methadone for severe knee pain. He receives adequate pain relief from the methadone which he has used daily for 4 to 5 years. He acknowledges the seriousness of the medication and disposes of extras, but it is unclear whether he disposes of it safely. Example 3: Small supply, ongoing prescription (21.5%; n = 41) Sometimes he uses through the prescription time and has a little extra. He usually comes out close. He waits to reorder until he just has 4-5 days left. Some participants such as this one maintain a small amount of their opioid medication to ensure a continuous supply (the VA refills prescriptions by signature-required Federal Express delivery). This participant (65 y, male) received 30 prescriptions in the prior year, most for a large number of immediate release oxycodone tablets and 240 tablets of sustained release oxycodone. He reports that he has used oxycodone daily for pain since the mid 1990s. Examples 4 to 7: Some supply, unknown quantity (44.0%; n = 84) He saves it “in case I really really need them.” A number of participants reported saving medication “just in case.” This participant (55 y, male) received 3 prescriptions, 1 for a hydrocodone/acetaminophen combination, and a few months later 2 prescriptions on consecutive days from different physicians for oxycodone and a hydrocodone/acetaminophen combination. He reported that he used it intermittently at first then daily for a month. He always has 1 bottle extra in case something happens. For psychological comfort, some participants choose to have opioid medications in reserve. However, for participants such as this one (78 y, male), who receives 180 tablets of a hydrocodone/acetaminophen combination, this means that a large supply of the medication is potentially available to others. He received 13 prescriptions in the prior year, all from the same provider, and reports taking it daily in the afternoon for 3 to 4 years. He saves it until it expires then throws it away. Some participants seemed to accumulate opioids primarily through inattention. This participant (74 y, male) r
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(11.8) (28.8) (20.0) (21.1)
Some Supply, Unknown Quantity (84) 63.6 21 7 41
(12.2) (40.4) (46.7) (45.6)
2.2 (14.3)
P (v2 or t) 0.056 0.435 0.670 0.907
Sample (191)
(2.6) 62.4 (11.7) (2.7) 52 (27.2) (1.5) 15 (7.8) (0.6) 90 (48.7)
0.537 (0.7)
2.4 (14.5)
received 2 prescriptions in the prior year (for oxycodone and codeine with acetaminophen), and reported using it for no more than 1 to 2 days or a week at a time. He had used opioids off and on for 7 to 8 years and more recently used them 3 to 4 months before the interview. Again, it is unclear if he disposes of it safely. He refills when it’s due, but he has 100 now and can get another prescription in 6 days. A final example is from a participant (63 y, male) with a regular prescription (17 in the prior year) who refills the prescription but does not use the medication fully, therefore accumulating a potentially large number of tablets. His prescription is for 150 tablets of a hydrocodone/acetaminophen combination that he reports using for 15 years, but taking as needed not daily. A MANOVA or w2 tests between participants by opioids management type found no significant differences between these 4 groups on 4 demographic factors: ethnicity, sex, being partnered, or years of education. Those who maintained or saved some opioid medications tended to be younger than participants who reported other opioid management patterns (t = 2.6; P = 0.056; Table 2).
Evidence of Nonprescribed Opioid Use A total of 34.0% (n = 65) of the sample reported engaging in behavior that met the definition of diversion or sharing (n = 126; Table 3). The percentage of participants who reported engaging in some kind of sharing with a known other person or receiving medications from a known other person (the most commonly reported behavior) was much higher than the number of participants who reported illegal activities related to obtaining or selling opioids (Table 3). The diversion or sharing behaviors participants described included taking an opioid medication from another person’s prescription “one time” or “very rarely,” occasionally using an opioid from a spouse’s prescription, exchanging their prescribed opioid for a different opioid prescribed to another person, and habitually having others borrow or steal their medication. Some diversion or medication sharing was past behavior or 1 time occurrences. Most participants who reported one of the 4 types of behaviors (illegally diverting their opioid, having their opioid stolen, sharing their opioid with others, and receiving opioids from others) reported only 1 behavior (66.2%; n = 43). An additional 30.8% (n = 20) of participants reported 2 types, and only 3.0% (n = 2) reported 3 of the types of behaviors. www.clinicalpain.com |
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TABLE 3. Types of Opioid Diversion or Sharing
N = 191 (n [%]) No evidence of diversion or sharing Evidence of diversion or sharing Types of diversion or sharing (not mutually exclusive) Participant illegally diverted his/her opioid to others Example: He would sell pills for pot, except in the winter Participant’s opioid was stolen Example: He had a cleaning lady who stole a vicodin bottle and a neighbor who takes them constantly Participant shared his/her opioid with family/ friends Example: He left the vicodin for his sister-in-law to use, it was too strong for him Participant received opioids from family/friends Example: Before he had a prescription, his mom, who was a nurse, would give him pain meds that she had
126 (65.9) 65 (34.0) 12 (18.5)
11 (16.9)
21 (32.3)
45 (69.2)
Using independent sample t tests and Pearson w2 tests, we examined whether there was significant variation on 5 demographic factors between participants who did or did not report diversion or sharing (Table 4). Again, the only significant difference between those who reported engaging in some form of diversion or sharing and those who did not was for average age: those who reported diversion or sharing were significantly more likely to be younger than those who reported none (t = 2.52; P = 0.01).
Risk Factors for Medication Misuse and Opioid Management Type and Reported Diversion or Sharing As stated earlier, the study sample was enriched for participants who met risk criteria for problematic opioid
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use. Accordingly, 70.7% (n = 135) had received at least one diagnosis of a mental health condition, 34.6% (n = 66) received a diagnosis of a SUD excluding tobacco, and an additional 15.7% (n = 30) received only a diagnosis of tobacco use. In Table 5 we present analyses for participants with a mental health diagnosis, SUD patients excluding those whose only SUD diagnosis is for tobacco, and SUD patients including those whose only SUD diagnosis is for tobacco. Using a MANOVA, independent sample t tests, or Pearson w2 tests, we examined whether there was significant variation on these risk criteria between participants by opioid management type (Table 5) and between participants who did or did not report engaging in any sharing or diversion (Table 6). Participants with a SUD diagnosis excluding tobacco are significantly more likely to report that they maintain or save opioid medications (w2 = 8.26; P = 0.04). Neither having a mental health diagnosis or a diagnosis of an SUD including tobacco was significantly associated with opioid management type. Participants with a SUD diagnosis including tobacco were significantly more likely to report diversion or sharing (w2 = 14.18; P < 0.001). Pain clinic visits were rare (only 4 participants) and therefore difficult to interpret its significant association with opioid management type; a pain clinic visit was not significantly associated with reported diversion or sharing (w2 = 0.17; P = 0.684). Emergency room visits were more common, and were significantly associated with having some supply of an unknown quantity of opioids (w2 = 10.31; P = 0.016) but not significantly associated with reported diversion or sharing (w2 = 0.38; P = 0.535).
DISCUSSION Almost two thirds of participants in this study (65.4%) reported that they had some or most of an opioid prescription readily available even if they were not actively using the medication. More than a third of participants (34.0%) also reported engaging in diversion or sharing activities at least once, most often receiving opioids from
TABLE 4. Patient Demographic Characteristics by Types of Opioid Diversion or Sharing
Types of Opioid Diversion or Sharing (n)* No Evidence Evidence of of Diversion or Diversion or Sharing (126) Sharing (65) P (v2 or t) Average age (SD) Non-white (N [%]) Female (N [%]) Married/ partnered (N [%]) Average years of education (SD)
63.8 (12.2)
59.4 (9.8)
0.01 (2.52)
Participant Illegally Diverted His/Her Participant’s Opioid to Others Opioid was (12) Stolen (11) 57.1 (4.1)
Participant Shared His/Her Opioid With Family/ Friends (21)
Participant Received Opioids From Family/ Friends (45)
57.9 (12.1)
62.0 (11.4)
59.0 (9.3)
30 (23.8)
22 (33.8)
0.14 (2.18)
5 (41.7)
4 (36.4)
7 (33.3)
15 (33.3)
10 (7.9)
5 (7.7)
0.95 (0.004)
1 (8.3)
3 (27.3)
1 (4.8)
2 (4.4)
65 (51.6)
28 (43.1)
0.27 (1.24)
6 (50.0)
2 (18.2)
9 (42.8)
23 (51.1)
14.6 (2.5)
14.1 (2.2)
0.17 (1.37)
14.3 (2.1)
14.1 (1.8)
14.2 (2.0)
14.2 (2.2)
*For sample averages see Table 3.
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TABLE 5. Opioid Misuse Risk Factors and Opioid Management Type (n = 183)*
Mental health diagnosis (N [%]) Yes (129) No (54) SUD diagnosis excluding tobacco (N [%]) Yes (63) No (120) SUD diagnosis including tobacco (N [%]) Yes (93) No (90) Pain clinic visits (N [%]) Yes (4) No (179) Emergency room visits (N [%]) Yes (57) No (126)
No Extras (46)
Dispose of Extras (12)
Small Supply, Ongoing Prescription (41)
Some Supply, Unknown Quantity (84)
37 (28.7) 9 (16.7)
9 (7.0) 3 (5.6)
29 (22.5) 12 (22.2)
54 (41.9) 30 (55.6)
0.28 (3.86)
21 (33.3) 25 (20.8)
7 (11.1) 5 (4.2)
13 (20.6) 28 (23.3)
22 (34.9) 62 (51.7)
0.04 (8.26)
28 (30.1) 18 (20.0)
7 (7.5) 5 (5.6)
21 (22.6) 20 (22.2)
37 (39.8) 47 (52.2)
0.30 (3.67)
0 (0) 46 (25.7)
2 (50) 10 (5.6)
0 (0) 41 (22.9)
2 (50) 82 (45.8)
0.003 (13.73)
14 (24.6) 32 (25.4)
4 (7.0) 8 (6.3)
5 (8.8) 36 (28.6)
34 (59.6) 50 (39.7)
0.016 (10.31)
P (v2)
*Participants whose opioid management type could not be determined (n = 8) are excluded from this analysis. SUD indicates substance use disorder.
family and friends. Being younger was significantly associated with both of these types of behaviors. Interestingly, known risk factors for problematic opioid use including emergency room visits and having a mental health diagnosis alone were not significantly associated with either maintaining or saving opioids or diverting or sharing. A recent nontobacco SUD diagnosis was significantly associated with maintaining or saving opioids and participants with a SUD diagnosis including tobacco were significantly more likely to report diversion or sharing. This study has a number of important limitations. First, there are several concerns about the representativeness of the sample. The participation rate was relatively low, the sample is heavily biased toward male patients, patients are all US Veterans, and the number of patients with risk factors for medication misuse was higher than in the general population. However, a comparison between participating patients (n = 191) and eligible participants (B9000) found only small differences between the groups by average age (62.5 vs. 63.8 y) and percent female (8% vs. 7%), indicating that our sample is generally representative of the eligible Veteran population. Participants had experienced a wide range of conditions and medications and their absolute rate of emergency room visits and pain clinic visits were low. Our findings about rates of opioid saving also closely parallel the results of a survey of Utah residents.24 Other limitations are inherent to a qualitative study. We relied on participants’ retrospective self-report which is subject to response bias and memory lapses. The data were collected at one point in time and patient’s opioid management patterns are likely dynamic and change as their health and life circumstances change. Unless selfreported, it is also unknown whether these Veteran patients are receiving opioids from non-VA sources. Although all data in this paper were coded by 2 coders, ultimately there is subjectivity in categorizing participants’ opioid management patterns, as there would be if this classification was done by clinicians. r
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The impact of unused prescribed opioids on pain management and disability is largely unknown. However, Shrank30 summarized the state of knowledge as “nonmedical use of opiates is the best-documented consequence of holding onto leftover medications.” Given the existing evidence that legitimate prescriptions are one of the leading sources of opioids used by people with addiction or
TABLE 6. Opioid Misuse Risk Factors and Reported Diversion or Sharing (n = 191)
No Evidence of Evidence of Diversion Diversion or Sharing or Sharing (65) (126) Mental health diagnosis (N [%]) Yes (135) No (56) SUD diagnosis excluding tobacco (N [%]) Yes (66) No (125) SUD diagnosis including tobacco (N [%]) Yes (96) No (95) Pain clinic visits (N [%]) Yes (4) No (187) Emergency room visits (N [%]) Yes (62) No (129)
P (v2)
51 (37.8) 14 (25.0)
84 (62.2) 42 (75.0)
0.09 (2.88)
28 (42.4) 37 (29.6)
38 (57.6) 88 (70.4)
0.08 (3.16)
45 (46.9) 20 (21.1)
51 (53.1) 75 (78.9)
1 (25.0) 64 (34.2)
3 (75.0) 120 (64.1)
0.684 (0.17)
23 (37.1) 42 (32.5)
39 (62.9) 87 (67.4)
0.535 (0.38)
< 0.001 (14.18)
SUD indicates substance use disorder.
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substance use problems, the findings of this study present providers with the challenge of working to limit the supply of opioid medications available for diversion while not undertreating patients’ pain. The larger literature on how patients use opioid medications suggests considerable cause for caution on the part of prescribers separate from the risk of a patient over-using the opioid. A recent study found that 39.2% of respondents had prescription pain medications in their possession and >80% had never received information about proper disposal of their prescription medications.17 Multiple research studies on opioid nonadherence also document that patients receive opioid medications and subsequently do not take them for a variety of reasons.15,17,18,31–33 For example, Fishman et al34 lists 16 reasons why patients might under-use opioid medications such as fear of addiction, side effects, and forgetfulness. Gunnarsdottir et al35 identifies 4 factors endorsed by patients as barriers to using analgesics including fatalism about pain and beliefs about the harmful effects of pain medications. The findings of this paper reinforce the growing evidence that while concern about over-use and abuse of opioids is legitimate, retention and failure to dispose of unused opioids is common. It also lays out some of the specific reasons and patterns of behavior presented by patients when asked to describe their medication management choices. Providers can take a number of concrete clinical actions to reduce the risk to the patient and others from prescribed opioids,36 including some identified in the “universal precautions” approach.37,38 Rather than reiterate these precautions here, we will focus on clinical actions that may be most relevant to improving patients’ understanding and behaviors. Implementation of these clinical actions will depend on the individual prescriber’s local context (eg, state-specific opioid prescribing policies39) and practice characteristics. Engage in clear, open, 2-way communication about opioid therapy and nonmedication options for pain management. This can help identify patients who may be reluctant to use opioids or who are concerned about using them. These patients can be offered nonopioid pain management options such as physical therapy or psychosocial treatments for pain. Counsel patients prescribed opioids (especially patients with a recent SUD diagnosis) not only about the risk of overdose to themselves but also about the risk to others with whom they might share their medication. In addition, providers can inform their patients that federal law prohibits sharing prescription medications with others, including family or friends. Offer patients initial prescriptions that are calibrated to their expected length of use (for acute pain) or appropriate for an adequate trial (if initiating opioids for chronic pain). Simultaneously, reassure patients that they will receive additional medication if needed. Just as initiating and maintaining a patient on an opioid medication is a process, educating patients about appropriate management of that opioid medication is a process. No 1-time discussion about the topic or inflexible policy is likely to be effective, as patients may have misperceptions or a lack of understanding about opioid medications.40 Changing patient behavior will likely require an approach tailored to the specific patient’s situation and repeated interactions around the topic of medication management and disposal, especially for patients with complex medication conditions requiring multiple medications and given the changing regulatory
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environment. An opioid trial with a patient or an ongoing opioid prescription for chronic pain both require individualized action by the provider, and the educational process about safe medication management must similarly be tailored to the patient based on clinical judgment and local laws and regulations. An essential part of this educational process is to have information easily accessible about options for safe disposal of opioid medications.36 The Responsible Drug Disposal Act of 2010 (http://www.govtrack.us/congress/bills/111/ s3397) facilitates drug take-back programs and should make it easier and more transparent for all patients to dispose of unused or unneeded medications in a safe, appropriate way. The US Food and Drug Administration41 and US Environmental Protection Agency42 have useful information available on medication disposal. The 3 main approaches to safe medication disposal are using medication disposal programs, disposing of medications in household trash after following specific procedures, and flushing some medications down the sink or toilet. Providers should also partner as closely as possible with the pharmacies filling the patients’ prescriptions. Pharmacists can reinforce information about safe medication disposal and incorporate this information into their routine patient counseling and educational handouts. If a prescriber suspect that a patient’s use of opioids may be problematic, there are additional actions he or she can consider: Use a validated screener for prescription medication misuse in all patients, but particularly patients with SUDs, the risk factor most commonly found to be associated with problematic opioid use.43 For example, the Current Opioid Misuse Measure44 is designed to help detect potentially problematic behavior with medications by chronic pain patients. Use an opioid pain care agreement. Multiple examples are available free online. Access state’s prescription drug monitoring program database to identify patients receiving opioids from multiple providers. As Hall et al45 states: “Clinicians have a critical role to play in preventing the diversion of prescription drugs.” Health care providers are beginning to acknowledge that they may be over-prescribing pain medications46 and supplementing the supply of opioids available to addicts.47 Fortunately, clinicians have a number of tools available to reduce unnecessary opioid prescribing and improve the efficacy of pain management.36,48 Of course, patients must take responsibility for communicating with their providers about their preference and intention to use opioid medication. Policy makers also owe the public clear information about options for safe opioid disposal, and owe health care providers and pharmacists streamlined regulatory guidance that facilitates this disposal. Reducing the flow of opioids available for diversion and abuse begins with the provider thinking about the lifecycle of the prescription in the patients’ hands.
ACKNOWLEDGMENTS The authors thank the contributions of Dr Michelle A. Skinner (PhD, San Mateo, CA) with data analysis for this paper and Ann Combs (MPH, Center for Innovation to Implementation, Veterans Affairs - Palo Alto Health Care System, Menlo Park, CA) for her assistance with the original interviews. r
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REFERENCES 1. Kuehn BM. Opioid prescriptions soar: increase in legitimate use as well as abuse. JAMA. 2007;297:249–251. 2. Paulozzi LJ, Jones CM, Mack KA, et al. Centers for Disease Control and Prevention (CDC) Vital Signs: overdoses of prescription opioid pain relievers—United States, 1999-2008. MMWR Surveill Summ. 2011;60:1487–1492. 3. Food and Drug Administration. Joint meeting of the anesthetic and life support drugs advisory committee and the drug safety and risk management advisory committee. 2010. Available at: http://www.fda.gov/downloads/Advisory Committees/CommitteesMeetingMaterials/Drugs/AnestheticAnd LifeSupportDrugsAdvisoryCommittee/UCM217510.pdf. Accessed June 16, 2013. 4. DeNoon DJ. The 10 most prescribed drugs: most-prescribed drug list differs from list of drugs with biggest market share. 2011. Available at: http://www.webmd.com/news/20110420/ the-10-most-prescribed-drugs. Accessed June 16, 2013. 5. Paulozzi LJ, Budnitz DS, Xi Y. Increasing deaths from opioid analgesics in the United States. Pharmacoepidemiol Drug Saf. 2006;15:618–627. 6. Manchikanti L, Singh A. Therapeutic opioids: a ten-year perspective on the complexities and complications of the escalating use, abuse, and nonmedical use of opioids. Pain Physician. 2008;11(suppl 2):S63–S88. 7. Cai R, Crane E, Poneleit K, et al. Emergency department visits involving nonmedical use of selected prescription drugs— United States, 2004-2008. CDC Morb Mortal Wkly Rep. 2010;59:705–709. 8. Maxwell JC. The prescription drug epidemic in the United States: a perfect storm. Drug Alcohol Rev. 2011;30:264–270. 9. Substance Abuse and Mental Health Services Administration. Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. NSDUH Series H-44, HHS Publication No. (SMA) 12-4713. Rockville, MD: Substance Abuse and Mental Health Services Administration. 2012. Available at: http://www.samhsa.gov/data/NSDUH/ 2k11Results/NSDUHresults2011.pdf. Accessed June 18, 2013. 10. Inciardi JA, Surratt HL, Cicero TJ, et al. Prescription opioid abuse and diversion in an urban community: the results of an ultra rapid assessment. Pain Med. 2009;10:537–548. 11. McCabe SE, Cranford JA, Boyd CJ, et al. Motives, diversion and routes of administration associated with nonmedical use of prescription opioids. Addict Behav. 2007;32:562–575. 12. Davis WR, Johnson BD. Prescription opioid use, misuse, and diversion among street drug users in New York City. Drug and Alcohol Dependence. 2008;92:267–276. 13. Goebel JR, Compton P, Zubkoff L, et al. Prescription sharing, alcohol use, and street drug use to manage pain among veterans. J Pain Symptom Manage. 2011;41:848–858. 14. National Community Pharmacists Association. 800 Community pharmacies launch initiative for safe disposal of unused patient medications. 2010. Available at: http://www.ncpanet. org/index.php/news-releases/144-800-community-pharmacieslaunch-initiative-for-safe-disposal-of-unused-patient-medications. Accessed August 6, 2012. 15. Tanabe P, Paice JA, Stancati J, et al. How do emergency department patients store and dispose of opioids after discharge? A pilot study. J Emerg Nurs. 2012;38:273–279. 16. Seehusen DA, Edwards J. Patient practices and beliefs concerning disposal of medications. J Am Board Fam Med. 2006;19:542–547. 17. Wieczorkiewicz SM, Kassamali Z, Danziger LH. Behind closed doors: medication storage and disposal in the home. Ann Pharmacother. 2013;47:482–489. 18. Lewis ET, Combs A, Trafton JA. Reasons for under-use of prescribed opioids by patients in pain. Pain Med. 2010;11:861–871. 19. Pound P, Britten N, Morgan M, et al. Resisting medicines: a synthesis of qualitative studies of medicine taking. Soc Sci Med. 2005;61:133–155. r
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20. Broekmans S, Dobbels F, Milisen K, et al. Medication adherence in patients with chronic non-malignant pain: Is there a problem? Eur J Pain. 2009;13:115–123. 21. Broekmans S, Dobbels F, Milisen K, et al. Pharmacologic pain treatment in a multidisciplinary pain center: do patients adhere to the prescription of the physician? Clin J Pain. 2010;26:81–86. 22. Ward L, Patel NM, Hanlon A, et al. Prescription medication borrowing among adult patients at an urban medical center. J Urban Health. 2011;88:997–1014. 23. Petersen EE, Rasmussen SA, Daniel KL, et al. Prescription medication borrowing and sharing among women of reproductive age. J Womens Health (Larchmt). 2008;17: 1073–1080. 24. Porucznik CA, Sauer BC, Johnson EM, et al. Adult use of prescription opioid pain medications—Utah, 2008. CDC Morb Mortal Wkly Rep. 2010;59:153–157. 25. Buck CJ. 2010 ICD-9-CM for Hospitals, Volumes 1, 2, and 3, Professional Edition. Maryland Heights, MO: Saunders Elsevier; 2010. Available at: http://www.amazon.com/ICD-9CM-Hospitals-Volumes-Professional-Spiral/dp/1437702074/ref =sr_1_4?s=books&ie=UTF8&qid=1380665973&sr=1-4&key words=Carol+Buck+and+ICD-9+2010. 26. Compton P, Darakjian J, Miotto K. Screening for addiction in patients with chronic pain and “problematic” substance use: evaluation of a pilot assessment tool. J Pain Symptom Manage. 1998;16:355–363. 27. Clark ME, Gironda RJ, Young RW. Development and validation of the Pain Outcomes Questionnaire-VA. J Rehabil Res Dev. 2003;40:381–395. 28. Green J, Thorogood N. Qualitative Methods for Health Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 2009. 29. Miles MB, Huberman AM. Qualitative Data Analysis: An Expanded Sourcebook. 2nd ed. Thousand Oaks, CA: Sage Publications; 1994. 30. Shrank WH. Our bulging medicine cabinets—the other side of medication nonadherence. N Engl J Med. 2011;364:1591–1593. 31. Manchikanti L, Damron KS, McManus CD, et al. Patterns of illicit drug use and opioid abuse in patients with chronic pain at initial evaluation: a prospective, observational study. Pain Physician. 2004;7:431–437. 32. Manchikanti L, Manchukonda R, Pampati V, et al. Evaluation of abuse of prescription and illicit drugs in chronic pain patients receiving short-acting (hydrocodone) or long-acting (methadone) opioids. Pain Physician. 2005;8:257–261. 33. Couto JE, Romney MC, Leider HL, et al. High rates of inappropriate drug use in the chronic pain population. Popul Health Manag. 2009;12:185–190. 34. Fishman S, Wilsey B, Yang J, et al. Adherence monitoring and drug surveillance in chronic opioid therapy. J Pain Symptom Manage. 2000;20:293–307. 35. Gunnarsdottir S, Donovan HS, Serlin RC, et al. Patientrelated barriers to pain management: the Barriers Questionnaire II (BQ-II). Pain. 2002;99:385–396. 36. American College of Preventive Medicine. Use, abuse, misuse, and disposal of prescription pain medication time tool. 2011. Available at: http://www.acpm.org/?UseAbuseRxClinRef. Accessed June 20, 2013. 37. Gourlay D, Heit HA, Almahrezi A. Universal precautions in pain medicine: a rational approach to the treatment of chronic pain. Pain Med. 2005;6:107–112. 38. Manchikanti L, Atluri S, Trescot AM, et al. Monitoring opioid adherence in chronic pain patients: tools, techniques, and utility. Pain Physician. 2008;11(suppl):S155–S180. 39. Medscape. State-by-State Opioid Prescribing Policies. Available at: http://www.medscape.com/resource/pain/opioidpolicies. Accessed June 19, 2013. 40. Mangione MP, Crowley-Matoka M. Improving pain management communication: how patients understand the terms “opioid” and “narcotic”. J Gen Intern Med. 2008;23:1336–1338. 41. US Food and Drug Administration. Disposal of unused medicines: what you should know. Available at: http://www. fda.gov/Drugs/ResourcesForYou/Consumers/BuyingUsing
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MedicineSafely/EnsuringSafeUseofMedicine/SafeDisposalof Medicines/ucm186187.htm. Accessed June 19, 2013. 42. US Environmental Protection Agency. How to dispose of medicines properly. Available at: http://water.epa.gov/scitech/ swguidance/ppcp/upload/ppcpflyer.pdf. Accessed June 19, 2013. 43. Chou R, Fanciullo GJ, Fine PG, et al. Clinical guidelines for the use of chronic opioid therapy in chronic noncancer pain. J Pain. 2009;10:113–130. 44. Butler S, Budman SH, Fanciullo GJ, et al. Cross validation of the Current Opioid Misuse Measure to monitor chronic pain patients on opioid therapy. Clin J Pain. 2010;26:770–776.
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45. Hall A, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA. 2008;300:2613–2620. 46. Bates C, Laciak R, Southwick A, et al. Overprescription of postoperative narcotics: a look at postoperative pain medication delivery, consumption and disposal in urological practice. J Urol. 2011;185:551–555. 47. McLellan AT, Turner BJ. Prescription opioids, overdose deaths, and physician responsibility. JAMA. 2008;300:2672–2673. 48. Volkow ND, McLellan TA. Curtailing diversion and abuse of opioid analgesics without jeopardizing pain treatment. JAMA. 2011;305:1346–1347.
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What Do Patients Do With Unused Opioid Medications? Eleanor T. Lewis, PhD,* Michael A. Cucciare, PhD,wz and Jodie A. Trafton, PhD*y
Objectives: The volume of opioid medications being prescribed in the United States is increasing rapidly. Problems associated with the misuse of opioid medications are also increasing, in part because of medication diversion from legitimate prescriptions. However, little is known about what patients do with any unused opioid medications. This paper uses a qualitative analysis of patients’ self-report of medication storage and retention habits to begin to address this gap. Methods: We analyzed responses to the Prescription Drug Use Questionnaire in conjunction with other data on prescription opioid use in a sample of 191 Veteran patients (83% of whom had a preexisting factor associated with higher rates of opioid misuse) who received one or more opioid prescriptions in the previous 12 months. Results: Only 6.3% of participants disposed of extra medications and 24.1% reported having no extra opioids. A total of 65.4% of participants reported retaining some or all opioids even if they ceased taking the medication, and some participants accumulated large amounts of medication. A total of 34.0% of participants described engaging in sharing or diversion of opioids at least once, most often receiving them from a family member or a friend. Discussion: A majority of patients retain unused opioids, and medication sharing is common. Interventions to improve monitoring of patient experience with opioid medication, educate patients about the dangers of opioid use by nonprescribed others, and increase information about medication disposal options could decrease the supply of opioid medications available for misuse. Key Words: pain, medication adherence, qualitative research, patient preferences
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T
he volume of opioid medications prescribed, sold, and consumed in the United States has been increasing rapidly for years.1 By 2010 opioid medication sales were 4
Received for publication February 13, 2013; revised October 9, 2013; accepted August 13, 2013. From the *Center for Innovation to Implementation, Veterans Affairs—Palo Alto Health Care System, Menlo Park; yDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA; wCenter for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Healthcare System; and zDepartment of Psychiatry and Behavioral Sciences, University of Arkansas for Medical Sciences, Little Rock, AR. Funded by RRP 07-316, “Validation of computerized risk assessment for prescription opioid abuse,” a grant awarded by the Department of Veterans’ Affairs (VA) Health Services Research and Development program (HSR&D) and the Quality Enhancement Research Initiative, Washington, DC. Additional support came from Grant # TRX 04-402 and Grant # IMA 04-156 from VA HSR&D, and by a Career Development Award-2 (CDA 08-004) to M.A.C. awarded by the VA HSR&D. The views expressed are those of the authors and not of the Department of Veterans Affairs. The authors declare no conflict of interest. Reprints: Eleanor T. Lewis, PhD, Center for Innovation to Implementation, Veterans Affairs—Palo Alto Health Care System, 795 Willow Road (152-MPD) Menlo Park, CA 94025 (e-mail: [email protected]). Copyright r 2013 by Lippincott Williams & Wilkins
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times the sales in 1999.2 In 2009 there were approximately 257 million prescriptions for opioids dispensed3 and in 2010 the most common medication prescribed in the United States was hydrocodone (131.2 million prescriptions).4 Increased prescription of opioid medications to treat pain has been paralleled by a large and well-documented increase in prescription opioid-related problems, including misuse, abuse, accidental poisoning, fatal and nonfatal overdoses, emergency department visits, and litigation against physicians.5–8 Opioid analgesics are now the most commonly misused prescription medications in the United States.9 Existing evidence suggests that a primary source of pain medications for people who misuse and abuse them is legitimate prescriptions.10 In the 2011 National Survey on Drug Use and Health,9 70.8% of those who used a prescription medication nonmedically obtained the medication from a friend or relative (with or without their knowledge), and an additional 18.1% received the medication from a single provider. Surveys of college-age students found that among those who used prescription opioids for nonmedical reasons a third reported their source for the opioid was a friend, and only slightly fewer reported the source was a parent.11 Similarly, a survey of people who abuse street drugs found that 37% reported family members or friends were sources of opioids.12 In a Veteran population with pain, 16.3% reported sharing pain medications.13 The National Community Pharmacists Association estimates that up to 40% of medications prescribed in the United States go unused,14 and unused prescription medications are rarely either stored safely or securely or disposed of properly.15–17 Although patients prescribed opioids may have legitimate reasons for choosing not to take their medication,18,19 the choice to keep but not to take the medication creates a potential source for diversion. This is especially concerning as large percentages of patients prescribed opioids do not take all the medications they receive,20,21 and medications for pain are among the most common medications borrowed from others or shared with them.22,23 Although other studies have looked at the source of opioids from the perspective of the person who is using the medication nonmedically, almost no research has examined the attitudes and behaviors of those who receive opioids legitimately regarding the use and disposal of unused opioid medications.24 This paper presents a qualitative analysis of the responses of a sample of Veterans who received an opioid prescription to questions about what they did with any remaining medication.
METHODS Participants The current study uses existing data collected as part of a study to identify risk factors for misuse of opioid Clin J Pain
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medications. Participants were 191 US Veterans receiving care at the Veterans Affairs Palo Alto Health Care System (VAPAHCS). Inclusion criteria for the study were receipt and use of an opioid prescription in the 12 months before recruitment and ability to provide written informed consent. Exclusion criteria were a diagnosis of metastatic cancer or failure to use the prescribed opioid medication. Participants were recruited through primary care providers at several locations within the VAPAHCS including Palo Alto, Menlo Park, Livermore, San Jose, Monterey, Modesto, Stockton, and Sonora.
Procedure Data from the VA regional Corporate Data Warehouse identified approximately 9000 eligible patients. The procedures for identifying and recruiting patients for this study and for conducting study assessments have been published in detail elsewhere.18 In brief, primary care providers chose to invite 1359 eligible patients by sending them letters informing them of their eligibility to participate in the study. We prioritized recruiting patients from the eligible population of approximately 9000 patients who had the following known risk criteria for problematic opioid use in the prior 12 months: (1) a VAPAHCS emergency room visit, (2) a diagnosis of a mental health condition or (3) substance use disorder (SUD) assigned at a clinical encounter, or (4) at least 1 visit to the VAPAHCS pain clinic. Some patients met more than one of these criteria. Each of these risk criteria were identified from the electronic medical record (EMR). Mental health conditions and SUDs in this sample were defined for the study by the International Classification of Diseases, 9th Revision Clinical Modification (ICD-9-CM), code range 290-311.25 For purposes of identifying eligible patients, these risk criteria were identified in the EMR for potential participants for the 12 months before the data pull. For purposes of analysis of actual participants, these risk criteria were all identified in the EMR as present at clinical encounters in the 12 months before the participant’s study participation. Diagnosis codes indicated that participants had the following mental health conditions: anxiety, bipolar disorder, depression, drug induced mental disorders, panic disorder, personality disorder, posttraumatic stress disorder, psychosis, schizophrenia, and suicidality. Participants had the following SUDs: alcohol dependence, alcohol abuse, amphetamine abuse, barbituate dependence, cannabis abuse, cannabis dependence, cocaine abuse, cocaine dependence, opioid abuse, tobacco use, other specific drug dependence, combinations of drug dependence excluding opioids, and unspecified drug dependence. Participants were assigned an average of 5 ICD-9 codes for mental health and/or SUDs at encounters over the 12 months before study participation compared with 3 assigned to the eligible population over the 12 months before the data pull for sample identification (the same general condition, such as depression, may have been coded multiple times). Eighteen percent of the 1359 invited patients responded to the letter (n = 227) and a total of 191 participants completed the study. Out of 191 participants, 83% met one or more of the known risk criteria listed above. The first author and an experienced research assistant completed 169 and 22 of the clinical interviews, respectively, and information was also extracted from the patients’ medical record about the type and timing of prescriptions r
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and refills. Participants had a higher average number of prescriptions in the 12 months before sample identification compared with the eligible population (7.9 vs. 6.5). Study participation consisted of a 1-time, B1.5-hour telephone or in-person interview and participants were compensated with a gift certificate. All participants completed IRB-approved consent forms and HIPAA authorization forms. This study and all recruitment materials were approved by the Stanford University Institutional Review Board and the VA Palo Alto Research and Development Committee. A Certificate of Confidentiality was obtained from the National Institute on Drug Abuse.
Measures Data for this paper are primarily from responses to questions on the Prescription Drug Use Questionnaire (PDUQ), a 42-item structured interview developed to guide clinician assessments of prescription medication misuse risk.26 The interview takes approximately 20 to 30 minutes to administer and asks participants a series of questions related to their pain condition(s), patterns of opioid use, social and family factors, family history of pain and substance abuse, and patient substance abuse and psychiatric history. The interviewer-scored PDUQ item that provides our primary data on unused opioids is “Does the patient save/hoard unused medication or have partially unused bottles of medication at home?” Other questions on the PDUQ elicited discussion of issues relevant to diversion and sharing, such as has the patient ever obtained opioids from nonlegal sources, had access to opioids through family or friends, or taken medications prescribed for someone else. Interviewers took detailed notes on participant responses to PDUQ questions that allowed subsequent review of ambiguous responses or responses where the interpretation was context dependent. To ensure consistent PDUQ administration and interpretation, the 2 interviewers met periodically throughout data collection. Interpretation of information from the PDUQ was supplemented by information from the Pain Outcomes Questionnaire, a screening tool primarily for identifying functional impairment due to pain.27 The Pain Outcomes Questionnaire includes questions about patients’ selfreported pain scores and acceptable pain levels and questions about duration of their pain, duration of opioid use, and frequency of opioid use (eg, last period of daily use, length of daily use).
Qualitative Data Analysis All PDUQ notes were reviewed by the first author for the answer to the save/hoard question. When the answer recorded was unclear or unresponsive, other sections of the PDUQ notes were reviewed for relevant information. In the few cases where relevant information was unavailable in the PDUQ notes, information was identified in the EMR about frequency of refills and consistency of the prescription provider. Following accepted qualitative analysis methods,28,29 the first and third author grouped statements into numerous potential categories related to what the participant said he or she did with the medication. After discussion, the initial larger set of categories was collapsed into 4 categories that reflect clinically meaningful types of opioid management and have high relevance for identifying the extent of opioids available for diversion or misuse: no opioid supply because of (1) disposal or (2) running out of the medication, (3) a small supply in the context of an www.clinicalpain.com |
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ongoing prescription, and (4) some supply of unknown quantity. The first and second author coded the data using these 4 categories (8 participants were unable to be coded). After initial training using data from 11 participants, the second author coded the remaining 180 participants in 3 phases each with an increasing number of participants, discussing disagreements with the first author after each phase. For these 180 participants, the coders achieved an initial percent agreement of 75.5% and a Cohen k coefficient of 65.8%. Cohen k coefficient is a conservative measure of interrater agreement for coding of categorical items that takes into account the probability of agreement occurring by chance. Of the 45 disagreements, 30 represented a systematically different interpretation of 2 coding categories. Excluding these 30 cases, the percent agreement was 90% and a Cohen k of 86.3%. Once this systematic difference was clarified, the remaining 15 cases of disagreement were resolved by discussion. Data from the PDUQ about diversion and sharing was similarly analyzed by the third author and a PhD clinical psychologist who extracted all statements from the PDUQ notes about diversion or sharing, broadly defined as any reported use of the participant’s prescribed opioid by another person and any use of a nonprescribed opioid by the participant. The use could be between family members and friends, or with an unknown other, and be an exchange based on emotional ties or for financial reasons. Patients’ self-reported behaviors were coded in 4 nonexclusive categories: (1) the patient illegally diverted his/her opioid to others, (2) the patient’s opioid was stolen, (3) the patient shared his/her opioid with family or friends, and (4) the patient received opioids from family or friends. The distinction between engaging in knowingly illegal activities and sharing medications with known others (which is also illegal) was meaningful to the participants. After jointly coding 10% of the sample (n = 19), coding categories were finalized, and an additional 10% were jointly coded with a percent agreement of 92.1%. Disagreements were resolved by discussion and the clinical psychologist coded the remaining data.
Statistical Analysis We used independent sample t tests and Pearson w2 tests to examine whether there was a significant variation on the 5 demographic factors between those with no opioid medications and those who maintained or saved some opioid medications, and between subjects who did or did not report diversion or sharing of opioid medications (the 8 participants with unclear answers were excluded). The demographic factors were age, ethnicity, sex, being partnered, and years of education. The same tests were conducted to examine whether there was significant variation on the 4 risk criteria for opioid misuse between patients who did or did not maintain or save their opioid medication and between patients who did or did not report engaging in any sharing or diversion.
RESULTS Demographic and Clinical Characteristics of the Sample Participants were 92% male, on average 62.5 years old, and predominantly white (73%). Participants reported pain conditions that ranged from extremely severe and
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chronic (eg, shrapnel throughout the body), to severe but short term (eg, kidney stones), to moderate and chronic (eg, arthritis, neuropathy from diabetes). The length of time that the participants reported experiencing their painful conditions ranged from a few days to >60 years. Sixteen percent of the sample reported pain lasting for 90 consecutive days. Participants received the following opioids: tramadol, codeine, hydrocodone, oxycodone (short-acting and extended release), morphine (short-acting and extended release), methadone, fentanyl, and hydromorphone.
Patterns of Opioid Management A total of 65.4% (n = 125) of patients reported maintaining or saving opioid medication even if they were no longer actively using it to treat a pain problem (Table 1). Only 30.4% (n = 58) of patients reported that they used all of their opioids or that they disposed of extra opioids promptly. Patients who reported that they had an ongoing prescription and always had a small supply received the highest average number of prescriptions in the prior 12 months (11.2). The following are excerpts from PDUQ interview notes in response to the save/hoard question. They are not direct quotes from patients unless placed in quotation marks. Patients who maintain or save some supply from their opioid prescriptions reported several patterns of behavior that are potentially problematic. Example 1: No extras (24.1%; n = 46) [He] doesn’t have any at all. If he has pain he talks to his doctor. This patient (56 y, male) received 2 prescriptions in the prior year, both for 40 tablets of a hydrocodone/ acetaminophen combination. He reported that he used them for 2 months after a painful foot operation and experienced good pain relief. The patient feels comfortable that if he returned to his physician for additional pain relief that he would be accommodated.
TABLE 1. Types of Opioid Management
No opioid medications No extras Dispose of extras Maintain or save opioid medications Small supply, ongoing prescription Some supply, unknown quantity Unclear: type of opioid management could not be determined
r
N = 191 (n [%])
Average Prescriptions (Range, SD)
58 46 12 125
(30.4) (24.1) (6.3) (65.4)
7.1 7.3 (1-30, 6.5) 6.7 (1-15, 5.1) 7.0
41 (21.5)
11.2 (3-30, 7.1)
84 (44.0)
5.0 (1-24, 5.4)
8 (4.2)
10.7 (1-31, 9.1)
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TABLE 2. Patient Demographic Characteristics by Types of Opioid Management
Opioid Management Type (n = 183)
Average age (SD) Non-white (N [%]) Female (N [%]) Married/partnered (N [%]) Average years of education (SD)
No Extras (46)
Dispose of Extras (12)
58.3 14 5 23
63.8 2 0 7
(9.3) (26.9) (33.3) (25.6)
2.5 (14.9)
Small Supply, Ongoing Prescription (41)
(13.4) (3.8) (0) (7.8)
2.3 (14.0)
64.0 15 3 19
2.8 (14.5)
Example 2: Dispose of extras (6.3%; n = 12) No extras. If there are extras he throws them away, he doesn’t mess around with it. This participant (52 y, male) received 13 prescriptions in the prior year, each for 60 tablets of methadone for severe knee pain. He receives adequate pain relief from the methadone which he has used daily for 4 to 5 years. He acknowledges the seriousness of the medication and disposes of extras, but it is unclear whether he disposes of it safely. Example 3: Small supply, ongoing prescription (21.5%; n = 41) Sometimes he uses through the prescription time and has a little extra. He usually comes out close. He waits to reorder until he just has 4-5 days left. Some participants such as this one maintain a small amount of their opioid medication to ensure a continuous supply (the VA refills prescriptions by signature-required Federal Express delivery). This participant (65 y, male) received 30 prescriptions in the prior year, most for a large number of immediate release oxycodone tablets and 240 tablets of sustained release oxycodone. He reports that he has used oxycodone daily for pain since the mid 1990s. Examples 4 to 7: Some supply, unknown quantity (44.0%; n = 84) He saves it “in case I really really need them.” A number of participants reported saving medication “just in case.” This participant (55 y, male) received 3 prescriptions, 1 for a hydrocodone/acetaminophen combination, and a few months later 2 prescriptions on consecutive days from different physicians for oxycodone and a hydrocodone/acetaminophen combination. He reported that he used it intermittently at first then daily for a month. He always has 1 bottle extra in case something happens. For psychological comfort, some participants choose to have opioid medications in reserve. However, for participants such as this one (78 y, male), who receives 180 tablets of a hydrocodone/acetaminophen combination, this means that a large supply of the medication is potentially available to others. He received 13 prescriptions in the prior year, all from the same provider, and reports taking it daily in the afternoon for 3 to 4 years. He saves it until it expires then throws it away. Some participants seemed to accumulate opioids primarily through inattention. This participant (74 y, male) r
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(11.8) (28.8) (20.0) (21.1)
Some Supply, Unknown Quantity (84) 63.6 21 7 41
(12.2) (40.4) (46.7) (45.6)
2.2 (14.3)
P (v2 or t) 0.056 0.435 0.670 0.907
Sample (191)
(2.6) 62.4 (11.7) (2.7) 52 (27.2) (1.5) 15 (7.8) (0.6) 90 (48.7)
0.537 (0.7)
2.4 (14.5)
received 2 prescriptions in the prior year (for oxycodone and codeine with acetaminophen), and reported using it for no more than 1 to 2 days or a week at a time. He had used opioids off and on for 7 to 8 years and more recently used them 3 to 4 months before the interview. Again, it is unclear if he disposes of it safely. He refills when it’s due, but he has 100 now and can get another prescription in 6 days. A final example is from a participant (63 y, male) with a regular prescription (17 in the prior year) who refills the prescription but does not use the medication fully, therefore accumulating a potentially large number of tablets. His prescription is for 150 tablets of a hydrocodone/acetaminophen combination that he reports using for 15 years, but taking as needed not daily. A MANOVA or w2 tests between participants by opioids management type found no significant differences between these 4 groups on 4 demographic factors: ethnicity, sex, being partnered, or years of education. Those who maintained or saved some opioid medications tended to be younger than participants who reported other opioid management patterns (t = 2.6; P = 0.056; Table 2).
Evidence of Nonprescribed Opioid Use A total of 34.0% (n = 65) of the sample reported engaging in behavior that met the definition of diversion or sharing (n = 126; Table 3). The percentage of participants who reported engaging in some kind of sharing with a known other person or receiving medications from a known other person (the most commonly reported behavior) was much higher than the number of participants who reported illegal activities related to obtaining or selling opioids (Table 3). The diversion or sharing behaviors participants described included taking an opioid medication from another person’s prescription “one time” or “very rarely,” occasionally using an opioid from a spouse’s prescription, exchanging their prescribed opioid for a different opioid prescribed to another person, and habitually having others borrow or steal their medication. Some diversion or medication sharing was past behavior or 1 time occurrences. Most participants who reported one of the 4 types of behaviors (illegally diverting their opioid, having their opioid stolen, sharing their opioid with others, and receiving opioids from others) reported only 1 behavior (66.2%; n = 43). An additional 30.8% (n = 20) of participants reported 2 types, and only 3.0% (n = 2) reported 3 of the types of behaviors. www.clinicalpain.com |
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TABLE 3. Types of Opioid Diversion or Sharing
N = 191 (n [%]) No evidence of diversion or sharing Evidence of diversion or sharing Types of diversion or sharing (not mutually exclusive) Participant illegally diverted his/her opioid to others Example: He would sell pills for pot, except in the winter Participant’s opioid was stolen Example: He had a cleaning lady who stole a vicodin bottle and a neighbor who takes them constantly Participant shared his/her opioid with family/ friends Example: He left the vicodin for his sister-in-law to use, it was too strong for him Participant received opioids from family/friends Example: Before he had a prescription, his mom, who was a nurse, would give him pain meds that she had
126 (65.9) 65 (34.0) 12 (18.5)
11 (16.9)
21 (32.3)
45 (69.2)
Using independent sample t tests and Pearson w2 tests, we examined whether there was significant variation on 5 demographic factors between participants who did or did not report diversion or sharing (Table 4). Again, the only significant difference between those who reported engaging in some form of diversion or sharing and those who did not was for average age: those who reported diversion or sharing were significantly more likely to be younger than those who reported none (t = 2.52; P = 0.01).
Risk Factors for Medication Misuse and Opioid Management Type and Reported Diversion or Sharing As stated earlier, the study sample was enriched for participants who met risk criteria for problematic opioid
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use. Accordingly, 70.7% (n = 135) had received at least one diagnosis of a mental health condition, 34.6% (n = 66) received a diagnosis of a SUD excluding tobacco, and an additional 15.7% (n = 30) received only a diagnosis of tobacco use. In Table 5 we present analyses for participants with a mental health diagnosis, SUD patients excluding those whose only SUD diagnosis is for tobacco, and SUD patients including those whose only SUD diagnosis is for tobacco. Using a MANOVA, independent sample t tests, or Pearson w2 tests, we examined whether there was significant variation on these risk criteria between participants by opioid management type (Table 5) and between participants who did or did not report engaging in any sharing or diversion (Table 6). Participants with a SUD diagnosis excluding tobacco are significantly more likely to report that they maintain or save opioid medications (w2 = 8.26; P = 0.04). Neither having a mental health diagnosis or a diagnosis of an SUD including tobacco was significantly associated with opioid management type. Participants with a SUD diagnosis including tobacco were significantly more likely to report diversion or sharing (w2 = 14.18; P < 0.001). Pain clinic visits were rare (only 4 participants) and therefore difficult to interpret its significant association with opioid management type; a pain clinic visit was not significantly associated with reported diversion or sharing (w2 = 0.17; P = 0.684). Emergency room visits were more common, and were significantly associated with having some supply of an unknown quantity of opioids (w2 = 10.31; P = 0.016) but not significantly associated with reported diversion or sharing (w2 = 0.38; P = 0.535).
DISCUSSION Almost two thirds of participants in this study (65.4%) reported that they had some or most of an opioid prescription readily available even if they were not actively using the medication. More than a third of participants (34.0%) also reported engaging in diversion or sharing activities at least once, most often receiving opioids from
TABLE 4. Patient Demographic Characteristics by Types of Opioid Diversion or Sharing
Types of Opioid Diversion or Sharing (n)* No Evidence Evidence of of Diversion or Diversion or Sharing (126) Sharing (65) P (v2 or t) Average age (SD) Non-white (N [%]) Female (N [%]) Married/ partnered (N [%]) Average years of education (SD)
63.8 (12.2)
59.4 (9.8)
0.01 (2.52)
Participant Illegally Diverted His/Her Participant’s Opioid to Others Opioid was (12) Stolen (11) 57.1 (4.1)
Participant Shared His/Her Opioid With Family/ Friends (21)
Participant Received Opioids From Family/ Friends (45)
57.9 (12.1)
62.0 (11.4)
59.0 (9.3)
30 (23.8)
22 (33.8)
0.14 (2.18)
5 (41.7)
4 (36.4)
7 (33.3)
15 (33.3)
10 (7.9)
5 (7.7)
0.95 (0.004)
1 (8.3)
3 (27.3)
1 (4.8)
2 (4.4)
65 (51.6)
28 (43.1)
0.27 (1.24)
6 (50.0)
2 (18.2)
9 (42.8)
23 (51.1)
14.6 (2.5)
14.1 (2.2)
0.17 (1.37)
14.3 (2.1)
14.1 (1.8)
14.2 (2.0)
14.2 (2.2)
*For sample averages see Table 3.
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What do Patients do With Unused Opioid Medication
TABLE 5. Opioid Misuse Risk Factors and Opioid Management Type (n = 183)*
Mental health diagnosis (N [%]) Yes (129) No (54) SUD diagnosis excluding tobacco (N [%]) Yes (63) No (120) SUD diagnosis including tobacco (N [%]) Yes (93) No (90) Pain clinic visits (N [%]) Yes (4) No (179) Emergency room visits (N [%]) Yes (57) No (126)
No Extras (46)
Dispose of Extras (12)
Small Supply, Ongoing Prescription (41)
Some Supply, Unknown Quantity (84)
37 (28.7) 9 (16.7)
9 (7.0) 3 (5.6)
29 (22.5) 12 (22.2)
54 (41.9) 30 (55.6)
0.28 (3.86)
21 (33.3) 25 (20.8)
7 (11.1) 5 (4.2)
13 (20.6) 28 (23.3)
22 (34.9) 62 (51.7)
0.04 (8.26)
28 (30.1) 18 (20.0)
7 (7.5) 5 (5.6)
21 (22.6) 20 (22.2)
37 (39.8) 47 (52.2)
0.30 (3.67)
0 (0) 46 (25.7)
2 (50) 10 (5.6)
0 (0) 41 (22.9)
2 (50) 82 (45.8)
0.003 (13.73)
14 (24.6) 32 (25.4)
4 (7.0) 8 (6.3)
5 (8.8) 36 (28.6)
34 (59.6) 50 (39.7)
0.016 (10.31)
P (v2)
*Participants whose opioid management type could not be determined (n = 8) are excluded from this analysis. SUD indicates substance use disorder.
family and friends. Being younger was significantly associated with both of these types of behaviors. Interestingly, known risk factors for problematic opioid use including emergency room visits and having a mental health diagnosis alone were not significantly associated with either maintaining or saving opioids or diverting or sharing. A recent nontobacco SUD diagnosis was significantly associated with maintaining or saving opioids and participants with a SUD diagnosis including tobacco were significantly more likely to report diversion or sharing. This study has a number of important limitations. First, there are several concerns about the representativeness of the sample. The participation rate was relatively low, the sample is heavily biased toward male patients, patients are all US Veterans, and the number of patients with risk factors for medication misuse was higher than in the general population. However, a comparison between participating patients (n = 191) and eligible participants (B9000) found only small differences between the groups by average age (62.5 vs. 63.8 y) and percent female (8% vs. 7%), indicating that our sample is generally representative of the eligible Veteran population. Participants had experienced a wide range of conditions and medications and their absolute rate of emergency room visits and pain clinic visits were low. Our findings about rates of opioid saving also closely parallel the results of a survey of Utah residents.24 Other limitations are inherent to a qualitative study. We relied on participants’ retrospective self-report which is subject to response bias and memory lapses. The data were collected at one point in time and patient’s opioid management patterns are likely dynamic and change as their health and life circumstances change. Unless selfreported, it is also unknown whether these Veteran patients are receiving opioids from non-VA sources. Although all data in this paper were coded by 2 coders, ultimately there is subjectivity in categorizing participants’ opioid management patterns, as there would be if this classification was done by clinicians. r
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The impact of unused prescribed opioids on pain management and disability is largely unknown. However, Shrank30 summarized the state of knowledge as “nonmedical use of opiates is the best-documented consequence of holding onto leftover medications.” Given the existing evidence that legitimate prescriptions are one of the leading sources of opioids used by people with addiction or
TABLE 6. Opioid Misuse Risk Factors and Reported Diversion or Sharing (n = 191)
No Evidence of Evidence of Diversion Diversion or Sharing or Sharing (65) (126) Mental health diagnosis (N [%]) Yes (135) No (56) SUD diagnosis excluding tobacco (N [%]) Yes (66) No (125) SUD diagnosis including tobacco (N [%]) Yes (96) No (95) Pain clinic visits (N [%]) Yes (4) No (187) Emergency room visits (N [%]) Yes (62) No (129)
P (v2)
51 (37.8) 14 (25.0)
84 (62.2) 42 (75.0)
0.09 (2.88)
28 (42.4) 37 (29.6)
38 (57.6) 88 (70.4)
0.08 (3.16)
45 (46.9) 20 (21.1)
51 (53.1) 75 (78.9)
1 (25.0) 64 (34.2)
3 (75.0) 120 (64.1)
0.684 (0.17)
23 (37.1) 42 (32.5)
39 (62.9) 87 (67.4)
0.535 (0.38)
< 0.001 (14.18)
SUD indicates substance use disorder.
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substance use problems, the findings of this study present providers with the challenge of working to limit the supply of opioid medications available for diversion while not undertreating patients’ pain. The larger literature on how patients use opioid medications suggests considerable cause for caution on the part of prescribers separate from the risk of a patient over-using the opioid. A recent study found that 39.2% of respondents had prescription pain medications in their possession and >80% had never received information about proper disposal of their prescription medications.17 Multiple research studies on opioid nonadherence also document that patients receive opioid medications and subsequently do not take them for a variety of reasons.15,17,18,31–33 For example, Fishman et al34 lists 16 reasons why patients might under-use opioid medications such as fear of addiction, side effects, and forgetfulness. Gunnarsdottir et al35 identifies 4 factors endorsed by patients as barriers to using analgesics including fatalism about pain and beliefs about the harmful effects of pain medications. The findings of this paper reinforce the growing evidence that while concern about over-use and abuse of opioids is legitimate, retention and failure to dispose of unused opioids is common. It also lays out some of the specific reasons and patterns of behavior presented by patients when asked to describe their medication management choices. Providers can take a number of concrete clinical actions to reduce the risk to the patient and others from prescribed opioids,36 including some identified in the “universal precautions” approach.37,38 Rather than reiterate these precautions here, we will focus on clinical actions that may be most relevant to improving patients’ understanding and behaviors. Implementation of these clinical actions will depend on the individual prescriber’s local context (eg, state-specific opioid prescribing policies39) and practice characteristics. Engage in clear, open, 2-way communication about opioid therapy and nonmedication options for pain management. This can help identify patients who may be reluctant to use opioids or who are concerned about using them. These patients can be offered nonopioid pain management options such as physical therapy or psychosocial treatments for pain. Counsel patients prescribed opioids (especially patients with a recent SUD diagnosis) not only about the risk of overdose to themselves but also about the risk to others with whom they might share their medication. In addition, providers can inform their patients that federal law prohibits sharing prescription medications with others, including family or friends. Offer patients initial prescriptions that are calibrated to their expected length of use (for acute pain) or appropriate for an adequate trial (if initiating opioids for chronic pain). Simultaneously, reassure patients that they will receive additional medication if needed. Just as initiating and maintaining a patient on an opioid medication is a process, educating patients about appropriate management of that opioid medication is a process. No 1-time discussion about the topic or inflexible policy is likely to be effective, as patients may have misperceptions or a lack of understanding about opioid medications.40 Changing patient behavior will likely require an approach tailored to the specific patient’s situation and repeated interactions around the topic of medication management and disposal, especially for patients with complex medication conditions requiring multiple medications and given the changing regulatory
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environment. An opioid trial with a patient or an ongoing opioid prescription for chronic pain both require individualized action by the provider, and the educational process about safe medication management must similarly be tailored to the patient based on clinical judgment and local laws and regulations. An essential part of this educational process is to have information easily accessible about options for safe disposal of opioid medications.36 The Responsible Drug Disposal Act of 2010 (http://www.govtrack.us/congress/bills/111/ s3397) facilitates drug take-back programs and should make it easier and more transparent for all patients to dispose of unused or unneeded medications in a safe, appropriate way. The US Food and Drug Administration41 and US Environmental Protection Agency42 have useful information available on medication disposal. The 3 main approaches to safe medication disposal are using medication disposal programs, disposing of medications in household trash after following specific procedures, and flushing some medications down the sink or toilet. Providers should also partner as closely as possible with the pharmacies filling the patients’ prescriptions. Pharmacists can reinforce information about safe medication disposal and incorporate this information into their routine patient counseling and educational handouts. If a prescriber suspect that a patient’s use of opioids may be problematic, there are additional actions he or she can consider: Use a validated screener for prescription medication misuse in all patients, but particularly patients with SUDs, the risk factor most commonly found to be associated with problematic opioid use.43 For example, the Current Opioid Misuse Measure44 is designed to help detect potentially problematic behavior with medications by chronic pain patients. Use an opioid pain care agreement. Multiple examples are available free online. Access state’s prescription drug monitoring program database to identify patients receiving opioids from multiple providers. As Hall et al45 states: “Clinicians have a critical role to play in preventing the diversion of prescription drugs.” Health care providers are beginning to acknowledge that they may be over-prescribing pain medications46 and supplementing the supply of opioids available to addicts.47 Fortunately, clinicians have a number of tools available to reduce unnecessary opioid prescribing and improve the efficacy of pain management.36,48 Of course, patients must take responsibility for communicating with their providers about their preference and intention to use opioid medication. Policy makers also owe the public clear information about options for safe opioid disposal, and owe health care providers and pharmacists streamlined regulatory guidance that facilitates this disposal. Reducing the flow of opioids available for diversion and abuse begins with the provider thinking about the lifecycle of the prescription in the patients’ hands.
ACKNOWLEDGMENTS The authors thank the contributions of Dr Michelle A. Skinner (PhD, San Mateo, CA) with data analysis for this paper and Ann Combs (MPH, Center for Innovation to Implementation, Veterans Affairs - Palo Alto Health Care System, Menlo Park, CA) for her assistance with the original interviews. r
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45. Hall A, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA. 2008;300:2613–2620. 46. Bates C, Laciak R, Southwick A, et al. Overprescription of postoperative narcotics: a look at postoperative pain medication delivery, consumption and disposal in urological practice. J Urol. 2011;185:551–555. 47. McLellan AT, Turner BJ. Prescription opioids, overdose deaths, and physician responsibility. JAMA. 2008;300:2672–2673. 48. Volkow ND, McLellan TA. Curtailing diversion and abuse of opioid analgesics without jeopardizing pain treatment. JAMA. 2011;305:1346–1347.
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