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A randomized pilot program to reduce opioid use following dental surgery and increase safe medication return
Addictive Behaviors 102 (2020) 106190
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Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
A randomized pilot program to reduce opioid use following dental surgery and increase safe medication return
T
⁎
Karen J. Derefinkoa, , Francisco I. Salgado Garcíaa, Karen C. Johnsona, Sarah Handa, James G. Murphyb, Meghan McDevitt-Murphyb, Katie J. Sudac, Frank Andrasikb, Zoran Bursacd, Chi-Yang Chiua, Kevin Talleya, Jeffrey H. Brookse a
University of Tennessee Health Science Center, Department of Preventive Medicine, United States University of Memphis, Department of Psychology, United States c VA Center of Innovation for Complex Chronic Healthcare, Edward Hines, Jr. VA Hospital and University of Illinois at Chicago, Department of Pharmacy, Systems, Outcomes, and Policy, United States d Florida International University, Department of Biostatistics, United States e University of Tennessee Health Science Center, Department of Oral and Maxillofacial Surgery, United States b
H I GH L IG H T S
study examined the efficacy of opioid exposure reduction in dental patients. • The to treat analysis indicated a non-significant trend for treatment group effect. • Intent analysis showed that the treated group self-reported less opioid use. • Sensitivity • A brief intervention and non-narcotic pain medication may reduce opioid use.
A R T I C LE I N FO
A B S T R A C T
Keywords: Opioid Prevention Dental surgery Opioid exposure Opioid misuse
Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Because dentists represent some of the highest opioid prescribing medical professionals in the US, dental practices offer a critical site for intervention. The current study used a randomized clinical trial design to examine the efficacy of an opioid misuse prevention program (OMPP), presented as a brief intervention immediately prior to dental extraction surgery. The OMPP provided educational counseling about risks and appropriate use of opioid medication, as well as 28 tablets of ibuprofen (200 mg) and 28 tablets of acetaminophen (500 mg) for weaning off opioid medication. This was compared with a Treatment as Usual (TAU) control condition. Participants were individuals presenting for surgery who were eligible for opioid medication (N = 76). Follow up assessment was conducted at 1 week following surgery, with 4 individuals refusing follow up or not prescribed opioid. Intent to treat analysis indicated a non-significant treatment group effect (N = 72, Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use (in morphine milligram equivalents, MMEs) than the TAU group (37.94 vs. 47.79, effect size d = 0.42). Sensitivity analysis, excluding individuals with complications following surgery (n = 6) indicated a significant treatment group effect (N = 66, Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less MMEs than the TAU group (29.74 vs. 43.59, effect size d = 0.56). Results indicate that a 10-minute intervention and provision of non-narcotic pain medications may reduce the amount of self-administered opioid medication following dental surgery.
1. Introduction Dentists represent some of the highest opioid prescribing medical professionals in the US. Research indicates that dentists are second only ⁎
to family physicians as the most frequent prescribers of opioid medication (Rigoni, 2003; Volkow, McLellan, Cotto, Karithanom, & Weiss, 2011). Although dentists represent 9% of opioid prescribers, they prescribe 45% of opioids (McCauley et al., 2016), and while prescribing of
Corresponding author. E-mail address: kderefi[email protected] (K.J. Derefinko).
https://doi.org/10.1016/j.addbeh.2019.106190 Received 3 June 2019; Received in revised form 21 October 2019; Accepted 21 October 2019 Available online 23 October 2019 0306-4603/ © 2019 Elsevier Ltd. All rights reserved.
Addictive Behaviors 102 (2020) 106190
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Fig. 1. CONSORT Diagram.
1.1. The risks of opioid exposure
opioids is decreasing in the US, there is evidence of increasing rates in dental settings (Gupta, Vujicic, & Blatz, 2018; Guy et al., 2017). Opioid prescription is especially common in maxillofacial surgery, as 85%–100% of dentists prescribe opioids to patients (Denisco et al., 2011; Moore, Nahouraii, Zovko, & Wisniewski, 2006). In addition, dentists and maxillofacial surgeons commonly prescribe hydrocodone and oxycodone, which are frequently misused (McCauley et al., 2016; Mutlu, Abubaker, & Laskin, 2013). This issue of opioid prescribing in dentistry is particularly problematic in the US; a recent study of prescribing rates suggests that in 2016, the proportion of prescriptions written for opioids by US dentists was 37 times greater than that for dentists in England (Suda et al., 2019).
Exposure to opioids is of critical importance to long-term outcomes. Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Medical claims research indicates that among opioid naïve patients (N = 536,767), those who fill opioid prescriptions one time are 2.9% likely to become long term users, whereas those who fill four or more times are 26.1% likely to use opioids long term (Deyo et al., 2017). Even acute and low-dose exposure appears to increase risk of longterm opioid use. In a medical records study derived from commercial health plan data (2006–2015; N = 1,294,247) individuals prescribed at least one day of opioids had a probability of continued opioid use at one year of 6.0%, and those prescribed eight days or more had a probability of continued use at one year of 30% (Shah, Hayes, & Martin, 2017). In a 2
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intervention (TAU; Treatment as Usual). Those in the OMPP received the intervention immediately following. Randomization was pre-determined using blocks of 6. Packets of study forms, which either included the intervention script (or not, for TAU) were stacked according to this scheme prior to the start of the study, so that the next packet in line for use determined randomization status. After randomization (and intervention, for those in the OMPP condition), participants responded to a knowledge questionnaire and received a $10 gift card. These procedures occurred during the waiting period immediately before surgery which is typically 45 min in duration. After study procedures were complete, the participant was moved to the operating room, sedated for surgery, and completed the rest of the surgical visit, which included receipt of opioid prescription. Opioid prescription dose and duration varied by severity of surgery, as decided by one of six surgeons on staff.
study of opioid prescribing in dental settings, of 14,888 individuals who received an opioid prescription, 6.9% received another opioid prescription between 90 and 365 days later, and 5.8% experienced one or more subsequent health care encounters with an opioid abuse-related diagnosis (as compared with 0.1% and 0.4% for a non-opioid exposed control) (Schroeder, Dehghan, Newman, Bentley, & Park, 2019). 1.2. The role of dentists in opioid use reduction Recent prescription guidelines for dentists have recommended limiting opioid prescribing and encouraging combined ibuprofen and acetaminophen for postoperative pain (Becker, 2010; Dana, Azarpazhooh, Laghapour, Suda, & Okunseri, 2018; Moore & Hersh, 2013). In addition, guidelines also encourage patient education on appropriate use of opioids, opioid disposal, and the risks of combining opioids with sedatives (Clark & Schumacher, 2017; Gandhi & Best, 2015), but to date, little work has examined brief intervention to reduce adverse consequences (Kennedy-Hendricks et al., 2016; McCauley, Back, & Brady, 2013).
2.2.2. Follow up phone call Study staff blinded to treatment condition called participants seven days after baseline to complete follow up questionnaires. Participants received a $20 gift card upon completion of the seven-day follow-up.
1.3. The current study 2.3. Intervention conditions The current study was a randomized clinical pilot trial exploring the efficacy of a patient-based psychoeducational and pharmacological opioid misuse prevention program (OMPP), administered to dental patients immediately prior to tooth extraction surgery, relative to a control group receiving treatment as usual (TAU). We hypothesized that patients who received the OMPP would report lower use of opioid medication post-surgery (i.e., fewer morphine milligram equivalents, or MMEs) and higher rates of safe disposal of unused opioid than patients who received TAU.
2.3.1. Opioid misuse prevention program (OMPP) The OMPP was developed based upon the Health Belief Model (Champion & Skinner, 2008), and consisted of two components: psychoeducation material presented by an interventionist, and a seven-day supply of acetaminophen (500 mg every 6–8 h PRN) and ibuprofen (200 mg every 6–8 h PRN) provided in a blister pack for optional use in weaning off opioid medication. The psychoeducation session included a 10-minute discussion (with active participation from the patient) of multiple topics based upon recommendations in the literature (Becker, 2010; Clark & Schumacher, 2017; Gandhi & Best, 2015): Importance: Opioids prescribed by dentists can be the initial exposure point for individuals. Tolerance and Use Disorder: Tolerance can begin quickly and lead a person to use more opioid. Consequences of Concomitant Alcohol/ Drug Use: Slowed heart rate, coma, death. Appropriate Use of Opioid Pain Medication: Patients are not required to use all prescribed opioid. We advised participants that on the second day following surgery if they are at a five or lower on the Wong-Baker Faces Pain Rating Scale (Baker & Wong, 1987), they should transition to acetaminophen and ibuprofen to reduce risk for becoming dependent. Appropriate Disposal: Dangers of keeping medication (inadvertent ingestion, legal issues with selling/ giving to someone else). Participants were provided a list of local opioid takeback sites, which included pharmacies (n = 6) and law enforcement locations (n = 11), and a handout with a summary of the session material (see Appendix).
2. Material and methods 2.1. Participants Participants were recruited at an oral and maxillofacial surgery clinic at a health science university in the Southern US. IRB approval was obtained. The study was conducted between December 2017 and July 2018. Prescriptions for opioid medication following surgery are standard at this practice. Patients were eligible to participate if they were 18 years of age or older, presented for dental surgery that would result in opioid prescription, and had a phone number for follow up assessment. Participants were excluded if they reported currently taking opioids or had contra-indications to opioids, acetaminophen, or ibuprofen. Staff at the dental clinic identified 112 interested participants who were approached for the study. Of these, 76 were randomized, 72 completed the follow up (intent to treat analysis), and 66 did not have post-surgical complications (sensitivity analysis; see Fig. 1).
2.3.2. Treatment as usual (TAU) Those randomized to the TAU group did not receive any psychoeducation or acetaminophen/ibuprofen from the study interventionist. They received usual care from their dental providers.
2.2. Procedures 2.2.1. Study visit on surgery day All patients presenting for surgery received brief instructions from the clinic staff when they presented for surgery to engage in nonpharmacological activities to promote comfort (e.g., saltwater rinse, soft foods, and cold compress) following surgery. This was typical clinic practice, and was not changed during the administration of these study procedures. After the patient checked in, staff at the dental clinic referred interested patients to the research interventionist, a bachelor’s level individual trained on the study protocol, before interaction with the dental surgeon. The interventionist screened for eligibility in a private room. Eligible participants provided informed consent and completed baseline assessment. Next, participants were randomized to either the Opioid Misuse Prevention program (OMPP; 10 min in duration) or no
2.4. Measures pre-surgery 2.4.1. Demographics This questionnaire included age, gender, race/ethnicity, marital status, household income, highest level of education, and prior medical use of opioids during the past six months (yes/no). 2.4.2. Knowledge questionnaire This questionnaire included 5 open-ended questions relevant to the OMPP to establish intervention comprehension immediately following administration. Questions included (1) definition of tolerance, (2) timeframe of tolerance development, (3) importance of tolerance to the development of opioid use disorder, (4) classification of alcohol and 3
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Table 1 Unadjusted comparisons between treatment and control groups (N = 76). Variable
Gender Male Female Transgender Race/Ethnicity Caucasian African American Hispanic or Latino Other Marital Status Married Widowed Divorced Separated Single Household Income Unsure < $10,000 $10,000–$19,999 $20,000–$29,999 $30,000–$39,999 $40,000–$49,999 $50,000–$59,999 $60,000–$69,999 $70,000–$79,999 $80,000–$89,999 $90,000–$99,999 > $100,000 Education 8th grade or less 9th–11th grade 12th grade/GED Associate’s degree Vocational/trade school Some college Bachelor's Graduate Refused to Answer Medication type prescribed Hydrocodone 5/325 mg Oxycodone 5/325 mg Not prescribed Previous use of opioids for medical reason Variable Age
Treatment (n = 38)
Control (n = 38)
χ2
df
p
2.13
2
0.3455
9.24
3
0.0263
6.59
4
0.1592
7.91
10
0.6372
10.40
7
0.1670
N
%
N
%
15 22 1
40% 58% 3%
11 27 0
29% 71% 0%
8 27 0 3
21% 71% 0% 8%
16 15 3 4
42% 40% 8% 11%
7 1 1 1 28
18% 3% 3% 3% 74%
8 5 4 2 19
21% 13% 11% 5% 50%
3 10 5 5 4 6 3 1 0 1 0 0
8% 26% 13% 13% 11% 16% 8% 3% 0% 3% 0% 0%
2 4 9 7 4 3 3 2 0 2 1 1
5% 11% 24% 18% 11% 8% 8% 5% 0% 5% 3% 3%
1 4 11 4 5 8 5 0 0
3% 11% 29% 12% 13% 21% 13% 0% 0%
0 1 10 3 2 14 3 4 1
0% 3% 27% 8% 5% 38% 8% 11% 3% 0.59
2
0.9708
22 14 2 29 Treatment (n = 36) Mean 39.71
58% 37% 5% 81%
23 13 2 28 Control (n = 36) Mean 42.95
61% 34% 5% 78%
0.84
1
0.772
SD 18.72
t -0.77
df 74
p 0.4421
SD 17.78
Note: Descriptive group difference analysis results were not different between the enrolled sample (N = 76) and that which was used in the outcomes analysis (N = 72) (data not shown).
2.5. Measures post-surgery
benzodiazepines, and (5) risks associated with mixing opioids and alcohol or benzodiazepines. These responses were coded as correct (1) or incorrect (0) and summed to create a score ranging from 0 to 5. Cronbach’s alpha = 0.67.
2.5.1. Prescribed and self-administered opioid medication This questionnaire asked about the opioid prescribed (type, quantity, and dose; confirmed via medical chart), which served to establish the severity of the surgery (Malamed, 2019; Seymour, Blair, & Wyatt, 1983), and the number of pills self-administered after surgery. Dose and number of pills prescribed and self-administered were used to calculate morphine milligram equivalents (MMEs) for each variable using the scales provided by the Centers for Disease Control and Prevention: Hydrocodone/Acetaminophen 5 mg/325 mg tablets were multiplied by 1, and Oxycodone/Acetaminophen 5 mg/325 mg tables were multiplied by 1.5 to reflect differing MMEs across these medications (Centers for Disease Control and Prevention, 2018). This provided a standardized value for opioid medication.
2.4.3. Non-opioid pain management Participants were asked about awareness of non-opioid alternatives to managing pain after surgery (acetaminophen, ibuprofen, and nonpharmacological methods). Responses were coded as aware (1) or not aware (0).
2.4.4. Leftover opioid disposal We asked participants about the most appropriate method for disposing of leftover opioid medication following surgery, and what participants predicted they would do with their leftover opioids. Responses were coded as appropriate disposal method (1) or inappropriate (0).
2.5.2. Knowledge questionnaire Re-administered at the follow up. Cronbach’s alpha for follow up = 0.60. 4
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The OMPP and TAU groups were not significantly different in terms of MMEs prescribed (MOMPP = 98.65 and MTAU = 91.00, t(70) = 0.81, p = .4232) or worst pain experienced after surgery (MOMPP = 6.54 and MTAU = 6.60, t(70) = −0.09, p = .9285). In addition, those in the OMPP group were more likely to have used acetaminophen (OMPP = 70% and TAU = 31%, χ2 = 10.86, df = 1, p = .0010), and to have used ibuprofen (OMPP = 84% and TAU = 46%, χ2 = 11.50, df = 1, p = .0007) to manage pain. Groups were not different in terms of use of non-medication strategies to manage pain (OMPP = 76% and TAU = 74%, χ2 = 0.11, df = 1, p = .8917).
2.5.3. Pain after surgery Participants were asked about pain rating following surgery using the Wong Baker pain scale with anchors of 0 = no pain and 10 = worst pain (Baker & Wong, 1987). 2.5.4. Non-Opioid pain management We asked participants if they used (1) acetaminophen, (2) ibuprofen, or (3) non-pharmacological forms of non-opioid pain management (yes/no) following surgery. 2.5.5. Leftover opioid disposal At post-test, for those with leftover medication, participants selfreported their actual opioid disposal method or their plans to dispose of leftover opioids. Responses were coded as appropriate disposal method (1) or inappropriate (0).
3.3. Opioid medication self-administration A multivariable linear regression was conducted to examine whether treatment contributed to differences in opioid self-administration. Opioid medication data were standardized across medication type into morphine milligram equivalents (MMEs). We tested for assumptions (e.g., multicollinearity between the independent variables, linearity, and normality assumption), and determined that no changes to analyses were deemed necessary.
2.6. Statistical data analysis All analyses were performed using SPSS software. We conducted univariate comparisons using t-tests and χ2 tests to assess baseline differences between OMPP and TAU. To examine the primary outcome, we used multivariable linear regression to investigate the effect of the treatment group on MMEs selfadministered following the surgery. We added two control variables to analyses: prescribed MMEs following the surgery, and participant-reported pain following surgery. Intent to treat analyses were conducted with the entire eligible sample (N = 72) and a sensitivity analysis excluding those who had complications following surgery (e.g., alveolar osteitis, N = 66). All associations were considered significant at the alpha level of 0.05.
3.3.1. Intent to treat analysis (N = 72; Table 3) Control variables included prescribed MMEs (as a proxy for surgery severity), worst pain experienced after surgery self-reported by the participant, and race (identified as a significant group difference in baseline adjusted group comparisons). The regression model predicting MMEs self-administered was significant (F(4,71) = 14.25, p < .0001, adjusted R2 = 0.43). Results indicated a non-significant trend for treatment group effect (Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use than the TAU group (37.94 MMEs vs. 47.79 MMEs, effect size d = 0.42, 95% CI : −0.05 to 0.88). MMEs prescribed and worst pain after surgery accounted for significant variance in the model (Beta = 0.44, p < .0001 and Beta = 0.41, p < .0001, respectively). Race was not a significant predictor of MMEs self-administered (Beta = −0.11, p = .2322).
3. Results 3.1. Descriptive statistics on demographic and opiate use variables Univariate comparisons between treatment and control groups were conducted using the entire enrolled sample (N = 76). The sample was 34% male, mean age 41.33 (SD = 18.21), with 28% having a high school level education or less and 37% with a household income of less than $20,000 per year. There were no significant treatment group differences in gender, marital status, household income, education, opioid medication type prescribed, previous use of prescribed opioids, or age. Results indicated significant group difference in race (χ2 = 9.24, df = 3, p = .0263); the OMPP group had a lower proportion of Caucasians than the TAU group (21% vs 42%, respectively) and a higher proportion of African Americans than the TAU group (71% vs. 40%, respectively; see Table 1 for descriptive information).
3.3.2. Sensitivity analysis (N = 66; Table 4) This analysis was conducted excluding individuals who presented with complications from surgery (n = 6) given that these individuals were still in recovery at the time of follow up. Control variables included total prescribed MMEs, worst pain after surgery self-reported by the participant, and race. The regression model predicting MME selfadministered was significant (F(4,65) = 8.24, p < .0001, adjusted R2 = 0.31). Results indicated a significant treatment group effect (Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less opioid use than the TAU group (29.74 MMEs vs. 43.59 MMEs, effect size d = 0.56, 95% CI: 0.07 to 1.05). MMEs prescribed and worst pain after surgery also accounted for significant variance in the model (Beta = 0.32, p = .0034 and Beta = 0.40, p = .0003, respectively). Race was not a significant predictor of MMEs self-administered (Beta = −0.11, p = .2912).
3.2. Treatment factors 3.2.1. Surgery day Group differences in potential treatment factors were examined (Table 2). Following the intervention delivery, those who received the OMPP (vs. TAU) had more knowledge of the risks associated with opioid use (MOMPP = 3.70 and MTAU = 1.56, t(69) = 7.65, p < .0001). Further, those in the OMPP group were more likely to be aware of nonmedication pain management strategies (OMPP = 84% and TAU = 50%, χ2 = 9.23, df = 1, p = .0024).
3.4. Leftover opioid disposal (Table 5) Following the intervention on surgery day, those in the OMPP group were more likely to be aware of the appropriate method for leftover opioid disposal (OMPP = 97% and TAU = 47%, χ2 = 22.82, df = 1, p < .0001), and had a higher likelihood of predicting that they would dispose of any leftover opioid appropriately (OMPP = 76% and TAU = 21%, χ2 = 21.51, df = 1, p < .0001). At 1-week follow up, those who received the OMPP were more likely to have a plan to dispose of any unused opioid appropriately (OMPP = 60% and TAU = 21%, χ2 = 8.21, df = 1, p = .0042). Groups were not significantly different in terms of medication return rates (OMPP = 21% and TAU = 4%, χ2 = 3.69, df = 1, p = .0548), but this difference represented an effect size of d = 0.49.
3.2.2. One week follow-up At the 1-week follow-up phone call, those who received the OMPP (vs. TAU) had more knowledge of the risks associated with opioid use (MOMPP = 3.11 and MTAU = 1.97, t(70) = 3.50, p = .0008). Repeated measures suggested that knowledge decreased for the OMPP group, F (1,36) = 12.76, p = .0010, and increased for the TAU group F (1,33) = 6.00, p = .0198. 5
Addictive Behaviors 102 (2020) 106190
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Table 2 Comparisons of treatment factors (N = 72). Pre-Surgery Treatment
Knowledge following intervention
Awareness of non-opioid strategies to manage pain
Control
Group n
Mean
SD
Group n
Mean
SD
df
t
p
37
3.70
1.33
34
1.56
0.99
69
7.65
0.0000
Group n
n
%
Group n
n
%
df
χ2
p
37
31
84%
35
17
50%
1
9.23
0.0024
One Week Follow-Up Treatment
Knowledge at 1-week follow-up Total MMEs prescribed Pain after surgery
Use of acetaminophen Use of ibuprofen Use of non-pharmacological strategies to manage pain
Control
Group n
Mean
SD
Group n
Mean
SD
df
t
p
37 37 37
3.11 98.65 6.54
1.61 40.85 2.79
35 35 35
1.97 91.00 6.60
1.07 39.63 2.82
70 70 70
3.50 0.81 −0.09
0.0008 0.4232 0.9285
Group n
N
%
Group n
N
%
df
χ2
p
37 37 37
26 31 28
70% 84% 76%
35 35 35
11 16 26
31% 46% 74%
1 1 1
10.86 11.50 0.02
0.0010 0.0007 0.8917
Note: MMEs = Morphine Milligram Equivalents. Significant predictors presented in bold type. One control participant’s data was not recorded on the knowledge measure Pre-Surgery, resulting in a smaller n of 34.
4. Discussion
opioid use, yet achieved scores similar to CDC recommendations (20–50 morphine milligram equivalents [MME]/day) (Centers for Disease Control and Prevention, 2017) for safety. However, it should be noted that beta weights for pain score and MMEs were larger than the beta weight for treatment group. This is expected, given the importance of pain and availability of opioid medication to opioid medication use. In addition to reductions in opioid use, the OMPP produced significant gains in leftover opioid disposal awareness and intentions. The effect size d = 0.49 for safe medication return suggests that even within one week, return rate group differences were considerable. Removal of available opioid from the community is a target of educational campaigns (Inciardi, Surratt, Lugo, & Cicero, 2007), but often patients do not know where to safely return their unused opioids. We provided participants a handout listing confirmed medication return locations in the city. This may be an important prevention strategy given that most pharmacies do not accept unused medication. Efforts to and incentivize the use of medication take-back programs and facilities could further decrease opioid diversion, a major factor in OUD (Buffington, Lozicki, Alfieri, & Bond, 2019; McCabe et al., 2017). Safe storage and disposal has been a target of other existing work which did not find significant return effects (McCauley et al., 2013).
Reducing cumulative exposure to opioids is of clear importance given high rates of long-term use. Although guidelines encourage nonnarcotic analgesics (Moore & Hersh, 2013), there remains widespread opioid prescribing in dental surgery settings to manage moderate to severe pain. The results of this pilot trial add to the emergent evidence supporting brief, patient-based interventions targeting inappropriate use of opioids following surgery (McCauley et al., 2013), and may be one of the first trials of brief intervention which directly targets reductions in prescribed opioid use. Our psychoeducational and pharmacological intervention addressed multiple targets, including describing the risks associated with prolonged opioid medication use and the benefits of acetaminophen and ibuprofen to wean off opioid medication. Opioid Misuse Prevention Program (OMPP) participants had higher knowledge scores, higher awareness of non-opioid pain relief strategies, and higher frequency of use of these non-opioid strategies post-surgery compared to Treatment as Usual (TAU) participants. These findings suggest that dental patients benefit from information provided in a brief format prior to surgery to promote non-opioid alternatives to pain management. As predicted, patients in the OMPP group self-reported less opioid use than patients in the TAU group. In the sensitivity analysis, the mean group difference between OMPP and TAU (29.74 vs. 43.59 MMEs) represents a medium sized effect of 0.56, which is promising for a brief intervention. The OMPP intervention did not target a clear limit to
4.1. Strengths and limitations This study had several strengths, including a diverse sample and the evaluation of a brief and practical intervention that has the potential for
Table 3 Intent to treat analysis of the prediction of cumulative morphine milligram equivalents (MMEs) self-administered following Opioid Misuse Prevention Program (OMPP) treatment vs. Treatment as Usual (TAU) control (N = 72).
Treatment group MMEs prescribed Worst pain after surgery Race
B
SEB
Beta
t
p
Effect Size d
Effect Size 95% CI
12.51 0.43 5.80 −5.05
7.12 0.09 1.32 4.19
0.16 0.44 0.41 -0.11
1.76 4.70 4.40 −1.21
0.0835 0.0000 0.0000 0.2322
0.42 1.11 1.04 -0.29
−0.05 to 0.88 0.61 to 1.60 0.54 to 1.53 −0.75 to 0.18
Note: OMPP = Opioid Misuse Prevention Program. TAU = Treatment as Usual. MMEs = morphine milligram equivalents. Significant predictors presented in bold type. Effect Size d was computed from t-score and sample size (Lipsey & Wilson, 2001). 6
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Table 4 Sensitivity analysis of the prediction of cumulative MMEs self-administered following OMPP treatment vs. TAU control (N = 66).
Treatment group MMEs prescribed Worst pain after surgery Race
B
SEB
Beta
t
p
Effect Size d
Effect Size 95% CI
15.30 0.28 4.74 −4.10
6.70 0.09 1.22 3.81
0.24 0.32 0.40 -0.11
2.28 3.05 3.88 −1.07
0.0259 0.0034 0.0003 0.2912
0.56 0.75 0.96 -0.26
0.07 to 1.05 0.25 to 1.25 0.45 to 1.47 −0.75 to 0.22
Note: OMPP = Opioid Misuse Prevention program. TAU = Treatment as Usual. MMEs = morphine milligram equivalents. Only individuals without extended prescriptions due to complications were eligible for analysis. Significant predictors presented in bold type. Effect Size d was computed from t-score and sample size (Lipsey & Wilson, 2001).
fidelity was not conducted in this pilot, which may have resulted in drift. However, this intervention was scripted (content designed to be delivered verbatim), making it unlikely administration varied considerably. Additionally, we did not control for contact time in the TAU group; it is possible that changes in opioid self-administration are partially due to time with the interventionist. Finally, the OMPP was delivered by a research interventionist, thereby limiting our ability to describe disseminability. Future work may benefit from having dental staff deliver the OMPP to assess distribution to broader populations.
wide dissemination across dental settings. Further, our study employed measures of knowledge, intentions, and behavior, which together demonstrate the mechanisms of change that may be at work following this intervention. Results of this study present some limitations. First, we used selfreported pill counts to calculate opioid use. Future work would benefit from in person pill counts to verify remaining medication. In addition, the setting where patients were recruited had a lower household income and lower education than other dental surgery settings, limiting generalizability. Moreover, the one-week follow-up timeframe may have been too short to detect specific outcomes, as some patients were ineligible for analysis due to complications that resulted in more opioid prescribed and due to the lack of sufficient time to return unused opioids to a takeback location. However, the first week following surgery is a critical time for the development of opioid tolerance, and our results demonstrate effective knowledge acquisition in the OMPP group which should reduce risk for subsequent misuse. Further, although the knowledge measure designed only to test for intervention effect, the Cronbach’s alpha was low. Additionally, we did not do a pre-test of knowledge prior to the intervention due to time constraints with patients prior to surgery. Our team decided that confirmation of the treatment effect immediately following intervention was ultimately the most important data given questions regarding possible retention of material prior to anesthesia. Furthermore, acetaminophen and ibuprofen was provided only to the treatment group, which introduced an accessibility bias. The alternative would have required counseling the control group given the contraindication to use concurrently with hydrocodone or oxycodone, and we did not wish to blur the distinction between groups. In addition,
4.2. Conclusions This study explored the use of a brief psychoeducational and pharmacological intervention prior to dental surgery to reduce the use of opioids post-surgery and increase the safe return of leftover opioid medication. Results indicated that this Psychoeducational and pharmacological program reduced cumulative opioid self-administration and increased awareness and intentions to return unused opioid medication to a takeback location. While treatment elements (counseling vs. non-opioid medication) could not be evaluated for individual effects, future work may isolate these therapeutic elements to establish their individual merit. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Appendix Tips for a Speedy and Safe Recovery 1. Take your pain medication as prescribed
• Follow your physician’s guidelines for taking your pain medication • Do not take more than prescribed Table 5 Leftover Opioid Disposal. Treatment
Control
Group n
n
%
Group n
n
%
df
χ2
p
Effect Size d
Effect Size 95% CI
Pre-Surgery Aware of leftover opioid disposal Predicted leftover opioid disposal
37 37
36 28
97% 76%
34 34
16 7
47% 21%
1 1
22.82 21.51
0.0000 0.0000
1.38 1.32
0.81 to 1.94 0.76 to 1.88
One Week Follow-Up Actual leftover opioid disposala Plans for leftover opioid disposalb
39 25
6 15
21% 60%
27 28
1 6
4% 21%
1 1
3.69 8.21
0.0548 0.0042
0.49 0.86
−0.01 to 0.98 0.27 to 1.44
Note: Post-surgery opioid disposal assessment questions not applicable to those who self-administered all of the opioid medication. a. Only individuals who had been prescribed opioid medication, had completed opioid medication administration, and had leftover medication were eligible for analysis. b. Only individuals who had been prescribed opioid medication, had leftover medication, and had not already returned medication were eligible for analysis. Significant predictors presented in bold type. Effect Size d was computed from chi-square values and sample sizes (Lipsey & Wilson, 2001). 7
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• Do not mix your pain medication with alcohol or other sedatives 2. Stop using the pain medication as soon as possible
• Identify where you are on the pain scale before you take pain medication again:
• If you are at a 5 or below on the pain scale, consider taking acetaminophen/ibuprofen instead of the pain medication 3. Take your leftover opioid to a takeback location
• The only safe place for leftover opioid medication is a takeback location • This removes the medication from circulation, and protects you from consequences 4. Questions?
• Talk to your dentist about any concerns you have. Your comfort and healing are important to us. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.addbeh.2019.106190.
(2017). Vital signs: Changes in opioid prescribing in the United States, 2006–2015. MMWR. Morbidity and Mortality Weekly Report, 66(26), 697. Inciardi, J. A., Surratt, H. L., Lugo, Y., & Cicero, T. J. (2007). The diversion of prescription opioid analgesics. Law Enforcement Executive Forum, 7(7), 127–141. Kennedy-Hendricks, A., Gielen, A., McDonald, E., McGinty, E. E., Shields, W., & Barry, C. L. (2016). Medication sharing, storage, and disposal practices for opioid medications among US adults sharing, storage, and disposal practices for opioids letters. JAMA Internal Medicine, 176(7), 1027–1029. Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis (Applied Social Research Methods) thousand oaks. CA: Sage Publications. Malamed, S. (2019). Handbook of local Anesthesia (7th ed.). Mosby. McCabe, S. E., West, B. T., Veliz, P., McCabe, V. V., Stoddard, S. A., & Boyd, C. J. (2017). Trends in medical and nonmedical use of prescription opioids among US adolescents: 1976–2015. Pediatrics. McCauley, J. L., Back, S. E., & Brady, K. T. (2013). Pilot of a brief, web-based educational intervention targeting safe storage and disposal of prescription opioids. Addictive Behaviors, 38(6), 2230–2235. McCauley, J. L., Hyer, J. M., Ramakrishnan, V. R., Leite, R., Melvin, C. L., Fillingim, R. B., ... Brady, K. T. (2016). Dental opioid prescribing and multiple opioid prescriptions among dental patients: Administrative data from the South Carolina prescription drug monitoring program. Journal of the American Dental Association, 147(7), 537–544. Moore, P. A., & Hersh, E. V. (2013). Combining ibuprofen and acetaminophen for acute pain management after third-molar extractions: Translating clinical research to dental practice. Journal of the American Dental Association, 144(8), 898–908. Moore, P. A., Nahouraii, H. S., Zovko, J. G., & Wisniewski, S. R. (2006). Dental therapeutic practice patterns in the U.S. I. Anesthesia and sedation. General Dentistry, 54(2), 92–98. Mutlu, I., Abubaker, A. O., & Laskin, D. M. (2013). Narcotic prescribing habits and other methods of pain control by oral and maxillofacial surgeons after impacted third molar removal. Journal of Oral and Maxillofacial Surgery, 71(9), 1500–1503. Rigoni, G. C. (2003). Drug Utilization for Immediate and Modified Release Opioids in the US. Retrieved from: https://wayback.archive-it.org/7993/20170404072744/, https://www.fda.gov/ohrms/dockets/ac/03/slides/. (Accessed 5/29/19). Schroeder, A. R., Dehghan, M., Newman, T. B., Bentley, J. P., & Park, K. T. (2019). Association of opioid prescriptions from dental clinicians for us adolescents and
References Baker, C., & Wong, D. (1987). Q.U.E.S.T.: A process of pain assessment in children. Orthopaedic Nursing, 6(1), 11–21. Becker, D. E. (2010). Pain management: Part 1: Managing acute and postoperative dental pain. Anesthesia Progress, 57(2), 67–80. Buffington, D. E., Lozicki, A., Alfieri, T., & Bond, T. C. (2019). Understanding factors that contribute to the disposal of unused opioid medication. Journal of Pain Research, 12, 725–732. Centers for Disease Control and Prevention. (2017). CDC Guideline for Prescribing Opioids for Chronic Pain. Retrieved from: https://www.cdc.gov/drugoverdose/ prescribing/guideline.html. (Accessed 3/13/19). Centers for Disease Control and Prevention. (2018). Calculating total daily dose of opioid for safer dosage. Retrieved from: https://www.cdc.gov/drugoverdose/pdf/ calculating_total_daily_dose-a.pdf. (Accessed 5/7/19). Champion, V. L., & Skinner, C. S. (2008). The health belief model. Health Behavior and Health Education: Theory, Research, and Practice, 4, 45–65. Clark, D. J., & Schumacher, M. A. (2017). America's opioid epidemic: Supply and demand considerations. Anesthesia and Analgesia, 125(5), 1667–1674. Dana, R., Azarpazhooh, A., Laghapour, N., Suda, K. J., & Okunseri, C. (2018). Role of dentists in prescribing opioid analgesics and antibiotics: An overview. Dental Clinics of North America, 62(2), 279–294. Denisco, R. C., Kenna, G. A., O'Neil, M. G., Kulich, R. J., Moore, P. A., Kane, W. T., ... Katz, N. P. (2011). Prevention of prescription opioid abuse: The role of the dentist. Journal of the American Dental Association, 142(7), 800–810. Deyo, R. A., Hallvik, S. E., Hildebran, C., Marino, M., Dexter, E., Irvine, J. M., ... Millet, L. M. (2017). Association between initial opioid prescribing patterns and subsequent long-term use among opioid-naive patients: A statewide retrospective cohort study. Journal of General Internal Medicine, 32(1), 21–27. Gandhi, T., & Best, K. (2015). Educate patients about proper disposal of unused Rx medications—for their safety. Current Psychiatry, 14(4), 60–67. Gupta, N., Vujicic, M., & Blatz, A. (2018). Opioid prescribing practices from 2010 through 2015 among dentists in the United States. The Journal of the American Dental Association, 149(4), 237–245.e236. Guy, G. P., Jr, Zhang, K., Bohm, M. K., Losby, J., Lewis, B., Young, R., ... Dowell, D.
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Report, 66, 265–269. Suda, K. J., Durkin, M. J., Calip, G. S., Gellad, W. F., Kim, H., Lockhart, P. B., ... Thornhill, M. H. (2019). Comparison of opioid prescribing by dentists in the United States and England. JAMA Network Open, 2(5), e194303. Volkow, N. D., McLellan, T. A., Cotto, J. H., Karithanom, M., & Weiss, S. R. B. (2011). Characteristics of opioid prescriptions in 2009. JAMA, 305(13), 1299–1301.
young adults with subsequent opioid use and abuse. JAMA Internal Medicine, 179(2), 145–152. Seymour, R., Blair, G., & Wyatt, F. (1983). Post-operative dental pain and analgesic efficacy Part II Analgesic usage and efficacy after dental surgery. British Journal of Oral Surgery, 21(4), 298–303. Shah, A., Hayes, C. J., & Martin, B. C. (2017). Characteristics of initial prescription episodes and likelihood of long-term opioid use. MMWR. Morbidity and Mortality Weekly
9
Contents lists available at ScienceDirect
Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
A randomized pilot program to reduce opioid use following dental surgery and increase safe medication return
T
⁎
Karen J. Derefinkoa, , Francisco I. Salgado Garcíaa, Karen C. Johnsona, Sarah Handa, James G. Murphyb, Meghan McDevitt-Murphyb, Katie J. Sudac, Frank Andrasikb, Zoran Bursacd, Chi-Yang Chiua, Kevin Talleya, Jeffrey H. Brookse a
University of Tennessee Health Science Center, Department of Preventive Medicine, United States University of Memphis, Department of Psychology, United States c VA Center of Innovation for Complex Chronic Healthcare, Edward Hines, Jr. VA Hospital and University of Illinois at Chicago, Department of Pharmacy, Systems, Outcomes, and Policy, United States d Florida International University, Department of Biostatistics, United States e University of Tennessee Health Science Center, Department of Oral and Maxillofacial Surgery, United States b
H I GH L IG H T S
study examined the efficacy of opioid exposure reduction in dental patients. • The to treat analysis indicated a non-significant trend for treatment group effect. • Intent analysis showed that the treated group self-reported less opioid use. • Sensitivity • A brief intervention and non-narcotic pain medication may reduce opioid use.
A R T I C LE I N FO
A B S T R A C T
Keywords: Opioid Prevention Dental surgery Opioid exposure Opioid misuse
Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Because dentists represent some of the highest opioid prescribing medical professionals in the US, dental practices offer a critical site for intervention. The current study used a randomized clinical trial design to examine the efficacy of an opioid misuse prevention program (OMPP), presented as a brief intervention immediately prior to dental extraction surgery. The OMPP provided educational counseling about risks and appropriate use of opioid medication, as well as 28 tablets of ibuprofen (200 mg) and 28 tablets of acetaminophen (500 mg) for weaning off opioid medication. This was compared with a Treatment as Usual (TAU) control condition. Participants were individuals presenting for surgery who were eligible for opioid medication (N = 76). Follow up assessment was conducted at 1 week following surgery, with 4 individuals refusing follow up or not prescribed opioid. Intent to treat analysis indicated a non-significant treatment group effect (N = 72, Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use (in morphine milligram equivalents, MMEs) than the TAU group (37.94 vs. 47.79, effect size d = 0.42). Sensitivity analysis, excluding individuals with complications following surgery (n = 6) indicated a significant treatment group effect (N = 66, Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less MMEs than the TAU group (29.74 vs. 43.59, effect size d = 0.56). Results indicate that a 10-minute intervention and provision of non-narcotic pain medications may reduce the amount of self-administered opioid medication following dental surgery.
1. Introduction Dentists represent some of the highest opioid prescribing medical professionals in the US. Research indicates that dentists are second only ⁎
to family physicians as the most frequent prescribers of opioid medication (Rigoni, 2003; Volkow, McLellan, Cotto, Karithanom, & Weiss, 2011). Although dentists represent 9% of opioid prescribers, they prescribe 45% of opioids (McCauley et al., 2016), and while prescribing of
Corresponding author. E-mail address: kderefi[email protected] (K.J. Derefinko).
https://doi.org/10.1016/j.addbeh.2019.106190 Received 3 June 2019; Received in revised form 21 October 2019; Accepted 21 October 2019 Available online 23 October 2019 0306-4603/ © 2019 Elsevier Ltd. All rights reserved.
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Fig. 1. CONSORT Diagram.
1.1. The risks of opioid exposure
opioids is decreasing in the US, there is evidence of increasing rates in dental settings (Gupta, Vujicic, & Blatz, 2018; Guy et al., 2017). Opioid prescription is especially common in maxillofacial surgery, as 85%–100% of dentists prescribe opioids to patients (Denisco et al., 2011; Moore, Nahouraii, Zovko, & Wisniewski, 2006). In addition, dentists and maxillofacial surgeons commonly prescribe hydrocodone and oxycodone, which are frequently misused (McCauley et al., 2016; Mutlu, Abubaker, & Laskin, 2013). This issue of opioid prescribing in dentistry is particularly problematic in the US; a recent study of prescribing rates suggests that in 2016, the proportion of prescriptions written for opioids by US dentists was 37 times greater than that for dentists in England (Suda et al., 2019).
Exposure to opioids is of critical importance to long-term outcomes. Research indicates that increased cumulative exposure (duration of administration and strength of dose) is associated with long-term opioid use. Medical claims research indicates that among opioid naïve patients (N = 536,767), those who fill opioid prescriptions one time are 2.9% likely to become long term users, whereas those who fill four or more times are 26.1% likely to use opioids long term (Deyo et al., 2017). Even acute and low-dose exposure appears to increase risk of longterm opioid use. In a medical records study derived from commercial health plan data (2006–2015; N = 1,294,247) individuals prescribed at least one day of opioids had a probability of continued opioid use at one year of 6.0%, and those prescribed eight days or more had a probability of continued use at one year of 30% (Shah, Hayes, & Martin, 2017). In a 2
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intervention (TAU; Treatment as Usual). Those in the OMPP received the intervention immediately following. Randomization was pre-determined using blocks of 6. Packets of study forms, which either included the intervention script (or not, for TAU) were stacked according to this scheme prior to the start of the study, so that the next packet in line for use determined randomization status. After randomization (and intervention, for those in the OMPP condition), participants responded to a knowledge questionnaire and received a $10 gift card. These procedures occurred during the waiting period immediately before surgery which is typically 45 min in duration. After study procedures were complete, the participant was moved to the operating room, sedated for surgery, and completed the rest of the surgical visit, which included receipt of opioid prescription. Opioid prescription dose and duration varied by severity of surgery, as decided by one of six surgeons on staff.
study of opioid prescribing in dental settings, of 14,888 individuals who received an opioid prescription, 6.9% received another opioid prescription between 90 and 365 days later, and 5.8% experienced one or more subsequent health care encounters with an opioid abuse-related diagnosis (as compared with 0.1% and 0.4% for a non-opioid exposed control) (Schroeder, Dehghan, Newman, Bentley, & Park, 2019). 1.2. The role of dentists in opioid use reduction Recent prescription guidelines for dentists have recommended limiting opioid prescribing and encouraging combined ibuprofen and acetaminophen for postoperative pain (Becker, 2010; Dana, Azarpazhooh, Laghapour, Suda, & Okunseri, 2018; Moore & Hersh, 2013). In addition, guidelines also encourage patient education on appropriate use of opioids, opioid disposal, and the risks of combining opioids with sedatives (Clark & Schumacher, 2017; Gandhi & Best, 2015), but to date, little work has examined brief intervention to reduce adverse consequences (Kennedy-Hendricks et al., 2016; McCauley, Back, & Brady, 2013).
2.2.2. Follow up phone call Study staff blinded to treatment condition called participants seven days after baseline to complete follow up questionnaires. Participants received a $20 gift card upon completion of the seven-day follow-up.
1.3. The current study 2.3. Intervention conditions The current study was a randomized clinical pilot trial exploring the efficacy of a patient-based psychoeducational and pharmacological opioid misuse prevention program (OMPP), administered to dental patients immediately prior to tooth extraction surgery, relative to a control group receiving treatment as usual (TAU). We hypothesized that patients who received the OMPP would report lower use of opioid medication post-surgery (i.e., fewer morphine milligram equivalents, or MMEs) and higher rates of safe disposal of unused opioid than patients who received TAU.
2.3.1. Opioid misuse prevention program (OMPP) The OMPP was developed based upon the Health Belief Model (Champion & Skinner, 2008), and consisted of two components: psychoeducation material presented by an interventionist, and a seven-day supply of acetaminophen (500 mg every 6–8 h PRN) and ibuprofen (200 mg every 6–8 h PRN) provided in a blister pack for optional use in weaning off opioid medication. The psychoeducation session included a 10-minute discussion (with active participation from the patient) of multiple topics based upon recommendations in the literature (Becker, 2010; Clark & Schumacher, 2017; Gandhi & Best, 2015): Importance: Opioids prescribed by dentists can be the initial exposure point for individuals. Tolerance and Use Disorder: Tolerance can begin quickly and lead a person to use more opioid. Consequences of Concomitant Alcohol/ Drug Use: Slowed heart rate, coma, death. Appropriate Use of Opioid Pain Medication: Patients are not required to use all prescribed opioid. We advised participants that on the second day following surgery if they are at a five or lower on the Wong-Baker Faces Pain Rating Scale (Baker & Wong, 1987), they should transition to acetaminophen and ibuprofen to reduce risk for becoming dependent. Appropriate Disposal: Dangers of keeping medication (inadvertent ingestion, legal issues with selling/ giving to someone else). Participants were provided a list of local opioid takeback sites, which included pharmacies (n = 6) and law enforcement locations (n = 11), and a handout with a summary of the session material (see Appendix).
2. Material and methods 2.1. Participants Participants were recruited at an oral and maxillofacial surgery clinic at a health science university in the Southern US. IRB approval was obtained. The study was conducted between December 2017 and July 2018. Prescriptions for opioid medication following surgery are standard at this practice. Patients were eligible to participate if they were 18 years of age or older, presented for dental surgery that would result in opioid prescription, and had a phone number for follow up assessment. Participants were excluded if they reported currently taking opioids or had contra-indications to opioids, acetaminophen, or ibuprofen. Staff at the dental clinic identified 112 interested participants who were approached for the study. Of these, 76 were randomized, 72 completed the follow up (intent to treat analysis), and 66 did not have post-surgical complications (sensitivity analysis; see Fig. 1).
2.3.2. Treatment as usual (TAU) Those randomized to the TAU group did not receive any psychoeducation or acetaminophen/ibuprofen from the study interventionist. They received usual care from their dental providers.
2.2. Procedures 2.2.1. Study visit on surgery day All patients presenting for surgery received brief instructions from the clinic staff when they presented for surgery to engage in nonpharmacological activities to promote comfort (e.g., saltwater rinse, soft foods, and cold compress) following surgery. This was typical clinic practice, and was not changed during the administration of these study procedures. After the patient checked in, staff at the dental clinic referred interested patients to the research interventionist, a bachelor’s level individual trained on the study protocol, before interaction with the dental surgeon. The interventionist screened for eligibility in a private room. Eligible participants provided informed consent and completed baseline assessment. Next, participants were randomized to either the Opioid Misuse Prevention program (OMPP; 10 min in duration) or no
2.4. Measures pre-surgery 2.4.1. Demographics This questionnaire included age, gender, race/ethnicity, marital status, household income, highest level of education, and prior medical use of opioids during the past six months (yes/no). 2.4.2. Knowledge questionnaire This questionnaire included 5 open-ended questions relevant to the OMPP to establish intervention comprehension immediately following administration. Questions included (1) definition of tolerance, (2) timeframe of tolerance development, (3) importance of tolerance to the development of opioid use disorder, (4) classification of alcohol and 3
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Table 1 Unadjusted comparisons between treatment and control groups (N = 76). Variable
Gender Male Female Transgender Race/Ethnicity Caucasian African American Hispanic or Latino Other Marital Status Married Widowed Divorced Separated Single Household Income Unsure < $10,000 $10,000–$19,999 $20,000–$29,999 $30,000–$39,999 $40,000–$49,999 $50,000–$59,999 $60,000–$69,999 $70,000–$79,999 $80,000–$89,999 $90,000–$99,999 > $100,000 Education 8th grade or less 9th–11th grade 12th grade/GED Associate’s degree Vocational/trade school Some college Bachelor's Graduate Refused to Answer Medication type prescribed Hydrocodone 5/325 mg Oxycodone 5/325 mg Not prescribed Previous use of opioids for medical reason Variable Age
Treatment (n = 38)
Control (n = 38)
χ2
df
p
2.13
2
0.3455
9.24
3
0.0263
6.59
4
0.1592
7.91
10
0.6372
10.40
7
0.1670
N
%
N
%
15 22 1
40% 58% 3%
11 27 0
29% 71% 0%
8 27 0 3
21% 71% 0% 8%
16 15 3 4
42% 40% 8% 11%
7 1 1 1 28
18% 3% 3% 3% 74%
8 5 4 2 19
21% 13% 11% 5% 50%
3 10 5 5 4 6 3 1 0 1 0 0
8% 26% 13% 13% 11% 16% 8% 3% 0% 3% 0% 0%
2 4 9 7 4 3 3 2 0 2 1 1
5% 11% 24% 18% 11% 8% 8% 5% 0% 5% 3% 3%
1 4 11 4 5 8 5 0 0
3% 11% 29% 12% 13% 21% 13% 0% 0%
0 1 10 3 2 14 3 4 1
0% 3% 27% 8% 5% 38% 8% 11% 3% 0.59
2
0.9708
22 14 2 29 Treatment (n = 36) Mean 39.71
58% 37% 5% 81%
23 13 2 28 Control (n = 36) Mean 42.95
61% 34% 5% 78%
0.84
1
0.772
SD 18.72
t -0.77
df 74
p 0.4421
SD 17.78
Note: Descriptive group difference analysis results were not different between the enrolled sample (N = 76) and that which was used in the outcomes analysis (N = 72) (data not shown).
2.5. Measures post-surgery
benzodiazepines, and (5) risks associated with mixing opioids and alcohol or benzodiazepines. These responses were coded as correct (1) or incorrect (0) and summed to create a score ranging from 0 to 5. Cronbach’s alpha = 0.67.
2.5.1. Prescribed and self-administered opioid medication This questionnaire asked about the opioid prescribed (type, quantity, and dose; confirmed via medical chart), which served to establish the severity of the surgery (Malamed, 2019; Seymour, Blair, & Wyatt, 1983), and the number of pills self-administered after surgery. Dose and number of pills prescribed and self-administered were used to calculate morphine milligram equivalents (MMEs) for each variable using the scales provided by the Centers for Disease Control and Prevention: Hydrocodone/Acetaminophen 5 mg/325 mg tablets were multiplied by 1, and Oxycodone/Acetaminophen 5 mg/325 mg tables were multiplied by 1.5 to reflect differing MMEs across these medications (Centers for Disease Control and Prevention, 2018). This provided a standardized value for opioid medication.
2.4.3. Non-opioid pain management Participants were asked about awareness of non-opioid alternatives to managing pain after surgery (acetaminophen, ibuprofen, and nonpharmacological methods). Responses were coded as aware (1) or not aware (0).
2.4.4. Leftover opioid disposal We asked participants about the most appropriate method for disposing of leftover opioid medication following surgery, and what participants predicted they would do with their leftover opioids. Responses were coded as appropriate disposal method (1) or inappropriate (0).
2.5.2. Knowledge questionnaire Re-administered at the follow up. Cronbach’s alpha for follow up = 0.60. 4
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The OMPP and TAU groups were not significantly different in terms of MMEs prescribed (MOMPP = 98.65 and MTAU = 91.00, t(70) = 0.81, p = .4232) or worst pain experienced after surgery (MOMPP = 6.54 and MTAU = 6.60, t(70) = −0.09, p = .9285). In addition, those in the OMPP group were more likely to have used acetaminophen (OMPP = 70% and TAU = 31%, χ2 = 10.86, df = 1, p = .0010), and to have used ibuprofen (OMPP = 84% and TAU = 46%, χ2 = 11.50, df = 1, p = .0007) to manage pain. Groups were not different in terms of use of non-medication strategies to manage pain (OMPP = 76% and TAU = 74%, χ2 = 0.11, df = 1, p = .8917).
2.5.3. Pain after surgery Participants were asked about pain rating following surgery using the Wong Baker pain scale with anchors of 0 = no pain and 10 = worst pain (Baker & Wong, 1987). 2.5.4. Non-Opioid pain management We asked participants if they used (1) acetaminophen, (2) ibuprofen, or (3) non-pharmacological forms of non-opioid pain management (yes/no) following surgery. 2.5.5. Leftover opioid disposal At post-test, for those with leftover medication, participants selfreported their actual opioid disposal method or their plans to dispose of leftover opioids. Responses were coded as appropriate disposal method (1) or inappropriate (0).
3.3. Opioid medication self-administration A multivariable linear regression was conducted to examine whether treatment contributed to differences in opioid self-administration. Opioid medication data were standardized across medication type into morphine milligram equivalents (MMEs). We tested for assumptions (e.g., multicollinearity between the independent variables, linearity, and normality assumption), and determined that no changes to analyses were deemed necessary.
2.6. Statistical data analysis All analyses were performed using SPSS software. We conducted univariate comparisons using t-tests and χ2 tests to assess baseline differences between OMPP and TAU. To examine the primary outcome, we used multivariable linear regression to investigate the effect of the treatment group on MMEs selfadministered following the surgery. We added two control variables to analyses: prescribed MMEs following the surgery, and participant-reported pain following surgery. Intent to treat analyses were conducted with the entire eligible sample (N = 72) and a sensitivity analysis excluding those who had complications following surgery (e.g., alveolar osteitis, N = 66). All associations were considered significant at the alpha level of 0.05.
3.3.1. Intent to treat analysis (N = 72; Table 3) Control variables included prescribed MMEs (as a proxy for surgery severity), worst pain experienced after surgery self-reported by the participant, and race (identified as a significant group difference in baseline adjusted group comparisons). The regression model predicting MMEs self-administered was significant (F(4,71) = 14.25, p < .0001, adjusted R2 = 0.43). Results indicated a non-significant trend for treatment group effect (Beta = 0.16, p = .0835), such that the OMPP group self-reported less opioid use than the TAU group (37.94 MMEs vs. 47.79 MMEs, effect size d = 0.42, 95% CI : −0.05 to 0.88). MMEs prescribed and worst pain after surgery accounted for significant variance in the model (Beta = 0.44, p < .0001 and Beta = 0.41, p < .0001, respectively). Race was not a significant predictor of MMEs self-administered (Beta = −0.11, p = .2322).
3. Results 3.1. Descriptive statistics on demographic and opiate use variables Univariate comparisons between treatment and control groups were conducted using the entire enrolled sample (N = 76). The sample was 34% male, mean age 41.33 (SD = 18.21), with 28% having a high school level education or less and 37% with a household income of less than $20,000 per year. There were no significant treatment group differences in gender, marital status, household income, education, opioid medication type prescribed, previous use of prescribed opioids, or age. Results indicated significant group difference in race (χ2 = 9.24, df = 3, p = .0263); the OMPP group had a lower proportion of Caucasians than the TAU group (21% vs 42%, respectively) and a higher proportion of African Americans than the TAU group (71% vs. 40%, respectively; see Table 1 for descriptive information).
3.3.2. Sensitivity analysis (N = 66; Table 4) This analysis was conducted excluding individuals who presented with complications from surgery (n = 6) given that these individuals were still in recovery at the time of follow up. Control variables included total prescribed MMEs, worst pain after surgery self-reported by the participant, and race. The regression model predicting MME selfadministered was significant (F(4,65) = 8.24, p < .0001, adjusted R2 = 0.31). Results indicated a significant treatment group effect (Beta = 0.24, p = .0259), such that the OMPP group self-reported significantly less opioid use than the TAU group (29.74 MMEs vs. 43.59 MMEs, effect size d = 0.56, 95% CI: 0.07 to 1.05). MMEs prescribed and worst pain after surgery also accounted for significant variance in the model (Beta = 0.32, p = .0034 and Beta = 0.40, p = .0003, respectively). Race was not a significant predictor of MMEs self-administered (Beta = −0.11, p = .2912).
3.2. Treatment factors 3.2.1. Surgery day Group differences in potential treatment factors were examined (Table 2). Following the intervention delivery, those who received the OMPP (vs. TAU) had more knowledge of the risks associated with opioid use (MOMPP = 3.70 and MTAU = 1.56, t(69) = 7.65, p < .0001). Further, those in the OMPP group were more likely to be aware of nonmedication pain management strategies (OMPP = 84% and TAU = 50%, χ2 = 9.23, df = 1, p = .0024).
3.4. Leftover opioid disposal (Table 5) Following the intervention on surgery day, those in the OMPP group were more likely to be aware of the appropriate method for leftover opioid disposal (OMPP = 97% and TAU = 47%, χ2 = 22.82, df = 1, p < .0001), and had a higher likelihood of predicting that they would dispose of any leftover opioid appropriately (OMPP = 76% and TAU = 21%, χ2 = 21.51, df = 1, p < .0001). At 1-week follow up, those who received the OMPP were more likely to have a plan to dispose of any unused opioid appropriately (OMPP = 60% and TAU = 21%, χ2 = 8.21, df = 1, p = .0042). Groups were not significantly different in terms of medication return rates (OMPP = 21% and TAU = 4%, χ2 = 3.69, df = 1, p = .0548), but this difference represented an effect size of d = 0.49.
3.2.2. One week follow-up At the 1-week follow-up phone call, those who received the OMPP (vs. TAU) had more knowledge of the risks associated with opioid use (MOMPP = 3.11 and MTAU = 1.97, t(70) = 3.50, p = .0008). Repeated measures suggested that knowledge decreased for the OMPP group, F (1,36) = 12.76, p = .0010, and increased for the TAU group F (1,33) = 6.00, p = .0198. 5
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Table 2 Comparisons of treatment factors (N = 72). Pre-Surgery Treatment
Knowledge following intervention
Awareness of non-opioid strategies to manage pain
Control
Group n
Mean
SD
Group n
Mean
SD
df
t
p
37
3.70
1.33
34
1.56
0.99
69
7.65
0.0000
Group n
n
%
Group n
n
%
df
χ2
p
37
31
84%
35
17
50%
1
9.23
0.0024
One Week Follow-Up Treatment
Knowledge at 1-week follow-up Total MMEs prescribed Pain after surgery
Use of acetaminophen Use of ibuprofen Use of non-pharmacological strategies to manage pain
Control
Group n
Mean
SD
Group n
Mean
SD
df
t
p
37 37 37
3.11 98.65 6.54
1.61 40.85 2.79
35 35 35
1.97 91.00 6.60
1.07 39.63 2.82
70 70 70
3.50 0.81 −0.09
0.0008 0.4232 0.9285
Group n
N
%
Group n
N
%
df
χ2
p
37 37 37
26 31 28
70% 84% 76%
35 35 35
11 16 26
31% 46% 74%
1 1 1
10.86 11.50 0.02
0.0010 0.0007 0.8917
Note: MMEs = Morphine Milligram Equivalents. Significant predictors presented in bold type. One control participant’s data was not recorded on the knowledge measure Pre-Surgery, resulting in a smaller n of 34.
4. Discussion
opioid use, yet achieved scores similar to CDC recommendations (20–50 morphine milligram equivalents [MME]/day) (Centers for Disease Control and Prevention, 2017) for safety. However, it should be noted that beta weights for pain score and MMEs were larger than the beta weight for treatment group. This is expected, given the importance of pain and availability of opioid medication to opioid medication use. In addition to reductions in opioid use, the OMPP produced significant gains in leftover opioid disposal awareness and intentions. The effect size d = 0.49 for safe medication return suggests that even within one week, return rate group differences were considerable. Removal of available opioid from the community is a target of educational campaigns (Inciardi, Surratt, Lugo, & Cicero, 2007), but often patients do not know where to safely return their unused opioids. We provided participants a handout listing confirmed medication return locations in the city. This may be an important prevention strategy given that most pharmacies do not accept unused medication. Efforts to and incentivize the use of medication take-back programs and facilities could further decrease opioid diversion, a major factor in OUD (Buffington, Lozicki, Alfieri, & Bond, 2019; McCabe et al., 2017). Safe storage and disposal has been a target of other existing work which did not find significant return effects (McCauley et al., 2013).
Reducing cumulative exposure to opioids is of clear importance given high rates of long-term use. Although guidelines encourage nonnarcotic analgesics (Moore & Hersh, 2013), there remains widespread opioid prescribing in dental surgery settings to manage moderate to severe pain. The results of this pilot trial add to the emergent evidence supporting brief, patient-based interventions targeting inappropriate use of opioids following surgery (McCauley et al., 2013), and may be one of the first trials of brief intervention which directly targets reductions in prescribed opioid use. Our psychoeducational and pharmacological intervention addressed multiple targets, including describing the risks associated with prolonged opioid medication use and the benefits of acetaminophen and ibuprofen to wean off opioid medication. Opioid Misuse Prevention Program (OMPP) participants had higher knowledge scores, higher awareness of non-opioid pain relief strategies, and higher frequency of use of these non-opioid strategies post-surgery compared to Treatment as Usual (TAU) participants. These findings suggest that dental patients benefit from information provided in a brief format prior to surgery to promote non-opioid alternatives to pain management. As predicted, patients in the OMPP group self-reported less opioid use than patients in the TAU group. In the sensitivity analysis, the mean group difference between OMPP and TAU (29.74 vs. 43.59 MMEs) represents a medium sized effect of 0.56, which is promising for a brief intervention. The OMPP intervention did not target a clear limit to
4.1. Strengths and limitations This study had several strengths, including a diverse sample and the evaluation of a brief and practical intervention that has the potential for
Table 3 Intent to treat analysis of the prediction of cumulative morphine milligram equivalents (MMEs) self-administered following Opioid Misuse Prevention Program (OMPP) treatment vs. Treatment as Usual (TAU) control (N = 72).
Treatment group MMEs prescribed Worst pain after surgery Race
B
SEB
Beta
t
p
Effect Size d
Effect Size 95% CI
12.51 0.43 5.80 −5.05
7.12 0.09 1.32 4.19
0.16 0.44 0.41 -0.11
1.76 4.70 4.40 −1.21
0.0835 0.0000 0.0000 0.2322
0.42 1.11 1.04 -0.29
−0.05 to 0.88 0.61 to 1.60 0.54 to 1.53 −0.75 to 0.18
Note: OMPP = Opioid Misuse Prevention Program. TAU = Treatment as Usual. MMEs = morphine milligram equivalents. Significant predictors presented in bold type. Effect Size d was computed from t-score and sample size (Lipsey & Wilson, 2001). 6
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Table 4 Sensitivity analysis of the prediction of cumulative MMEs self-administered following OMPP treatment vs. TAU control (N = 66).
Treatment group MMEs prescribed Worst pain after surgery Race
B
SEB
Beta
t
p
Effect Size d
Effect Size 95% CI
15.30 0.28 4.74 −4.10
6.70 0.09 1.22 3.81
0.24 0.32 0.40 -0.11
2.28 3.05 3.88 −1.07
0.0259 0.0034 0.0003 0.2912
0.56 0.75 0.96 -0.26
0.07 to 1.05 0.25 to 1.25 0.45 to 1.47 −0.75 to 0.22
Note: OMPP = Opioid Misuse Prevention program. TAU = Treatment as Usual. MMEs = morphine milligram equivalents. Only individuals without extended prescriptions due to complications were eligible for analysis. Significant predictors presented in bold type. Effect Size d was computed from t-score and sample size (Lipsey & Wilson, 2001).
fidelity was not conducted in this pilot, which may have resulted in drift. However, this intervention was scripted (content designed to be delivered verbatim), making it unlikely administration varied considerably. Additionally, we did not control for contact time in the TAU group; it is possible that changes in opioid self-administration are partially due to time with the interventionist. Finally, the OMPP was delivered by a research interventionist, thereby limiting our ability to describe disseminability. Future work may benefit from having dental staff deliver the OMPP to assess distribution to broader populations.
wide dissemination across dental settings. Further, our study employed measures of knowledge, intentions, and behavior, which together demonstrate the mechanisms of change that may be at work following this intervention. Results of this study present some limitations. First, we used selfreported pill counts to calculate opioid use. Future work would benefit from in person pill counts to verify remaining medication. In addition, the setting where patients were recruited had a lower household income and lower education than other dental surgery settings, limiting generalizability. Moreover, the one-week follow-up timeframe may have been too short to detect specific outcomes, as some patients were ineligible for analysis due to complications that resulted in more opioid prescribed and due to the lack of sufficient time to return unused opioids to a takeback location. However, the first week following surgery is a critical time for the development of opioid tolerance, and our results demonstrate effective knowledge acquisition in the OMPP group which should reduce risk for subsequent misuse. Further, although the knowledge measure designed only to test for intervention effect, the Cronbach’s alpha was low. Additionally, we did not do a pre-test of knowledge prior to the intervention due to time constraints with patients prior to surgery. Our team decided that confirmation of the treatment effect immediately following intervention was ultimately the most important data given questions regarding possible retention of material prior to anesthesia. Furthermore, acetaminophen and ibuprofen was provided only to the treatment group, which introduced an accessibility bias. The alternative would have required counseling the control group given the contraindication to use concurrently with hydrocodone or oxycodone, and we did not wish to blur the distinction between groups. In addition,
4.2. Conclusions This study explored the use of a brief psychoeducational and pharmacological intervention prior to dental surgery to reduce the use of opioids post-surgery and increase the safe return of leftover opioid medication. Results indicated that this Psychoeducational and pharmacological program reduced cumulative opioid self-administration and increased awareness and intentions to return unused opioid medication to a takeback location. While treatment elements (counseling vs. non-opioid medication) could not be evaluated for individual effects, future work may isolate these therapeutic elements to establish their individual merit. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Appendix Tips for a Speedy and Safe Recovery 1. Take your pain medication as prescribed
• Follow your physician’s guidelines for taking your pain medication • Do not take more than prescribed Table 5 Leftover Opioid Disposal. Treatment
Control
Group n
n
%
Group n
n
%
df
χ2
p
Effect Size d
Effect Size 95% CI
Pre-Surgery Aware of leftover opioid disposal Predicted leftover opioid disposal
37 37
36 28
97% 76%
34 34
16 7
47% 21%
1 1
22.82 21.51
0.0000 0.0000
1.38 1.32
0.81 to 1.94 0.76 to 1.88
One Week Follow-Up Actual leftover opioid disposala Plans for leftover opioid disposalb
39 25
6 15
21% 60%
27 28
1 6
4% 21%
1 1
3.69 8.21
0.0548 0.0042
0.49 0.86
−0.01 to 0.98 0.27 to 1.44
Note: Post-surgery opioid disposal assessment questions not applicable to those who self-administered all of the opioid medication. a. Only individuals who had been prescribed opioid medication, had completed opioid medication administration, and had leftover medication were eligible for analysis. b. Only individuals who had been prescribed opioid medication, had leftover medication, and had not already returned medication were eligible for analysis. Significant predictors presented in bold type. Effect Size d was computed from chi-square values and sample sizes (Lipsey & Wilson, 2001). 7
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• Do not mix your pain medication with alcohol or other sedatives 2. Stop using the pain medication as soon as possible
• Identify where you are on the pain scale before you take pain medication again:
• If you are at a 5 or below on the pain scale, consider taking acetaminophen/ibuprofen instead of the pain medication 3. Take your leftover opioid to a takeback location
• The only safe place for leftover opioid medication is a takeback location • This removes the medication from circulation, and protects you from consequences 4. Questions?
• Talk to your dentist about any concerns you have. Your comfort and healing are important to us. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.addbeh.2019.106190.
(2017). Vital signs: Changes in opioid prescribing in the United States, 2006–2015. MMWR. Morbidity and Mortality Weekly Report, 66(26), 697. Inciardi, J. A., Surratt, H. L., Lugo, Y., & Cicero, T. J. (2007). The diversion of prescription opioid analgesics. Law Enforcement Executive Forum, 7(7), 127–141. Kennedy-Hendricks, A., Gielen, A., McDonald, E., McGinty, E. E., Shields, W., & Barry, C. L. (2016). Medication sharing, storage, and disposal practices for opioid medications among US adults sharing, storage, and disposal practices for opioids letters. JAMA Internal Medicine, 176(7), 1027–1029. Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis (Applied Social Research Methods) thousand oaks. CA: Sage Publications. Malamed, S. (2019). Handbook of local Anesthesia (7th ed.). Mosby. McCabe, S. E., West, B. T., Veliz, P., McCabe, V. V., Stoddard, S. A., & Boyd, C. J. (2017). Trends in medical and nonmedical use of prescription opioids among US adolescents: 1976–2015. Pediatrics. McCauley, J. L., Back, S. E., & Brady, K. T. (2013). Pilot of a brief, web-based educational intervention targeting safe storage and disposal of prescription opioids. Addictive Behaviors, 38(6), 2230–2235. McCauley, J. L., Hyer, J. M., Ramakrishnan, V. R., Leite, R., Melvin, C. L., Fillingim, R. B., ... Brady, K. T. (2016). Dental opioid prescribing and multiple opioid prescriptions among dental patients: Administrative data from the South Carolina prescription drug monitoring program. Journal of the American Dental Association, 147(7), 537–544. Moore, P. A., & Hersh, E. V. (2013). Combining ibuprofen and acetaminophen for acute pain management after third-molar extractions: Translating clinical research to dental practice. Journal of the American Dental Association, 144(8), 898–908. Moore, P. A., Nahouraii, H. S., Zovko, J. G., & Wisniewski, S. R. (2006). Dental therapeutic practice patterns in the U.S. I. Anesthesia and sedation. General Dentistry, 54(2), 92–98. Mutlu, I., Abubaker, A. O., & Laskin, D. M. (2013). Narcotic prescribing habits and other methods of pain control by oral and maxillofacial surgeons after impacted third molar removal. Journal of Oral and Maxillofacial Surgery, 71(9), 1500–1503. Rigoni, G. C. (2003). Drug Utilization for Immediate and Modified Release Opioids in the US. Retrieved from: https://wayback.archive-it.org/7993/20170404072744/, https://www.fda.gov/ohrms/dockets/ac/03/slides/. (Accessed 5/29/19). Schroeder, A. R., Dehghan, M., Newman, T. B., Bentley, J. P., & Park, K. T. (2019). Association of opioid prescriptions from dental clinicians for us adolescents and
References Baker, C., & Wong, D. (1987). Q.U.E.S.T.: A process of pain assessment in children. Orthopaedic Nursing, 6(1), 11–21. Becker, D. E. (2010). Pain management: Part 1: Managing acute and postoperative dental pain. Anesthesia Progress, 57(2), 67–80. Buffington, D. E., Lozicki, A., Alfieri, T., & Bond, T. C. (2019). Understanding factors that contribute to the disposal of unused opioid medication. Journal of Pain Research, 12, 725–732. Centers for Disease Control and Prevention. (2017). CDC Guideline for Prescribing Opioids for Chronic Pain. Retrieved from: https://www.cdc.gov/drugoverdose/ prescribing/guideline.html. (Accessed 3/13/19). Centers for Disease Control and Prevention. (2018). Calculating total daily dose of opioid for safer dosage. Retrieved from: https://www.cdc.gov/drugoverdose/pdf/ calculating_total_daily_dose-a.pdf. (Accessed 5/7/19). Champion, V. L., & Skinner, C. S. (2008). The health belief model. Health Behavior and Health Education: Theory, Research, and Practice, 4, 45–65. Clark, D. J., & Schumacher, M. A. (2017). America's opioid epidemic: Supply and demand considerations. Anesthesia and Analgesia, 125(5), 1667–1674. Dana, R., Azarpazhooh, A., Laghapour, N., Suda, K. J., & Okunseri, C. (2018). Role of dentists in prescribing opioid analgesics and antibiotics: An overview. Dental Clinics of North America, 62(2), 279–294. Denisco, R. C., Kenna, G. A., O'Neil, M. G., Kulich, R. J., Moore, P. A., Kane, W. T., ... Katz, N. P. (2011). Prevention of prescription opioid abuse: The role of the dentist. Journal of the American Dental Association, 142(7), 800–810. Deyo, R. A., Hallvik, S. E., Hildebran, C., Marino, M., Dexter, E., Irvine, J. M., ... Millet, L. M. (2017). Association between initial opioid prescribing patterns and subsequent long-term use among opioid-naive patients: A statewide retrospective cohort study. Journal of General Internal Medicine, 32(1), 21–27. Gandhi, T., & Best, K. (2015). Educate patients about proper disposal of unused Rx medications—for their safety. Current Psychiatry, 14(4), 60–67. Gupta, N., Vujicic, M., & Blatz, A. (2018). Opioid prescribing practices from 2010 through 2015 among dentists in the United States. The Journal of the American Dental Association, 149(4), 237–245.e236. Guy, G. P., Jr, Zhang, K., Bohm, M. K., Losby, J., Lewis, B., Young, R., ... Dowell, D.
8
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K.J. Derefinko, et al.
Report, 66, 265–269. Suda, K. J., Durkin, M. J., Calip, G. S., Gellad, W. F., Kim, H., Lockhart, P. B., ... Thornhill, M. H. (2019). Comparison of opioid prescribing by dentists in the United States and England. JAMA Network Open, 2(5), e194303. Volkow, N. D., McLellan, T. A., Cotto, J. H., Karithanom, M., & Weiss, S. R. B. (2011). Characteristics of opioid prescriptions in 2009. JAMA, 305(13), 1299–1301.
young adults with subsequent opioid use and abuse. JAMA Internal Medicine, 179(2), 145–152. Seymour, R., Blair, G., & Wyatt, F. (1983). Post-operative dental pain and analgesic efficacy Part II Analgesic usage and efficacy after dental surgery. British Journal of Oral Surgery, 21(4), 298–303. Shah, A., Hayes, C. J., & Martin, B. C. (2017). Characteristics of initial prescription episodes and likelihood of long-term opioid use. MMWR. Morbidity and Mortality Weekly
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