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American Society for Enhanced Recovery and Perioperative Quality Initiative-4 Joint Consensus Statement on Persistent Postoperative Opioid Use: Definition, Incidence, Risk Factors, and Health Care System Initiatives

Kent, Michael L. MD*; Hurley, Robert W. MD, PhD, FASA; Oderda, Gary M. PharmD, MPH; Gordon, Debra B. RN-BC, DNP, FAAN§; Sun, Eric MD, PhD; Mythen, Monty MBBS, MD, FRCA, FFICM, FCAI (Hon); Miller, Timothy E. MB, ChB*; Shaw, Andrew D. MB, FRCA, FFICM, FCCM#; Gan, Tong J. MD, MBA, MHS, FRCA**; Thacker, Julie K. M. MD††; McEvoy, Matthew D. MD‡‡; Argoff, Charles MD; Edwards, David A. MD, PHD; Geiger, Timothy M. MD, MMHC, FACS, FASCRS; Grant, Michael C. MD; Grocott, Michael BSc, MBBS, MD, FRCA, FRCP, FFICM; Gulur, Padma MD; Gupta, Ruchir MD; Hah, Jennifer M. MD, MS; Hedrick, Traci L. MD, MS, FACS, FASCRS; Holubar, Stefan D. MD, MS, FACS, FASCRS; Jayaram, Jennifer APRN, MSN; King, Adam B. MD; Mythen, Michael G. MBBS, MD, FRCA, FFICM, FCAI (Hon); Sun, Erin MD, PhD; Wu, Christopher L. MD; POQI-4 Working Group

doi: 10.1213/ANE.0000000000003941
Chronic Pain Medicine
Free
SDC
CME
Continuing Medical Education

Persistent postoperative opioid use is thought to contribute to the ongoing opioid epidemic in the United States. However, efforts to study and address the issue have been stymied by the lack of a standard definition, which has also hampered efforts to measure the incidence of and risk factors for persistent postoperative opioid use. The objective of this systematic review is to (1) determine a clinically relevant definition of persistent postoperative opioid use, and (2) characterize its incidence and risk factors for several common surgeries. Our approach leveraged a group of international experts from the Perioperative Quality Initiative-4, a consensus-building conference that included representation from anesthesiology, surgery, and nursing. A search of the medical literature yielded 46 articles addressing persistent postoperative opioid use in adults after arthroplasty, abdominopelvic surgery, spine surgery, thoracic surgery, mastectomy, and thoracic surgery. In opioid-naïve patients, the overall incidence ranged from 2% to 6% based on moderate-level evidence. However, patients who use opioids preoperatively had an incidence of >30%. Preoperative opioid use, depression, factors associated with the diagnosis of substance use disorder, preoperative pain, and tobacco use were reported risk factors. In addition, while anxiety, sex, and psychotropic prescription are associated with persistent postoperative opioid use, these reports are based on lower level evidence. While few articles addressed the health policy or prescriber characteristics that influence persistent postoperative opioid use, efforts to modify prescriber behaviors and health system characteristics are likely to have success in reducing persistent postoperative opioid use.

From the *Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina

Departments of Anesthesiology and Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, North Carolina

College of Pharmacy, University of Utah, Salt Lake City, Utah

§Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington

Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Palo Alto, California

University College London National Institute of Health Research (NIHR) Biomedical Research Centre, London, United Kingdom

#Department of Anesthesiology and Pain Medicine, University of Alberta, Edmonton, Alberta, Canada

**Department of Anesthesiology, Stony Brook School of Medicine, Stony Brook, New York

††Division of Advanced Oncologic and Gastrointestinal Surgery, Duke University Medical Center, Durham, North Carolina

‡‡Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee.

Published ahead of print 16 October 2018.

Accepted for publication October 16, 2018.

Funding: The PeriOperative Quality Initiative (POQI)-4 consensus conference was supported by unrestricted educational grants from the American Society for Enhanced Recovery (ASER) and the POQI, which have received grants from Baxter, Bev MD, Cadence, Cheetah Medical, Edwards, Heron Pharmaceutical, Mallinckrodt, Medtronic, Merck, Pacira, and Trevena.

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website.

A full list of contributors can be found at the end of the article.

Reprints will not be available from the authors.

Address correspondence to Michael L. Kent, MD, Department of Anesthesiology, Duke University Medical Center, 3094 #4, Durham, NC 27710. Address e-mail to Michael.kent@duke.edu.

See Editorial, p

In light of the opioid epidemic in the United States, anesthesiologists are uniquely positioned to play a role in reducing opioid use for surgical patients, for whom opioids continue to be first-line analgesic agents and nonopioid medications are inconsistently prescribed.1,2 Crucially, several studies suggest that surgery is associated with an increased risk of long-term opioid use, a phenomenon known as persistent postoperative opioid use.3,4 As such, efforts to reduce the risk of persistent postoperative opioid use can have a direct effect on opioid use at the population level. In addition, decreasing the risk of persistent postoperative opioid use could also have indirect benefits in reducing population-level opioid use by reducing the incidence of diversion, particularly in light of studies suggesting a substantial amount of opioid overprescription and large amounts of unused pills among patients undergoing surgery.5–7

Efforts to address persistent postoperative opioid use have faced several limitations. First, the term remains poorly defined in the literature (Table 1). Additionally, it is likely driven by a wide variety of causal factors, including patient characteristics (eg, comorbidities), nature of the patient’s surgery, and health system characteristics (eg, clinical pathways and health legislation).17 Indeed, 1 stated benefit of initiatives such as the perioperative surgical home and enhanced recovery after surgery programs is the possibility that they may reduce the risk of persistent postoperative opioid use. As a result of these limitations, to date, there have been few systematic attempts to characterize the incidence of persistent postoperative opioid use and the associated patient, surgery, and health care system characteristics that may serve as risk factors. As part of the fourth American Society for Enhanced Recovery Perioperative and Quality Initiative-4 working group, we used a systematic literature review and modified Delphi Grading of Recommendations Assessment, Development and Evaluation consensus process to address the following questions:

Table 1.

Table 1.

  • What is the definition and incidence of persistent postoperative opioid use?
  • What are patient and surgery characteristics associated with persistent postoperative opioid use?
  • What health system characteristics are associated with persistent postoperative opioid use?
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METHODS

Expert Group and Process

The Perioperative Quality Initiative-4 conference was convened with the goal of advancing the understanding of opioid use throughout all perioperative phases. This article is the result of a modified Delphi analysis performed by the Perioperative Quality Initiative-4 working subgroup, whereby evidence pertaining to perioperative opioid use was reviewed. The Delphi method is detailed in the first article in this series.18 Twenty-four experts in anesthesiology, nursing, surgery, pharmacy, and pain medicine met on January 4–6, 2018 in Nashville, TN. Each workshop participant was chosen based on a record of significant clinical and/or research experience in perioperative pain medicine. We systematically reviewed the literature pertaining to the definition/incidence of and risk factors for persistent postoperative opioid use within specific surgical subtypes. In the interest of feasibility, the workgroup focused on 5 commonly performed surgery subtypes affecting major body regions and tissue types, including joint arthroplasty, mastectomy, spine surgery, thoracic surgery, and abdominopelvic surgery. Based on the literature review described next, the working group arrived at a consensus regarding the (1) definition and incidence of persistent postoperative opioid use, (2) patient and surgeries associated with persistent postoperative opioid use, and (3) health care system characteristics associated with persistent postoperative opioid use. These results were presented to the Perioperative Quality Initiative-4 collaborative, and the following conclusions and recommendations reflect the consensus of the collaborative.

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Literature Review

Data Sources and Search.

We complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines conducting a systematic search of available literature pertaining to the incidence of and risk factors for persistent postoperative opioid use. We searched MEDLINE, Embase, and Scopus within the past 10 years (January 1, 2007 to February 2, 2018) restricting articles to the English language (Supplemental Digital Content, PPOU Database Search, http://links.lww.com/AA/C663). Due to the recent expansion of enhanced recovery after surgery programs, comprehensive acute pain management programs, and recent attention to opioid over prescription, the working group chose a 10-year search strategy. As seen here, only 1 of 46 articles that met inclusion criteria was published before 2010. We constructed a search strategy using terms focusing on adults undergoing arthroplasty, mastectomy, spine surgery, thoracic surgery, and abdominopelvic surgery (population), postoperative opioids (exposure), and the incidence of or risk factors for persistent postoperative opioid use (outcome). Because evidence for contributory health care system characteristics to persistent postoperative opioid use is emerging, we decided to narratively review this topic and offer recommendations for research and policy considerations.

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Inclusion Criteria and Outcome Definition.

We included studies of adults within the United States and Canada undergoing total knee/hip arthroplasty, mastectomy, thoracic surgery, abdominopelvic surgery, and spine surgery. The United States and Canada were chosen due to similar opioid-prescribing practices and being characterized by the highest opioid consumption in the world.19,20 We required that the patient’s opioid use or exposure be measured during the postdischarge period and include the incidence of and/or risk factors for opioid use or prescription filling after 90 days postoperatively. There was no time limit on follow-up for this initial search.

From our Perioperative Quality Initiative-4 working group, 1 reviewer (M.L.K.) assessed 2540 abstracts, and 2478 were excluded for not meeting content inclusion criteria. Sixty-two titles underwent full-text review by 2 reviewers (M.L.K. and G.M.O.), after which 46 studies met inclusion criteria. The primary set of outcomes included the incidence of persistent postoperative opioid use (as defined by the given study) in opioid-naïve and opioid-exposed patients and patient/surgical characteristics associated with the development of persistent postoperative opioid use across all patients. These outcomes were obtained for each of the aforementioned surgical subtypes.

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Quality Assessment.

Two reviewers (M.L.K. and G.M.O.) independently assessed the quality of studies. The Grading of Recommendations Assessment, Development and Evaluation assessment for prognostic studies set forth by Iorio et al21 and Huguet et al22 was used to evaluate study limitations, indirectness of evidence, imprecision, and publication bias.21,22 Limitations were primarily assessed as risk of bias, with particular attention paid to appropriate study sample and adjustment for confounding prognostic factors. Indirectness of evidence was rated on whether study data corresponded to the population of interest and at the same time using appropriate measures. Imprecision was evaluated based on variables such as appropriate sample size and observation of CIs for outcomes. Studies were also evaluated based on the presence of univariate/multivariate analysis. After Grading of Recommendations Assessment, Development and Evaluation evaluation of individual articles, patient characteristics associated with persistent postoperative opioid use were reviewed to generate a list of the most common factors for each surgical subtype. Based on the aggregate quality of evidence, each patient characteristic was also evaluated and assigned a Grading of Recommendations Assessment, Development and Evaluation score. In the case of disagreement, a third reviewer (R.W.H.) functioned as a tie-breaker.

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Data Extraction and Synthesis.

One of the reviewers (M.L.K.) extracted pertinent study characteristics using an agreed-on extraction template. Data included study design, setting, patient population, number of patients, incidence of persistent postoperative opioid use in opioid-naïve and tolerant patients per the study author’s definition, and risk factors.

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RESULTS

Figure 1.

Figure 1.

After full-text review, 46 studies met inclusion criteria across prespecified surgical subtypes (Figure 123; Supplemental Digital Content, Table 1, http://links.lww.com/AA/C663). The majority of studies were retrospective, with data originating from institutional records or external databases (ie, insurance claims, state prescription monitoring, etc). Studies addressed patient/surgical characteristics associated with persistent postoperative opioid use, the incidence of persistent postoperative opioid use, or both. Of note, certain retrospective cohort studies included numerous surgical subtypes and patient/surgical characteristics associated with persistent postoperative opioid use, and such studies were analyzed in aggregate.8,9,12 In these scenarios, manuscripts underwent Grading of Recommendations Assessment, Development and Evaluation assessment for each respective surgical subtype, but the lack of surgery-specific analysis within such mixed surgical studies was taken into account when assessing the quality of evidence. No studies received an assessment of “high quality” in part due to variability in persistent postoperative opioid use definition, sample size, and lack of representation of the entire surgery-specific population.

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Definition of Persistent Postoperative Opioid Use

There was no consistent definition of persistent postoperative opioid use across the studies due to variations in how opioid use was measured (eg, prescriptions written, prescriptions filled, or opioid usage per patient report), the starting and ending points during which opioid use was measured (eg, 90 days postoperatively until 1 postoperative year), and the level of opioid use required to meet the threshold for persistent postoperative opioid use. Despite this variation, a notable proportion of articles focused on the time period from 90 postoperative days to 1 postoperative year.3,8–12,15,24–45

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Incidence of Persistent Postoperative Opioid Use

Due to the variability in time frame used to describe persistent postoperative opioid use and the trends noted earlier, the consensus group chose to initially focus on studies that characterized the incidence of persistent postoperative opioid use from 90 days until 1 year postoperatively as patients using opioids longer than 1 year postoperatively may have had other confounding painful conditions not linked to the surgical insult for which they were using opioids.

Table 2.

Table 2.

Differences were noted among each surgical subtype, and a wide range of reported incidence rates were likely due to variability among studies, including sample size, definition of persistent postoperative opioid use, and total number of institutions represented in any given study. Unlike other patient characteristics (ie, depression, anxiety, etc), preoperative opioid users were often treated as a separate patient category where incidence rates were measured. Thus, our working group found it important to report the differing incidence rates between these 2 groups (Table 2). Even when considering the heterogeneity of sample sizes and definitions of persistent postoperative opioid use, the incidence of persistent postoperative opioid use was >10 times greater in preoperative opioid users when compared to opioid-naïve patients for arthroplasty and abdominopelvic patients and was rated as high-quality evidence. In patients undergoing spine surgery, preoperative opioid users were more than twice as likely to develop persistent postoperative opioid use when compared to opioid-naïve patients (59% vs 26% incidence of persistent postoperative opioid use) in 1 moderate quality study.24 While only a few studies assessed persistent postoperative opioid use in thoracic surgery (4 studies) and mastectomy (3 studies), those studies that were considered moderate quality reported the incidence of persistent postoperative opioid use to be >10% in opioid-naïve patients in both surgical subclasses. No studies in thoracic surgery or mastectomy evaluated preoperative opioid users.

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Patient and Surgical Characteristics Associated With Persistent Postoperative Opioid Use

Table 3.

Table 3.

The majority of studies measuring patient characteristics drew data from large insurance claim databases where comorbid conditions were gathered via International Classification of Diseases coding. Prescription fills were determined either through claims data, state prescription monitoring databases, or institutional prescription records. Studies that were prospective observational or institutional chart review in design measured patient characteristics such as anxiety or depressive symptoms through validated research tools (ie, Hospital Anxiety and Depression Scale, Zung Depression Scale).24,34 In these studies, opioid prescription/use was measured by patient report. Only 4 studies described surgery-specific variables such as the Knee Society Score for total knee arthroplasty or the presence of adjuvant chemotherapy/radiation in oncologic samples.10,12,34,41 Summative patient characteristics associated with persistent postoperative opioid use in all of the combined surgical groups are presented in Table 3.

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Arthroplasty.

Seventeen studies assessed patient characteristics associated with persistent postoperative opioid use in patients undergoing total knee arthroplasty or total hip arthroplasty (Supplemental Digital Content, Tables 2–3, http://links.lww.com/AA/C663).9,13,31–41,46–49 While heterogeneously defined, all studies that measured preoperative opioid use indicated a significant relationship with persistent postoperative opioid use. Moderate quality evidence was given to depression, substance use, preoperative painful conditions, and smoking. Five studies measured associated factors for persistent postoperative opioid use in both total hip arthroplasty and total knee arthroplasty.9,32,34,37,40 Three of these 5 studies identified total knee arthroplasty as a risk factor for persistent postoperative opioid use when compared to total hip arthroplasty.34,37,40 Additionally, Sun et al9 conducted a residual confounding analysis supporting the notion that total hip arthroplasty and total knee arthroplasty were risk factors for persistent postoperative opioid use when compared to a nonsurgical cohort.

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Abdominopelvic.

Sixteen studies assessed patient characteristics associated with persistent postoperative opioid use; however, significant heterogeneity was observed regarding the types of reported surgeries (Supplemental Digital Content, Tables 4–5, http://links.lww.com/AA/C663).3,8,9,11,12,15,26–30,42,45,50–52 Moderate-level evidence was observed for depression, substance use, preoperative painful conditions, tobacco use, and use of psychotropic prescription drugs. While some studies measured both minimally invasive and open surgical techniques, no formal comparative analyses were performed to determine an association between surgery type and persistent postoperative opioid use.

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Spine.

Five of 13 studies reported on associated patient characteristics, and a significant degree of diversity in surgery types was observed (Supplemental Digital Content, Tables 6–7, http://links.lww.com/AA/C663).24,25,43,44,53–61 Lumbar arthrodesis was the most commonly reported surgical intervention. Preoperative opioid use and depression were assigned high-quality level of evidence for their influence on persistent postoperative opioid use. Larger than other surgical types, the baseline presence of preoperative opioid use was noted to be >50%.24,58 Relative to other spine surgical subclasses, 2 studies observed lumbar fusion as having a higher association with persistent postoperative opioid use, while the 3 remaining studies identified revision and/or more invasive surgeries as risks.24,25,55,56,58

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Thoracic Surgery.

All 4 studies that involved thoracic surgery were conducted on mixed surgical groups (Supplemental Digital Content, Tables 8–9, http://links.lww.com/AA/C663).8,12,30,62 Two of the 4 studies analyzed the same sample from a large Canadian database but utilized 2 different measures of postoperative opioid use.8,30 Given these limitations, preoperative opioid use was given a low-quality level of evidence. Very low-quality evidence was observed for depression, substance use, age, and use of prescription psychotropic drugs. Clarke et al8 reported a significantly higher risk of persistent postoperative opioid use in open thoracic surgeries versus minimally invasive approaches.

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Mastectomy.

Three studies evaluated risk factors in patients undergoing mastectomy (Supplemental Digital Content, Tables 10–11, http://links.lww.com/AA/C663).10,12,13 Only 1 study focused solely on opioid-naïve patients undergoing mastectomy with immediate reconstruction instead of a mixed surgical cohort.10 Given this finding, a low-quality level of evidence was observed for preoperative opioid use, anxiety, and depression. No studies conducted a comparative analysis of differing surgical types (ie, radical mastectomy versus simple mastectomy, etc).

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DISCUSSION

Defining Persistent Postoperative Opioid Use

There are 3 elements in defining persistent postoperative opioid use: how to measure opioid use, timeframe to measure opioid use, and magnitude of opioid use required to trigger a diagnosis of persistent postoperative opioid use. With regard to the former, the working group noted that direct measurements of opioid consumption are labor intensive and expensive for researchers to measure and are also not readily available for most clinicians. By contrast, prescription data are easier for researchers and clinicians to obtain, and the use of prescription data as a proxy for actual drug consumption is a commonly used practice.63 Therefore, the working group decided that any definition of persistent postoperative opioid use should be based on prescription data.

In terms of the timeframe to measure persistent postoperative opioid use, because some opioid use immediately after surgery is expected, the working group decided that the timeframe should start at a point when acute surgical pain should have resolved and end at a point that (1) provides enough time to evaluate an individual’s opioid use over the long term, and (2) is practical for research purposes because patients can be lost to follow-up over longer periods of time. Overall, the working group decided that persistent postoperative opioid use should be measured during opioid use between postoperative days 90 and 365 for 2 reasons. First, this was a common period described for the assessment of persistent postoperative opioid use for several of the studies we examined.3,9 Second, this timeframe corresponds to a period where acute surgical pain should have resolved.64–66

Table 4.

Table 4.

Defining the level of opioid use during the timeframe required to trigger the diagnosis of persistent postoperative opioid use was also considered. Any choice of threshold incorporates a tradeoff between sensitivity and specificity: lower thresholds make a diagnosis more likely but also run the risk of including postsurgical patients who are incidentally using opioids for nonsurgical reasons. For example, in a large retrospective analysis of health care claims, Sun et al9 reported persistent postoperative opioid use rates <2% across numerous surgical groups using a threshold of having filled ≥10 prescriptions or >120 days’ supply within 90 days to 1 year postoperatively. Conversely, Brummett et al3 reported rates of persistent postoperative opioid use of 5.9%–6.5% using a less restrictive definition of opioid prescription fulfillment between 90 and 180 days postoperatively. In addition, any threshold should be based on the level of opioid use before surgery because patients who use opioids preoperatively may be expected to have higher postoperative use than opioid-naïve patients. Based on the studies we reviewed, the working group suggested that in the case of opioid-naïve patients, persistent postoperative opioid use should be defined as having filled opioid prescriptions for at least a 60 days supply during postoperative days 90–365 (Table 4). For patients who used opioids before surgery, we suggest that persistent postoperative opioid use be defined as any increase in opioid use relative to baseline (Table 4).

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Incidence of Risk Factors for Persistent Postoperative Opioid Use

Across surgeries in moderate quality studies, the incidence of persistent postoperative opioid use ranges from 0.6% to 26% for opioid-naïve patients and from 35% to 77% for patients with previous opioid exposure. These ranges take into account variations in the definition and measurement of persistent postoperative opioid use across the studies in our review. The following patient characteristics were consistently identified as risk factors for persistent postoperative opioid use: preoperative opioid use, depression, substance use, tobacco use, sex, psychotropic drug prescription, and anxiety (Table 3). Indeed 1 strength of these associations is that they were robust across a wide array of definitions for each characteristic (eg, preoperative opioid use was not defined consistently across studies). However, few studies assessed the relative importance of these risk factors. In addition, no studies assessed whether modification of these risk factors was associated with a reduced risk of persistent postoperative opioid use, which is a promising area for further research.

We were unable to identify any specific surgeries that were identified with an increased risk of persistent postoperative opioid use. A few studies suggest that total knee arthroplasty, open thoracic, and lumbar fusion may be linked to higher rates of persistent postoperative opioid use within their own subclasses (ie, orthopedics, thoracic surgery, etc), but large-scale studies where important biopsychosocial variables are controlled for between surgical groups have not occurred.8,9 Of note, 1 study suggested that the incidence of persistent postoperative opioid use was fairly consistent across major and minor surgeries, suggesting that surgery characteristics may play a small role in determining the risk of persistent postoperative opioid use.3

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Systems and Prescribing Characteristics Associated With Persistent Postoperative Opioid Use

Finally, we found only 1 study that examined the association between persistent postoperative opioid use and prescriber or health care system characteristics.67 In this large database of commercially insured patients, the duration of the initial opioid prescription, not the total dosage of opioids prescribed, was associated with factors indicative of persistent postoperative opioid use, including opioid dependence, misuse, or overdose after surgery. This finding was stable across 7 different surgical types.

This paucity of studies is concerning because persistent postoperative opioid use likely represents the end result of numerous interactions between a patient and his or her health care team, such as the surgeon, anesthesiologist, and primary care provider. Moreover, there recently have been many efforts aimed at modifying prescriber behaviors and modifying health care systems, with the goal of reducing persistent postoperative opioid use, such as surgeon education,6,68 quality improvement initiatives,6,69–72 legislative initiatives to reduce opioid prescribing,73–76 and initiatives to limit coverage for opioids.75 However, whether these efforts have succeeded in reducing persistent postoperative opioid use remains unknown. Overall, characterizing the prescriber and health care system characteristics remains an important area for further study.

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Study Limitations

We recognize numerous limitations regarding the incidence of and risk factors for persistent postoperative opioid use. One limit relates to the heterogeneous definition of persistent postoperative opioid use in studies, leading to variability in reported rates of persistent postoperative opioid use. Additionally, risk factors for persistent postoperative opioid use were often measured via different systems, whether by International Classification of Diseases diagnostic codes (depression, substance abuse, etc) or symptoms related to a particular condition (ie, anxiety symptoms as measured by the hospital depression and anxiety scale). Future studies that utilize consistent definitions of persistent postoperative opioid use and standardized outcomes that consider condition duration and severity will likely further specify persistent postoperative opioid use rates and risk factors. Our review is also limited by differing measures of opioid use or prescription. These measures were heterogeneously reported and represent different facets of persistent postoperative opioid use. Studies where opioid use was reported often described a link to the surgical insult, whereas opioid prescription filling cannot always be clearly linked to surgery. Future studies that focus on contributions of patient use versus opioid availability (ie, prescription) will provide additional clarity and possible strategies to curb persistent postoperative opioid use. Finally, we recognize that our focus on US and Canadian health care systems introduces bias because other international sites were not included. While this decision was made based on similar opioid-prescribing practices, future studies that stratify persistent postoperative opioid use by country, region, and health care models are needed.

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CONCLUSIONS

In summary, our working group arrived at the following conclusions:

  • For opioid-naïve patients, persistent postoperative opioid use should be defined as having filled a 60 days’ supply of opioid during postoperative days 90–365. For patients who used opioids before surgery, persistent postoperative opioid use should be defined as any increase in opioid use above baseline during this time period.
  • The incidence of persistent postoperative opioid use ranges from 0.6% to 26% for opioid-naïve patients and from 35% to 77% for patients with previous opioid exposure.
  • Patient characteristics associated with an increased risk of persistent postoperative opioid use included preoperative opioid use, depression, substance use disorder, preoperative pain conditions, and smoking. Whether specific surgeries are associated with an increased risk of persistent postoperative opioid use remains unclear, and is the extent to which the risk of persistent postoperative opioid use has been affected by health care system characteristics and health policy.
Figure 2.

Figure 2.

As a result of its analysis, the working group provides several recommendations (Table 4; Figure 2) to the anesthesiology and medical communities. Each of these recommendations is rooted in the results of the literature review described earlier. By implementing these recommendations, the working group believes that physicians and other health care providers will be better positioned to find ways of reducing the risk of persistent postoperative opioid use among patients undergoing surgery.

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CONTRIBUTORS

Conference Organizers

Matthew D. McEvoy, MD, Department of Anesthesiology, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN; Timothy E. Miller, MB, ChB FRCA, Department of Anesthesiology, Duke University Medical Center, Durham, NC; Julie K. M. Thacker, MD, FACS, FASCRS, Department of Surgery, Duke University Medical Center, Durham, NC; Andrew D. Shaw, MB, FRCA, FFICM, FCCM, MMHC, Department of Anesthesiology and Pain Medicine, University of Alberta, Edmonton, AB, Canada; Tong J. Gan, MD, MBA, MHS, FRCA, Department of Anesthesiology, Stony Brook University, Stony Brook, NY.

Participants (alphabetical)

Charles Argoff, MD, Department of Neurology, Albany Medical College, Albany, NY; David A. Edwards, MD, PhD, Department of Anesthesiology, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN; Timothy M. Geiger, MD, MMHC, FACS, FASCRS, Department of Surgery, Colorectal Surgery, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN; Debra B. Gordon, RN, DNP, FAAN, Anesthesiology & Pain Medicine, University of Washington, Seattle, WA; Michael C. Grant, MD, Department of Anesthesiology, The Johns Hopkins Hospital, Baltimore, MD; Michael Grocott, BSc, MBBS, MD, FRCA, FRCP, FFICM, Respiratory and Critical Care Research Area, NIHR Biomedical Research Centre, University Hospital Southampton, NHS Foundation Trust, Southampton UK and Integrative Physiology and Critical Illness Group, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Padma Gulur, MD, Department of Anesthesiology, Duke University Medical Center, Durham, NC; Ruchir Gupta, MD, Department of Anesthesiology, Stony Brook University, Stony Brook, NY; Jennifer M. Hah, MD, MS, Department of Anesthesiology, Preoperative and Pain Medicine, Department of Health Research and Policy (by courtesy), Stanford University, Palo Alto, CA; Traci L. Hedrick, MD, MS, FACS, FASCRS, Department of Surgery, Section Colon and Rectal Surgery, University of Virginia Health System, Charlottesville, VA; Stefan D. Holubar, MD, MS, FACS, FASCRS, Department of Colorectal Surgery, Cleveland Clinic, Cleveland, OH; Robert W. Hurley, MD, PhD, FASA, Wake Forest School of Medicine, Wake Forest Baptist Medical Center, Winston-Salem, NC; Jennifer Jayaram, APRN, MSN, Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN; Michael L. Kent, MD, Department of Anesthesiology, Duke University Medical Center, Durham, NC; Adam B. King, MD, Department of Anesthesiology, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN; Michael G. Mythen, MBBS, MD, FRCA, FFICM, FCAI (Hon), UCL/UCLH National Institute of Health Research Biomedical Research Centre, London, UK; Gary M. Oderda, PharmD, MPH, Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT; Erin Sun, MD, PhD, Department of Anesthesiology, Preoperative and Pain Medicine, Department of Health Research and Policy (by courtesy), Stanford University, Palo Alto, CA; Christopher L. Wu, MD, Department of Anesthesiology, The Johns Hopkins Hospital, Baltimore, MD.

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DISCLOSURES

Name: Michael L. Kent, MD.

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Robert W. Hurley, MD, PhD, FASA.

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Gary M. Oderda, PharmD, MPH.

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Debra B. Gordon, RN-BC, DNP, FAAN.

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Eric Sun, MD, PhD.

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Monty Mythen, MBBS, MD, FRCA, FFICM, FCAI (Hon).

Contribution: This author helped with the conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Timothy E. Miller, MB, ChB.

Contribution: This author helped with the organization of the conference, conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Andrew D. Shaw, MB, FRCA, FFICM, FCCM.

Contribution: This author helped with the organization of the conference, conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Tong J. Gan, MD, MBA, MHS, FRCA.

Contribution: This author helped with the organization of the conference, conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Julie K. M. Thacker, MD.

Contribution: This author helped with theorganization of the conference, conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Name: Matthew D. McEvoy, MD.

Contribution: This author helped with the organization of the conference, conception, design, analysis, and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

This manuscript was handled by: Honorio T. Benzon, MD.

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REFERENCES

1. Ladha KS, Patorno E, Huybrechts KF, Liu J, Rathmell JP, Bateman BT. Variations in the use of perioperative multimodal analgesic therapy. Anesthesiology. 2016;124:837–845.
2. Wunsch H, Wijeysundera DN, Passarella MA, Neuman MD. Opioids prescribed after low-risk surgical procedures in the United States, 2004-2012. JAMA. 2016;315:1654–1657.
3. Brummett CM, Waljee JF, Goesling J. New persistent opioid use after minor and major surgical procedures in US adults. JAMA Surg. 2017;152:e170504.
4. Hah JM, Bateman BT, Ratliff J, Curtin C, Sun E. Chronic opioid use after surgery: implications for perioperative management in the face of the opioid epidemic. Anesth Analg. 2017;125:1733–1740.
5. Bicket MC, Long JJ, Pronovost PJ, Alexander GC, Wu CL. Prescription opioid analgesics commonly unused after surgery: a systematic review. JAMA Surg. 2017;152:1066–1071.
6. Hill MV, McMahon ML, Stucke RS, Barth RJ Jr.. Wide variation and excessive dosage of opioid prescriptions for common general surgical procedures. Ann Surg. 2017;265:709–714.
7. Bartels K, Mayes LM, Dingmann C, Bullard KJ, Hopfer CJ, Binswanger IA. Opioid use and storage patterns by patients after hospital discharge following surgery. PLoS One. 2016;11:e0147972.
8. Clarke H, Soneji N, Ko DT, Yun L, Wijeysundera DN. Rates and risk factors for prolonged opioid use after major surgery: population based cohort study. BMJ. 2014;348:g1251.
9. Sun EC, Darnall BD, Baker LC, Mackey S. Incidence of and risk factors for chronic opioid use among opioid-naive patients in the postoperative period. JAMA Intern Med. 2016;176:1286–1293.
10. Marcusa DP, Mann RA, Cron DC, et al. Prescription opioid use among opioid-naive women undergoing immediate breast reconstruction. Plast Reconstr Surg. 2017;140:1081–1090.
11. Bateman BT, Franklin JM, Bykov K. Persistent opioid use following cesarean delivery: patterns and predictors among opioid-naïve women. Am J Obstet Gynecol. 2016;215:353.e1–353.e18.
12. Lee JS, Hu HM, Edelman AL. New persistent opioid use among patients with cancer after curative-intent surgery. J Clin Oncol. 2017;35:4042–4049.
13. Carroll I, Barelka P, Wang CK, et al. A pilot cohort study of the determinants of longitudinal opioid use after surgery. Anesth Analg. 2012;115:694–702.
14. Mudumbai SC, Oliva EM, Lewis ET, et al. Time-to-cessation of postoperative opioids: a population-level analysis of the Veterans Affairs Health Care System. Pain Med. 2016;17:1732–1743.
15. Alam A, Gomes T, Zheng H, Mamdani MM, Juurlink DN, Bell CM. Long-term analgesic use after low-risk surgery: a retrospective cohort study. Arch Intern Med. 2012;172:425–430.
16. Singh JA, Lewallen DG. Predictors of pain medication use for arthroplasty pain after revision total knee arthroplasty. Rheumatology (Oxford). 2014;53:1752–1758.
17. Hooten WM, Brummett CM, Sullivan MD. A conceptual framework for understanding unintended prolonged opioid use. Mayo Clin Proc. 2017;92:1822–1830.
18. Gan TJ, Scott M, Thacker J, Hedrick T, Thiele RH, Miller TE. American society for enhanced recovery: advancing enhanced recovery and perioperative medicine. Anesth Analg. 2018;126:1870–1873.
19. Gomes T, Mamdani MM, Paterson JM, Dhalla IA, Juurlink DN. Trends in high-dose opioid prescribing in Canada. Can Fam Physician. 2014;60:826–832.
20. King NB, Fraser V, Boikos C, Richardson R, Harper S. Determinants of increased opioid-related mortality in the United States and Canada, 1990–2013: a systematic review. Am J Public Health 2014;104:e32–e42.
21. Iorio A, Spencer FA, Falavigna M. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ. 2015;350:h870.
22. Huguet A, Hayden JA, Stinson J. Judging the quality of evidence in reviews of prognostic factor research: adapting the GRADE framework. Syst Rev. 2013;2:71.
23. Moher D, Liberati A, Tetzlaff J, Altman DG; The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.
24. Armaghani SJ, Lee DS, Bible JE. Preoperative opioid use and its association with perioperative opioid demand and postoperative opioid independence in patients undergoing spine surgery. Spine (Phila Pa 1976). 2014;39:E1524–E1530.
25. Schoenfeld AJ, Nwosu K, Jiang W. Risk factors for prolonged opioid use following spine surgery, and the association with surgical intensity, among opioid-naive patients. J Bone Joint Surg Am. 2017;99:1247–1252.
26. Kulshrestha S, Barrantes F, Samaniego M, Luan FL. Chronic opioid analgesic usage post-kidney transplantation and clinical outcomes. Clin Transplant. 2014;28:1041–1046.
27. Morgan K, Owczarski SM, Borckardt J, Madan A, Nishimura M, Adams DB. Pain control and quality of life after pancreatectomy with islet autotransplantation for chronic pancreatitis. J Gastrointest Surg. 2012;16:129–133.
28. Raebel MA, Newcomer SR, Reifler LM. Chronic use of opioid medications before and after bariatric surgery. JAMA. 2013;310:1369–1376.
29. Raebel MA, Newcomer SR, Bayliss EA, et al. Chronic opioid use emerging after bariatric surgery. Pharmacoepidemiol Drug Saf. 2014;23:1247–1257.
30. Soneji N, Clarke HA, Ko DT, Wijeysundera DN. Risks of developing persistent opioid use after major surgery. JAMA Surg. 2016;151:1083–1084.
31. Bedard NA, Pugely AJ, Westermann RW, Duchman KR, Glass NA, Callaghan JJ. Opioid use after total knee arthroplasty: trends and risk factors for prolonged use. J Arthroplasty. 2017;32:2390–2394.
32. Bedard NA, DeMik DE, Dowdle SB, Callaghan JJ. Trends and risk factors for prolonged opioid use after unicompartmental knee arthroplasty. Bone Joint J. 2018;100-B:62–67.
33. Cancienne JM, Patel KJ, Browne JA, Werner BC. Narcotic use and total knee arthroplasty. J Arthroplasty. 2018;33:113–118.
34. Goesling J, Moser SE, Zaidi B, et al. Trends and predictors of opioid use after total knee and total hip arthroplasty. Pain. 2016;157:1259–1265.
35. Hadlandsmyth K, Vander Weg MW, McCoy KD, Mosher HJ, Vaughan-Sarrazin MS, Lund BC. Risk for prolonged opioid use following total knee arthroplasty in Veterans. J Arthroplasty. 2018;33:119–123.
36. Kim KY, Anoushiravani AA, Chen KK, Roof M, Long WJ, Schwarzkopf R. Preoperative chronic opioid users in total knee arthroplasty-which patients persistently abuse opiates following surgery? J Arthroplasty. 2018;33:107–112.
37. Kim SC, Choudhry N, Franklin JM, et al. Patterns and predictors of persistent opioid use following hip or knee arthroplasty. Osteoarthritis Cartilage. 2017;25:1399–1406.
38. Namba RS, Inacio MCS, Pratt NL, Graves SE, Roughead EE, Paxton EW. Persistent opioid use following total knee arthroplasty: a signal for close surveillance. J Arthroplasty. 2018;33:331–336.
39. Sun EC, Bateman BT, Memtsoudis SG, Neuman MD, Mariano ER, Baker LC. Lack of association between the use of nerve blockade and the risk of postoperative chronic opioid use among patients undergoing total knee arthroplasty: evidence from the Marketscan database. Anesth Analg. 2017;125:999–1007.
40. Zarling BJ, Yokhana SS, Herzog DT, Markel DC. Preoperative and postoperative opiate use by the arthroplasty patient. J Arthroplasty. 2016;31:2081–2084.
41. Franklin PD, Karbassi JA, Li W, Yang W, Ayers DC. Reduction in narcotic use after primary total knee arthroplasty and association with patient pain relief and satisfaction. J Arthroplasty. 2010;25:12–16.
42. Shah AS, Blackwell RH, Kuo PC, Gupta GN. Rates and risk factors for opioid dependence and overdose after urological surgery. J Urol. 2017;198:1130–1136.
43. Nguyen TH, Randolph DC, Talmage J, Succop P, Travis R. Long-term outcomes of lumbar fusion among workers’ compensation subjects: a historical cohort study. Spine (Phila Pa 1976). 2011;36:320–331.
44. Lawrence JT, London N, Bohlman HH, Chin KR. Preoperative narcotic use as a predictor of clinical outcome: results following anterior cervical arthrodesis. Spine (Phila Pa 1976). 2008;33:2074–2078.
45. Ladha KS, Patorno E, Liu J, Bateman BT. Impact of perioperative epidural placement on postdischarge opioid use in patients undergoing abdominal surgery. Anesthesiology. 2016;124:396–403.
46. Singh JA, Lewallen D. Predictors of pain and use of pain medications following primary total hip arthroplasty (THA): 5,707 THAs at 2-years and 3,289 THAs at 5-years. BMC Musculoskelet Disord. 2010;11:90.
47. Singh JA, Lewallen DG. Predictors of use of pain medications for persistent knee pain after primary total knee arthroplasty: a cohort study using an institutional joint registry. Arthritis Res Ther. 2012;14:R248.
48. Hernandez NM, Parry JA, Taunton MJ. Patients at risk: large opioid prescriptions after total knee arthroplasty. J Arthroplasty. 2017;32:2395–2398.
49. Politzer CS, Kildow BJ, Goltz DE, Green CL, Bolognesi MP, Seyler TM. Trends in opioid utilization before and after total knee arthroplasty. J Arthroplasty. 2018;33:S147.e1–S153.e1.
50. Darnall B, Li H. Hysterectomy and predictors for opioid prescription in a chronic pain clinic sample. Pain Med. 2011;12:196–203.
51. King WC, Chen JY, Belle SH, et al. Use of prescribed opioids before and after bariatric surgery: prospective evidence from a US multicenter cohort study. Surg Obes Relat Dis. 2017;13:1337–1346.
52. Moran RA, Klapheke R, John GK, et al. Prevalence and predictors of pain and opioid analgesic use following total pancreatectomy with islet autotransplantation for pancreatitis. Pancreatology. 2017;17:732–737.
53. Zigler JE, Delamarter RB. Does 360° lumbar spinal fusion improve long-term clinical outcomes after failure of conservative treatment in patients with functionally disabling single-level degenerative lumbar disc disease? Results of 5-year follow-up in 75 postoperative patients. Int J Spine Surg. 2013;7:e1–e7.
54. Mirza SK, Deyo RA, Heagerty PJ, Turner JA, Martin BI, Comstock BA. One-year outcomes of surgical versus nonsurgical treatments for discogenic back pain: a community-based prospective cohort study. Spine J. 2013;13:1421–1433.
55. Mayer TG, Gatchel RJ, Brede E, Theodore BR. Lumbar surgery in work-related chronic low back pain: can a continuum of care enhance outcomes? Spine J. 2014;14:263–273.
56. Anderson JT, Haas AR, Percy R, Woods ST, Ahn UM, Ahn NU. Chronic opioid therapy after lumbar fusion surgery for degenerative disc disease in a workers’ compensation setting. Spine (Phila Pa 1976). 2015;40:1775–1784.
57. De la Garza-Ramos R, Xu R, Ramhmdani S, et al. Long-term clinical outcomes following 3- and 4-level anterior cervical discectomy and fusion. J Neurosurg Spine. 2016;24:885–891.
58. Connolly J 3rd, Javed Z, Raji MA, Chan W, Kuo YF, Baillargeon J. Predictors of long-term opioid use following lumbar fusion surgery. Spine (Phila Pa 1976). 2017;42:1405–1411.
59. Mino DE, Munterich JE, Castel LD. Lumbar fusion surgery for degenerative conditions is associated with significant resource and narcotic use 2 years postoperatively in the commercially insured: a medical and pharmacy claims study. J Spine Surg. 2017;3:141–148.
60. Buttermann GR. Anterior cervical discectomy and fusion outcomes over 10 years: a prospective study. Spine (Phila Pa 1976). 2018;43:207–214.
61. O’Connell C, Azad TD, Mittal V, et al. Preoperative depression, lumbar fusion, and opioid use: an assessment of postoperative prescription, quality, and economic outcomes. Neurosurg Focus. 2018;44:E5.
62. Carroll IR, Hah JM, Barelka PL, et al. Pain duration and resolution following surgery: an inception cohort study. Pain Med. 2015;16:2386–2396.
63. Goldman DP, Joyce GF, Zheng Y. Prescription drug cost sharing: associations with medication and medical utilization and spending and health. JAMA. 2007;298:61–69.
64. Shah A, Hayes CJ, Martin BC. Characteristics of initial prescription episodes and likelihood of long-term opioid use: United States, 2006-2015. MMWR Morb Mortal Wkly Rep. 2017;66:265–269.
65. Kent ML, Tighe PJ, Belfer I, et al. The ACTTION-APS-AAPM Pain Taxonomy (AAAPT) multidimensional approach to classifying acute pain conditions. J Pain. 2017;18:479–489.
66. Strengthen Opioid Misuse Prevention Act of 2017. Available at: https://www.ncleg.net/Sessions/2017/Bills/House/PDF/H243v6.pdf. Accessed February 19, 2018.
67. Brat GA, Agniel D, Beam A, et al. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. BMJ. 2018;360:j5790.
68. Harle CA, Marlow NM, Schmidt SO, et al. The effect of EHR-integrated patient-reported outcomes on satisfaction with chronic pain care. Am J Manag Care. 2016;22:e403–e408.
69. Losby JL, Hyatt JD, Kanter MH, Baldwin G, Matsuoka D. Safer and more appropriate opioid prescribing: a large healthcare system’s comprehensive approach. J Eval Clin Pract. 2017;23:1173–1179.
70. Meissner W, Huygen F, Neugebauer EAM, et al. Management of acute pain in the postoperative setting: the importance of quality indicators. Curr Med Res Opin. 2018;34:187–196.
71. Modesitt SC, Sarosiek BM, Trowbridge ER, et al. Enhanced recovery implementation in major gynecologic surgeries: effect of care standardization. Obstet Gynecol. 2016;128:457–466.
72. Stanek JJ, Renslow MA, Kalliainen LK. The effect of an educational program on opioid prescription patterns in hand surgery: a quality improvement program. J Hand Surg Am. 2015;40:341–346.
73. Johnson H, Paulozzi L, Porucznik C, Mack K, Herter B; Hal Johnson Consulting and Division of Disease Control and Health Promotion, Florida Department of Health. Decline in drug overdose deaths after state policy changes: Florida, 2010-2012. MMWR Morb Mortal Wkly Rep. 2014;63:569–574.
74. American Academy of Pain Medicine. State Legislative Updates. Available at: http://www.painmed.org/advocacy/state-updates/. Accessed March 27, 2018.
75. Updated NC Medicaid Prior Approval Criteria for Opioid Analgesics. Available at: https://files.nc.gov/ncdhhs/PA_Criteria-Opioid-Analgesics.pdf. Accessed March 27, 2018.
76. The Strengthen Opioid Misuse Prevention (STOP) Act of 2017 (Session Law 2017–74/H243). 2017. Available at: https://www.ncmedboard.org/images/uploads/article_images/The_STOP_Act_summary-OnLetterhead.pdf. Accessed March 27, 2018.

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