Abstract
Objective
Guidelines recommend that clinicians make decisions about opioid tapering for patients with chronic pain using a benefit-to-harm framework and engaging patients. Studies have not examined clinician documentation about opioid tapering using this framework.
Design and Setting
Thematic and content analysis of clinician documentation about opioid tapering in patients’ medical records in a large academic health system.
Methods
Medical records were reviewed for patients aged 18 or older, without cancer, who were prescribed stable doses of long-term opioid therapy between 10/2015 and 10/2016 then experienced an opioid taper (dose reduction ≥30%) between 10/2016 and 10/2017. Inductive thematic analysis of clinician documentation within six months of taper initiation was conducted to understand rationale for taper, and deductive content analysis was conducted to determine the frequencies of a priori elements of a benefit-to-harm framework.
Results
Thematic analysis of 39 patients’ records revealed 1) documented rationale for tapering prominently cited potential harms of continuing opioids, rather than observed harms or lack of benefits; 2) patient engagement was variable and disagreement with tapering was prominent. Content analysis found no patients’ records with explicit mention of benefit-to-harm assessments. Benefits of continuing opioids were mentioned in 56% of patients’ records, observed harms were mentioned in 28%, and potential harms were mentioned in 90%.
Conclusions
In this study, documentation of opioid tapering focused on potential harms of continuing opioids, indicated variable patient engagement, and lacked a complete benefit-to-harm framework. Future initiatives should develop standardized ways of incorporating a benefit-to-harm framework and patient engagement into clinician decisions and documentation about opioid tapering.
Keywords: Chronic Pain, Opioid Taper, Primary Care, Pain Management, Clinician Documentation
Introduction
In the context of the current opioid epidemic, opioid tapering (i.e., reducing the dose or discontinuing opioid medications) has emerged as a strategy to mitigate the potential harms of long-term opioid therapy for chronic pain [1–3]. Early studies support the feasibility and success of opioid tapers among engaged patients who choose or agree to taper [4, 5]. Consensual tapers have been associated with improvements in pain intensity, quality of life, and self-efficacy for managing pain [4, 6]. In real-world practice, opioid tapers vary widely, including rapid tapers ending in discontinuation of opioids and slow dose reductions over months or years [7, 8]. Currently, evidence is insufficient to recommend specific tapering strategies, including optimal speed or targeted end dose [7, 9, 10].
Over the past decade, experts and guidelines including the Centers for Disease Control and Prevention’s (CDC’s) 2016 Guideline for Prescribing Opioids for Chronic Pain and the recent guide from the Department of Health and Human Services have recommended that clinicians base opioid tapering decisions on an individualized assessment of the relative benefits and harms of continued opioid therapy for each patient, hereafter referred to as the “benefit-to-harm framework” [1, 3, 9–12]. The benefit-to-harm framework has been employed in other areas of medical decision-making, for example, when deciding whether to initiate or continue aspirin for cardiovascular health in light of potential or observed harms of gastrointestinal bleeding. A strength of the benefit-to-harm framework is that it facilitates the patient and clinician aligning around common goals of safety and effectiveness for the unique patient, which can improve patient engagement in the treatment plan [13]. This framework is particularly valuable in opioid tapering decisions when disagreement between patients and clinicians causes challenges in the clinician–patient relationship [14–17]. Furthermore, the CDC guidelines recommend that clinicians engage patients in the clinical decision-making process, such that opioid tapering decisions are based on a relationship and shared understanding between the clinician and patient [2].
In such situations where clinicians are weighing the relative benefits and harms of continuing a medical treatment, medical record documentation about decision-making is important. Although it is impossible to gain a complete understanding of clinician–patient communications from reviewing clinician notes, documentation of a clinician’s assessment and rationale for medical decisions is used for communication with patients as well as other members of the medical team [18–20]. Opioid tapering can require interdisciplinary team-based care (e.g., a team might include a primary care provider, nurse care manager, social worker, pharmacist, mental health provider, and/or a specialist in a discipline such as pain medicine or addiction medicine) [ 4, 21], and effective communication between clinicians is essential for high-quality patient care. Current guidelines do not provide specific guidance for clinicians about how to document a benefit-to-harm framework or patient engagement in patients’ medical records [22–24].
The overarching goal of this qualitative study was to describe clinician documentation about opioid tapering decisions in patients’ medical records. Specifically, we sought to examine how clinicians document their rationale for tapering and patient engagement in tapering decisions and the extent to which documentation is consistent with guideline recommendations to use a benefit-to-harm framework in tapering decisions.
Methods
Overview
Thematic and content analyses of clinician documentation were conducted retrospectively for patients who underwent opioid tapers in a large urban academic health care system. For this study, analysis of clinician notes in each patient record included two parts: inductive thematic analysis (a qualitative research technique used to identify themes or patterns of meaning in text as they emerge from the data) to identify themes that describe clinicians’ opioid tapering decisions and documentation; and deductive content analysis (a qualitative research technique used to determine and quantify the presence of certain words or concepts within text) to determine the presence or absence of a benefit-to-harm framework. The study was approved by the Albert Einstein College of Medicine and Montefiore Health System Institutional Review Board.
Setting
This study was conducted at a large academic health care system with almost 21 primary care practices in the Bronx, New York. During the study period, there were educational sessions about opioid management at several primary care centers and the primary hospital. Additionally, New York State required a three-hour training in opioid management for all licensed physicians in 2017. There were no health system–wide initiatives to reduce opioid prescribing.
Patient Record Selection
Patient records were included if the patient was 1) aged 18 years or older, 2) prescribed a stable dose of long-term opioid therapy between 10/2015 and 10/2016, and 3) initiated and underwent an opioid taper between 10/2016 and 10/2017 (definitions below), confirmed on manual chart review. This time frame was chosen to focus on patients who experienced opioid tapers that were initiated after the release of clinical guidelines formally recommending opioid tapering as a way to mitigate harms for patients receiving long-term opioid therapy [2]. Patient records for patients with any cancer diagnosis (ICD-9 codes 140–209, 230–239) were excluded because guidelines for opioid tapering generally exclude patients with cancer pain.
To determine if patients were prescribed a stable dose of long-term opioid therapy (criterion #2), opioid prescription data (i.e., outpatient medication orders) were extracted from the electronic medical record (EMR) for each patient. Individual opioid prescriptions were organized into four distinct six-month periods between 10/2015 and 10/2017 (10/2015–3/2016 , 4/2016–9/2016 , 10/2016–3/2017 , and 4/2017–9/2017). Then, a daily opioid dose was calculated for each six-month period by determining the morphine milligram equivalent (MME) units prescribed per prescription using standardized MME conversion factors [25], summing the MME for all prescriptions during the six-month period, and dividing the total MME per six-month period by 180 days [2, 25]. Prescriptions for all formulations of opioid medications were included in MME calculations to determine if criterion #2 was met, with the following exceptions: 1) buprenorphine and liquid methadone, because they were likely to be used for treatment of opioid use disorder rather than for treatment of chronic pain; and 2) intravenous or injection opioid medications, because they were likely to be used for acute rather than chronic pain treatment. To determine if a patient was on a stable dose of long-term opioid therapy, long-term opioid therapy was defined as having three or more qualifying opioid prescriptions at least 21 days apart in each of two consecutive six-month periods between 10/2015 and 10/2016, a definition used previously [26]. The dose of long-term opioid therapy was considered stable if there was a <20% difference in daily opioid dose between the two periods of six months (“baseline”).
To determine if patients underwent an opioid taper (criterion #3), possible opioid tapers were first identified using EMR prescription data, then confirmed using manual chart review. Specifically, a patient was considered to have undergone a possible opioid taper if there was a reduction in daily opioid dose of at least 30% in either a six-month period between 10/2016 and 10/2017 (considered the “identified taper period”) or relative to baseline (between 10/2015 and 10/2016), as prescribed in the EMR. Using manual chart review by two independent researchers (MB and JMS), an opioid taper was confirmed if three requirements were met: 1) there was a change in a recurring opioid prescription (including a change in the dose or frequency, or a discontinuation of the medication); 2) the change resulted in a new daily opioid dose (sum of all new opioid prescriptions) within six months of taper initiation that was at least 30% less than the established baseline total opioid dose; and 3) there was nothing in the EMR that suggested that the reduction in opioid dose could be explained by an alternate explanation (i.e., was not due to a taper), for example, if hospitalization led to a gap in prescriptions or the patient transferred care outside the health system, moved, or was otherwise lost to follow-up. Because there is no expert consensus or standardized definition to determine what magnitude of dose reduction over what time frame constitutes an opioid taper [27], the decision was made to define it as a reduction of at least 30% within a six-month period. Though any reduction in dose may be considered a taper [27], a conservative threshold requiring at least a 30% dose reduction was chosen for this analysis of documentation of tapers, with the goal of being specific rather than sensitive for identifying true tapers over minor dose fluctuations. In addition, a 30% dose reduction has face validity as a clinically meaningful change and has been used previously [28]. As a final step, to minimize bias due to overrepresentation of patients who were treated by a clinician with an atypically high tendency to taper (i.e., an “outlier clinician” for whom the number of tapered patients was more than three standard deviations above the mean), the number of patient records selected for inclusion in this study who were treated by an outlier clinician was restricted to the median number of patients treated by other clinicians (i.e., one), chosen randomly using a random number generator. All patient records that met inclusion criteria for the study were analyzed using both inductive thematic analysis and deductive content analysis, described below.
Medical Record Data Abstraction
Data about demographic (age, race/ethnicity, gender) and clinical characteristics (diagnoses, visits, and prescription data) were extracted from the EMR via electronic queries. Then, manual chart review of each included patient’s records within six months before and after the patient’s date of taper initiation was conducted using a structured data abstraction form. All natural language text about opioid tapering decisions that were documented in clinician notes written by the patient’s primary opioid prescriber or a colleague at the same practice was abstracted. Data abstraction for all patient records was completed independently by two researchers (MB and RA). The first five patient records were reviewed together initially to ensure consistent abstraction and eligibility determinations, and discrepancies were settled by group discussion. De-identified textual data from clinician notes were uploaded into the qualitative data management software program Dedoose (Hermosa Beach, CA, USA [29]).
Analysis
Inductive Thematic Analysis
Inductive thematic analysis was conducted using all textual data abstracted from clinician notes to understand reasons for initiating an opioid taper and to identify themes that describe clinicians’ documentation about decisions to taper. Textual data from the first 10 patient records were reviewed and coded using an open coding approach by two independent researchers (MB and RA), identifying an initial coding scheme that was developed inductively and iteratively revised based on themes that emerged about opioid tapering documentation. The final coding scheme was derived through iterative group discussion (MB, RA, JS), and all textual data were coded using the final coding scheme. Once the coding was completed, the immersion/crystallization approach [30] was used to look for patterns in the data (MB, RA, JMS), before synthesizing into themes (MB, RA, JMS, HP, JM, SN, JS). Themes were then evaluated for concordance and discordance (MB and JS), and the original textual data were reviewed for disconfirming evidence (MB and RA). Textual data from all 39 patient records were included, and thematic saturation was achieved.
Deductive Content Analysis
Content analysis was conducted by creating an a priori coding scheme to identify whether the textual data abstracted from clinician notes included elements of a benefit-to-harm framework. The a priori coding scheme was based on the CDC guideline for prescribing opioids for chronic pain [2] and a benefit-to-harm framework initially proposed by Nicolaidis [2, 14]. Specifically, two independent researchers (MB and RA) coded clinician notes from each patient record for the following elements of a benefit-to-harm framework: 1) mention of any rationale for opioid tapering, 2) mention of a benefit of continuing opioids (such as pain reduction or functional improvement), 3) mention of an observed harm of continuing opioids (a negative outcome experienced as a result of long-term opioid therapy, e.g., an adverse event), 4) mention of a potential harm of continuing opioids (risk of a future opioid-related harm, e.g., opioid use disorder or overdose), and 5) an explicit assessment of the benefits vs observed or potential harms of continuing opioids. Within each patient’s record, it was determined whether the five elements of the benefit-to-harm framework were present (dichotomous variables). Summary statistics were performed to determine the count and percentage of patient records that included the elements. To determine inter-rater reliability, a Cohen’s kappa statistic was calculated.
Results
Of 13, 338 patients with any opioid prescription between 10/2015 and 10/2016, 664 patients were identified as having been on long-term opioid therapy between 10/2015 and 10/2016, and 251 patients were identified as having possible opioid tapers from the EMR. After manual chart review, 39 patient records had confirmed opioid tapers that met study inclusion criteria (Figure 1). The 39 patient records included 28 unique primary opioid prescribers, with a median (interquartile range) of one (one to two) patient record per clinician included in the study.
Figure 1.
Study flow diagram.
The mean patient age was 50 years, 21 (54%) were female, and patients identified as 44% black, 36% Latinx, and 10% white (Table 1). Primary opioid prescribers practiced diverse medical specialties including Family or Internal Medicine (26%), Infectious Diseases (46%), Hematology (15%), Anesthesiology (5%), Orthopedic Surgery (3%), Pain Medicine (3%), and Physical Medicine and Rehabilitation (3%). Twenty-six (67%) primary opioid prescribers were listed as the primary care provider (PCP) in the patient record.
Table 1.
Patient demographic and clinical characteristics
| Characteristic | Total (N = 39), No. (%) |
|---|---|
| Patient demographic characteristics | |
| Age, mean ± SD, y | 50 ± 12.3 |
| Race/ethnicity | |
| Black | 17 (44) |
| Latinx | 14 (36) |
| White | 4 (10) |
| Other | 4 (10) |
| Female | 21 (54) |
| Patient clinical characteristics | |
| HIV-positive | 20 (51) |
| Sickle cell disease | 7 (18) |
| Enrolled in opioid treatment program | 9 (23) |
| Patients on concurrent benzodiazepines | 10 (26) |
| Baseline opioid dose, median (IQR), MME | 85 (27.5–180) |
IQR = interquartile range;: MME = morphine milligram equivalents.
Two key themes were identified in clinician documentation about opioid tapering (Table 2). First, the rationale documented for opioid tapering predominantly focused on patient behaviors, particularly opioid or substance use. Specifically, documentation tended to only reflect the clinician’s viewpoint, and suggested tapers were clinician-initiated in response to concerning patient behaviors such as unexpected urine drug test results or running out of medications early. For example, one clinician wrote, “I explained the repercussions of [running out early] and the fact that his opioid agreement with our practice is breeched…. I’ll give him 1 month worth of oxycodone and then he’ll search for another practice that manages opioids.” Another clinician wrote, “Patient denies ongoing use; however last 2 months of utox + cocaine. Repeat utox today. Patient aware that we will continue opiate taper with continued substance use.”
Table 2.
Themes of clinician documentation about opioid tapering
| Themes | Exemplary Quote(s) |
|---|---|
| Rationale for opioid tapering predominantly focused on patient behaviors, particularly opioid or substance use | “Confronted on +cocaine on Utox - patient adamantly denies recent use. Will emphasize that if any further positive screens then we will have to reconsider giving him oxycodone script from this clinic.” |
| “Ongoing taper of Oxycodone 2/2 continued cocaine use and adultering urine samples.” | |
| “Discontinue Oxycodone, UDT are negative.” | |
| “Patient denies ongoing use; however last 2 months of utox + cocaine. Repeat utox today. Patient aware that we will continue opiate taper with continued substance use.” | |
| “I explained the repercussions of [running out early/incorrect pill count] and the fact that his opioid agreement with our practice is breeched. He understands that I will no longer prescribe his medications. I’ll give him 1 month worth of oxycodone and then he’ll search for another practice that manages opioids.” | |
| Clinician documentation of patient engagement in opioid taper was limited; clinicians frequently documented patient disagreement |
|
UDT = urine drug testing.
The second theme identified was that in scenarios where patient engagement with the opioid taper was documented, there was a wide range of responses, and patient disagreement with the clinician’s plan was prominent. Specifically, documentation of patient engagement ranged from no mention of patient agreement with a plan to taper through statements describing patients’ frank disagreement with a plan to taper. Some clinician notes documented a discussion with the patient without indicating the patient’s response, such as, “The patient was informed of the above decision.” Other clinicians documented passive agreement, for example, “[The patient] agrees with tapering Percocet.” Some clinicians documented that patients expressed hesitation or concern with the clinician’s plan, for example, “She was quite reluctant to decrease dose” and “When the conversation is initiated… he gets teary and says he’s fearful about being in pain.” Lastly, other clinicians documented that patients felt tapering was inappropriate or expressed anger. For example, “Patient requested to speak to the medical director because he did not feel that his pain was appropriately addressed” and “[The patient] expresses anger and feels his entire health care team ‘painted me as this bad person.’” Exemplary quotes across the range of patient engagement are included in Table 2.
Deductive Content Analysis
Of the 39 patient records with confirmed opioid tapers included in the study, none documented an explicit benefit-to-harm assessment. Thirty-three (85%) contained any rationale for tapering (Table 3). Twenty-two (56%) mentioned benefits of continuing opioids; of these, all 22 mentioned pain control and seven mentioned functional or quality of life benefits. Eleven (28%) mentioned observed harms of continuing opioids (most frequently, opioid use disorder), and 35 (90%) documented potential harms of continuing opioids. Assessment of inter-rater reliability using Cohen’s kappa statistic yielded very good inter-rater agreement (κ = 0.82).
Table 3.
Benefit-to-harm framework in clinician documentation about opioid tapering
| Benefit-to-Harm Framework Element | Frequency, No. (%) | Exemplary Quote |
|---|---|---|
| Rationale for opioid tapering | ||
| No mention of rationale | 6 (15) | — |
| Any mention of rationale | 33 (85) | “Ongoing taper of Oxycodone 2/2 continued cocaine use and adulterating urine samples.” |
| Opioid-related benefit | ||
| No mention of benefit | 17 (44) | — |
| Any mention of benefit | 22 (56) | |
| Analgesia | 22 | “Using dilaudid 2-3 times per day – she finds it helpful in ‘easing the pain’ but doesn’t totally ‘get rid of the pain.’” |
| Function/quality of life | 7 | “Helps her with being able to complete daily tasks and participate in the care of her 90s y/o mother…. Functional status is good.” |
| Observed opioid-related harm | ||
| No mention of observed harm | 28 (72) | — |
| Any mention of observed harm | 11 (28) | |
| Opioid use disorder | 9 | “Currently using 2-3 bags of heroin daily, via injection. Relapsed about 2 months ago.” |
| Side effect of opioid medication | 6 | “Feels sleepy from Methadone after the second dose.” |
| Potential opioid-related harm | ||
| No mention of potential harm | 4 (10) | — |
| Any mention of potential harm | 35 (90) | |
| Underlying risk factor | 29 | “Pt has a history of depression/bipolar.” |
| Concerning patient behavior | 13 | “[The patient] called, noting that he has run out of hydromorphone more than one week before expectation.” |
| Mention of discussing potential harm with patient | 26 | “I engaged [the patient] in discussion regarding very high opioid dose and concomitant multiple benzodiazepine use.” |
| Benefit-to-harm framework | ||
| No mention of benefit-to-harm assessment | 39 (100) | — |
| Any mention of benefit-to-harm assessment | 0 (0.0) | — |
Discussion
The present study is the first qualitative study of clinician documentation about opioid tapering in the patient medical record. Findings demonstrate that clinician documentation about opioid tapering often lacks a guideline-recommended benefit-to-harm framework. Clinicians’ documented rationale for tapering focused prominently on patient behaviors that could indicate risk for harms of continuing long-term opioid therapy, rather than focusing on observed benefits or observed harms. As documented by clinicians, patient engagement with opioid tapers varied widely, and disagreement with a plan to taper opioids was prominent. Taken together, these findings raise concerns that guideline recommendations to make decisions about opioid tapering using an individualized benefit-to-harm framework with an engaged patient are not consistently applied.
The present study’s findings that clinicians’ documented rationale for tapering with a focus on patient behaviors that could indicate risk for potential harms of continuing long-term opioid therapy, and that patients often disagree with a plan to taper, are consistent with and extend prior research. Particularly, a recent study of patients in the Veterans Health Administration found that 85% of discontinuations of long-term opioid therapy were clinician-initiated in response to concerning patient behaviors [31]. Thus, taking into consideration that decisions to taper opioids are largely clinician-initiated, patient engagement with a plan to taper becomes particularly important to ensure that tapers incorporate a shared understanding between the clinician and patient as is recommended [9]. To date, most studies that have found benefits of opioid tapering were comprised of patients who were consensually enrolled in opioid tapers [4, 5, 27]. Little is known about the outcomes of opioid tapers without patient engagement and whether they result in the same improvements in pain, function, quality of life, or reduced opioid problems as consensual opioid tapers [10, 32]. In fact, recent retrospective studies of clinician-initiated opioid tapers in real-world settings have identified harms associated with opioid tapering , including worsened pain and loss of function [33], termination of medical care [34], suicidal ideation [35], and overdose death [36, 37].
Important to note is that although engaging patients in shared decision-making about opioid tapering is optimal to facilitate successful opioid tapers [ 38, 39], there are circumstances where the potential or observed harms of continuing opioids are so great that a taper is indicated even if the patient disagrees [40, 41]. For example, a recent study found that the vast majority of patients continued opioid therapy following nonfatal opioid overdose, and this was associated with overdose death [40]. It is important for clinician documentation regarding opioid tapering decisions to include a clear benefit-to-harm framework for this reason. Prior research has found that predictors of tapering or discontinuation of long-term opioid therapy appropriately include previous or current substance use disorders [28, 42]. However, studies have also found black race and female gender to be associated with opioid tapering, whereas no such association was found for clinical risk factors such as benzodiazepine use [28]. The present study’s finding that clinician documentation about opioid tapering lacks the guideline-recommended benefit-to-harm framework makes understanding, and determining the appropriateness of, an opioid tapering decision difficult.
In the context of the opioid crisis in the United States and evolving standards of care for opioid tapering, the present study highlights a gap between guideline recommendations and real-world clinician documentation about decisions made for patients undergoing opioid tapers. This gap is important to address. Because the medical record is used to communicate among clinicians as well as between clinicians and patients, missing information has the potential to negatively impact patient care [36, 43]. Incomplete documentation (e.g., that focuses on potential harms but not benefits or observed harms) may bias future clinicians or cause patients to feel stigmatized [20]. In addition, accurate documentation of clinician rationale for, as well as patient engagement with, the plan for opioid taper is necessary in order to advance research that will expand our understanding of outcomes of opioid tapering in real- world settings. To be consistent with guideline recommendations, a clinician’s benefit-to-harm assessment should explicitly acknowledge and weigh the benefits of continuing long-term opioid therapy vis-a-vis the potential and observed harms. For example, one could document the following: “In light of the patient’s recent admission for sedation and fall, as well as the lack of functional benefit, the harms of continuing opioid therapy at the current dose seem to outweigh the benefits. Thus, we discussed opioid tapering, and the patient expressed hesitancy but agreed to make a dose reduction at this time.”
Although the strengths of this study include a real-world and racially diverse population, the study also has limitations. It was conducted at a single institution. To optimize specificity, we included records of patients who met a conservative definition of an opioid taper, requiring at least a 30% dose reduction in a six-month period, resulting in a small but well-specified sample. It is possible that these findings are not representative of slower or nonlinear tapers or tapering attempts that resulted in a dose reduction of <30%. The resulting sample had a high proportion of patients with HIV or sickle cell disease and patients enrolled in opioid treatment programs, which may reflect overselection of patients who had routine and consistent follow-up in which tapers of 30% in six months occurred. This may limit generalizability. Additionally, it is important to note that clinician documentation may not always accurately reflect clinician decision-making or communication with the patient. Clinician documentation may include intentional or unintentional omissions, have a particular focus, or be influenced by external forces such as concern about liability or billing. However, because the medical record serves a critical role in patient care, documentation is important in its own right.
This work underscores the need for future initiatives to help develop standardized ways of incorporating a benefit-to-harm framework, as well as patient engagement, into clinician decisions and documentation about opioid tapering. Medical record documentation serves not only to communicate between health care clinicians but also to communicate with patients, and therefore it is important that documentation be informative and understandable. Future studies are needed to determine best practices for increasing patient engagement with opioid tapers and to examine patient outcomes of opioid tapers that lack patient engagement.
Acknowledgments
We would like to thank the Substance Use Affinity Group of the Division of General Internal Medicine at Montefiore Medical Center for their feedback on this project.
Contributor Information
Michele Buonora, Department of Medicine, Albert Einstein College of Medicine and Montefiore Health System, Bronx, New York.
Hector R Perez, Department of Medicine, Albert Einstein College of Medicine and Montefiore Health System, Bronx, New York.
Jordan Stumph, Department of Physical Medicine and Rehabilitation, New York-Presbyterian Columbia/Cornell, New York, New York.
Robert Allen, Department of Emergency Medicine, SUNY Downstate Medical Center, Brooklyn, New York.
Shadi Nahvi, Department of Medicine, Albert Einstein College of Medicine and Montefiore Health System, Bronx, New York.
Chinazo O Cunningham, Department of Medicine, Albert Einstein College of Medicine and Montefiore Health System, Bronx, New York.
Jessica S Merlin, Center for Research on Healthcare, Divisions of General Internal Medicine and Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Joanna L Starrels, Department of Medicine, Albert Einstein College of Medicine and Montefiore Health System, Bronx, New York.
Funding sources: Support was provided by the following grants: R01DA039046 and K24DA046309 (JS), K24DA036955 (CC), and K23DA044327 (HP), as well as the Einstein-Montefiore Clinical and Translational Science Award (supported by National Institutes of Health/National Center for Advancing Translational Science grant number UL1TR001073). Additionally, JS receives research support from the Opioid Post-Marketing Requirement Consortium, an Food and Drug Administration–mandated consortium of opioid manufacturers, for an observational study of the risks of opioids. SN receives research support (active and placebo varenicline) from Pfizer.
Conflicts of interest: The other authors have no conflicts of interest to disclose, and no commercial entities were involved in any way with this study.
Prior presentation: Preliminary findings from this study were presented at the Association for Multidisciplinary Education and Research in Substance use and Addiction (AMERSA) 42nd Annual National Conference in San Francisco on November 8, 2018.
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