Search

To investigate how clinicians correct patient misconceptions, we analyzed 23 video recordings of primary care visits. Analysis focused on operationalizing, identifying, and characterizing clinician corrections, integrating two inductive approaches: microanalysis of clinical interaction and conversation analysis. According to our definition, patient misconception-clinician correction episodes met three essential criteria: (1) the clinician refuted something the patient had said, (2) which the patient had presented without uncertainty, and (3) which contained a proposition that was factually incorrect. We identified 59 such episodes; the patient misconceptions most commonly related to medication issues; fewer than half had foreseeable implications for patients' future actions. We identified seven clinician correction practices: Three direct practices (displaying surprise, marking disagreement, contradicting the patient) and four indirect practices (presenting the correct proposition, providing explanations, invoking an outside authority, demonstrating with evidence). We found an almost equal distribution of these direct and indirect practices.

State and national guidelines recommend that prescribing opioids for chronic pain should be based on patients’ progress towards mutually agreed on, objective treatment goals. Physicians lack practical advice on discussing goals. We lack research on how, when, and why patients with chronic pain discuss treatment goals during clinic visits.

BACKGROUND: Both increases and decreases in patients prescribed daily opioid dose have been linked to increased overdose risk, but associations between 30-day dose trajectories and subsequent overdose risk have not been systematically examined. OBJECTIVE: To examine the associations between 30-day prescribed opioid dose trajectories and fatal opioid overdose risk during the subsequent 15 days. DESIGN: Statewide cohort study using linked prescription drug monitoring program and death certificate data. We constructed a multivariable Cox proportional hazards model that accounted for time-varying prescription-, prescriber-, and pharmacy-level factors. PARTICIPANTS: All patients prescribed an opioid analgesic in California from March to December, 2013 (5,326,392 patients). MAIN MEASURES: Dependent variable: fatal drug overdose involving opioids. Primary independent variable: a 16-level variable denoting all possible opioid dose trajectories using the following categories for current and 30-day previously prescribed daily dose: 0-29, 30-59, 60-89, or ≥90 milligram morphine equivalents (MME). KEY RESULTS: Relative to patients prescribed a stable daily dose of 0-29 MME, large (≥2 categories) dose increases and having a previous or current dose ≥60 MME per day were associated with significantly greater 15-day overdose risk. Patients whose dose decreased from ≥90 to 0-29 MME per day had significantly greater overdose risk compared to both patients prescribed a stable daily dose of ≥90 MME (aHR 3.56, 95%CI 2.24-5.67) and to patients prescribed a stable daily dose of 0-29 MME (aHR 7.87, 95%CI 5.49-11.28). Patients prescribed benzodiazepines also had significantly greater overdose risk; being prescribed Z-drugs, carisoprodol, or psychostimulants was not associated with overdose risk. CONCLUSIONS: Large (≥2 categories) 30-day dose increases and decreases were both associated with increased risk of fatal opioid overdose, particularly for patients taking ≥90 MME whose opioids were abruptly stopped. Results align with 2022 CDC guidelines that urge caution when reducing opioid doses for patients taking long-term opioid for chronic pain.

OBJECTIVES: Effective communication skills are essential for optimally managing chronic pain and opioids. This exploratory, sequential mixed methods study tested the effect of a novel framework designed to improve pain-related communication and outcomes. METHODS: Study 1 developed a novel 5-step framework for helping primary care clinicians discuss chronic pain and opioids with patients. Study 2 pilot tested an intervention for teaching this framework using standardized patient instructors-actors trained to portray patients and provide immediate clinician feedback-deployed during regular clinic hours. Primary care physicians were randomized to receive either the intervention or pain management recommendations from the Centers for Disease Control and Prevention. Primary outcomes were pain-related interference at 2 months and clinician use of targeted communication skills (coded from transcripts of audio-recorded visits); secondary outcomes were pain intensity at 2 months, clinician self-efficacy for communicating about chronic pain, patient experience, and clinician-reported visit difficulty. RESULTS: We enrolled 47 primary care physicians from 2 academic teaching clinics and recorded visits with 48 patients taking opioids for chronic pain who had an appointment scheduled with an enrolled physician. The intervention was not associated with significant changes in primary or secondary outcomes other than clinician self-efficacy, which was significantly greater in the intervention group. DISCUSSION: This study developed a novel framework and intervention for teaching clinician pain-related communications skills. Although the intervention showed promise, more intensive or multicomponent interventions may be needed to have a significant impact on clinicians pain-related communication and pain outcomes.

Approximately 20% of the US adult population experiences chronic pain.1 In one study, 59% of hospitalized patients reported pain, with 10% reporting inadequately controlled pain.2 Yet, little research has been conducted on how physicians communicate with each other about pain, especially during end-of-shift handoffs. Research question: how do resident and attending physicians discuss pain in end-of shift handoffs?

BACKGROUND: Patients on long-term opioid therapy are particularly vulnerable to disruptions in medication access, especially during traumatic and chaotic events such as wildfires and other natural disasters. OBJECTIVES: To determine whether past highly destructive California wildfires were associated with disrupted access to prescription opioids for patients receiving long-term, and therefore physically dependent on, opioid medications. METHODS: Using California prescription drug monitoring program data, this retrospective study selected patients with long-term prescription opioid use episodes residing in ZIP code tabulation areas impacted by either the Camp Fire or Tubbs Fire. Autoregressive integrated moving average time series models were fit to pre-fire data to forecast post-fire expected values and then compared with observed post-fire data, specifically for weekly proportions of long-term episodes with early fills, late fills, changes in patients prescriber and pharmacy, and fills within a different ZIP code tabulation area than the patients residence. RESULTS: After the Camp Fire, there were significant spikes in the proportions of early fills (peak at 56% of total, week 1 after fire), late fills (peak at 29%, week 6), and immediate significant increases in prescriber (peak at 37%, week 3) and pharmacy changes (peak at 71%, week 1) in high-impact ZIP code tabulation areas. Low-impact ZIP code tabulation areas experienced no similar disruptions. Disruptions due to the Tubbs Fire were far less severe. CONCLUSION: Access to prescription opioids was greatly disrupted for patients living in areas most impacted by the Camp Fire. Future research should explore effectiveness of current state and federal controlled substance prescribing policies to determine what improvements are needed to minimize disruptions in medication access due to wildfires and other natural disasters.

BackgroundLimiting the incidence of opioid-naïve patients who transition to long-term opioid use (i.e., continual use for > 90 days) is a key strategy for reducing opioid-related harms.ObjectiveTo identify variables constructed from data routinely collected by prescription drug monitoring programs that are associated with opioid-naïve patients' likelihood of transitioning to long-term use after an initial opioid prescription.DesignStatewide cohort study using prescription drug monitoring program data PARTICIPANTS: All opioid-naïve patients in California (no opioid prescriptions within the prior 2 years) age ≥ 12 years prescribed an initial oral opioid analgesic from 2010 to 2017.Methods and main measuresMultiple logistic regression models using variables constructed from prescription drug monitoring program data through the day of each patient's initial opioid prescription, and, alternatively, data available up to 30 and 60 days after the initial prescription were constructed to identify probability of transition to long-term use. Model fit was determined by the area under the receiver operating characteristic curve (C-statistic).Key resultsAmong 30,569,125 episodes of patients receiving new opioid prescriptions, 1,809,750 (5.9%) resulted in long-term use. Variables with the highest adjusted odds ratios included concurrent benzodiazepine use, ≥ 2 unique prescribers, and receipt of non-pill, non-liquid formulations. C-statistics for the day 0, day 30, and day 60 models were 0.81, 0.88, and 0.94, respectively. Models assessing opioid dose using the number of pills prescribed had greater discriminative capacity than those using milligram morphine equivalents.ConclusionsData routinely collected by prescription drug monitoring programs can be used to identify patients who are likely to develop long-term use. Guidelines for new opioid prescriptions based on pill counts may be simpler and more clinically useful than guidelines based on days' supply or milligram morphine equivalents.

BackgroundTools are needed to aid clinicians in estimating their patients' risk of transitioning to long-term opioid use and to inform prescribing decisions.ObjectiveThe objective of this study was to develop and validate a model that predicts previously opioid-naive patients' risk of transitioning to long-term use.Research designThis was a statewide population-based prognostic study.SubjectsOpioid-naive (no prescriptions in previous 2 y) patients aged 12 years old and above who received a pill-form opioid analgesic in 2016-2018 and whose prescriptions were registered in the California Prescription Drug Monitoring Program (PDMP).MeasuresA multiple logistic regression approach was used to construct a prediction model with long-term (ie, >90 d) opioid use as the outcome. Models were developed using 2016-2017 data and validated using 2018 data. Discrimination (c-statistic), calibration (calibration slope, intercept, and visual inspection of calibration plots), and clinical utility (decision curve analysis) were evaluated to assess performance.ResultsDevelopment and validation cohorts included 7,175,885 and 2,788,837 opioid-naive patients with outcome rates of 5.0% and 4.7%, respectively. The model showed high discrimination (c-statistic: 0.904 for development, 0.913 for validation), was well-calibrated after intercept adjustment (intercept, -0.006; 95% confidence interval, -0.016 to 0.004; slope, 1.049; 95% confidence interval, 1.045-1.053), and had a net benefit over a wide range of probability thresholds.ConclusionsA model for the transition from opioid-naive status to long-term use had high discrimination and was well-calibrated. Given its high predictive performance, this model shows promise for future integration into PDMPs to aid clinicians in formulating opioid prescribing decisions at the point of care.

ObjectivesOpioid use disorder remains undertreated in the United States. One of the primary mechanisms for expanding access to treatment has been the use of buprenorphine. In this study, we compare prescribing trends of buprenorphine paid through Medicaid versus other payer sources.MethodsCombined data from California's prescription drug monitoring program and California's Department of Health Care Services was used to obtain statewide quarterly prescription rates for buprenorphine, indicated for the treatment of opioid use disorder, from 2012 to 2018.ResultsFrom 2012 to 2018, the rate of individuals treated with buprenorphine in Medicaid increased by 657% (1.39-10.5 Medicaid beneficiaries per 10,000) with increases beginning in 2014 and continuing through 2018. Rate of individual prescribing among non-Medicaid sources increased by 93.7% (6.54-12.7 non-Medicaid individuals per 10,000) with most increases occurring before 2014.ConclusionsCalifornia Medicaid has made considerable gains in buprenorphine access, with access growing steadily even after expansions through the Affordable Care Act plateaued. In contrast, recent gains in buprenorphine access for individuals without Medicaid are uninspiring, indicating that initiatives to improve buprenorphine access to patients without Medicaid are urgently needed.

Drug, and specifically opioid-related, overdoses remain a major public health problem in the United States. Multiple studies have examined individual risk factors associated with overdose risk, but research developing clinical risk prediction tools for overdose has only emerged in the last few years. We conducted a comprehensive review of the literature on patient-level factors associated with opioid-related overdose risk, with an emphasis on clinical risk prediction models for opioid-related overdose in the United States. Studies that developed and/or validated clinical prediction models were closely reviewed and evaluated to determine the state of the field. We identified 12 studies that reported risk prediction models for opioid-related overdose risk. Published models were developed from a variety of data sources, including Veterans Health Administration data, Medicare data, commercial insurance data, and statewide linked datasets. Studies reported model performance using measures of discrimination, usually at good-to-excellent levels, though they did not always assess calibration. C-statistics were better for models that included clinical predictors (c-statistics: 0.75-0.95) compared to models without them (c-statistics: 0.69-0.82). External validation of models was rare, and we found no studies evaluating implementation of models or risk prediction tools into clinical practice. A common feature of these models was a high rate of false positives, largely because opioid-related overdose is rare in the general population. Thus, efforts to implement prediction models into practice should take into account that published models overestimate overdose risk for many low-risk patients. Future prediction models assessing overdose risk should employ external validation and address model calibration. In order to translate findings from prediction models into clinical public health benefit, future studies should focus on developing clinical prediction tools based on prediction models, implementing these tools into clinical practice, and evaluating the impact of these models on treatment decisions, patient outcomes, and, ultimately, opioid overdose rates.

BackgroundNarrative communication is often more persuasive for promoting health behaviour change than communication using facts and figures; the extent to which narrative persuasiveness is due to patients' identification with the storyteller vs engagement with the story is unclear.ObjectiveTo examine the relative impacts of patient engagement, age concordance and gender concordance on perceived persuasiveness of video-recorded narrative clips about opioid tapering.MethodsPatient raters watched and rated 48 brief video-recorded clips featuring 1 of 7 different storytellers describing their experiences with opioid tapering. The dependent variable was clips' perceived persuasiveness for encouraging patients to consider opioid tapering. Independent variables were rater engagement with the clip, rater-storyteller gender concordance and rater-storyteller age concordance (

ObjectiveThe University of California (UC) leadership sought to develop a robust educational response to the epidemic of opioid-related deaths. Because the contributors to this current crisis are multifactorial, a comprehensive response requires educating future physicians about safe and effective management of pain, safer opioid prescribing, and identification and treatment of substance use disorder (SUD).MethodsThe six UC medical schools appointed an opioid crisis workgroup to develop educational strategies and a coordinated response to the opioid epidemic. The workgroup had diverse specialty and disciplinary representation. This workgroup focused on developing a foundational set of educational competencies for adoption across all UC medical schools that address pain, SUD, and public health concerns related to the opioid crisis.ResultsThe UC pain and SUD competencies were either newly created or adapted from existing competencies that addressed pain, SUD, and opioid and other prescription drug misuse. The final competencies covered three domains: pain, SUD, and public health issues related to the opioid crisis.ConclusionsThe authors present a novel set of educational competencies as a response to the opioid crisis. These competencies emphasize the subject areas that are fundamental to the opioid crisis: pain management, the safe use of opioids, and understanding and treating SUD.

ObjectiveTo compare effectiveness of a narrative-based educational video versus an informational pamphlet for increasing patients' self-efficacy and intention to taper their opioid use.MethodsFive thousand participants recruited from MTurk were screened to identify eligible patients. Eligible participants (n = 365, 49.9 % female, mean age = 37 years) were randomized to either watch the narrative video or read the pamphlet. Linear regression models were used for the main analysis.ResultsParticipants' perceptions of tapering effectiveness were higher in the video group (mean = 4.06) than the pamphlet group (mean = 3.67), adjusted mean difference = 0.34, 95 %CI 0.13 - 0.54,P < 0.001. Participants' perceptions of tapering self-efficacy were also higher in the video group (mean = 3.97) than the pamphlet group (mean = 3.60), adjusted mean difference = 0.32, 95 %CI 0.09 - 0.55, P < 0.001. Perceived tapering effectiveness and self-efficacy were both positively associated with post-intervention tapering intention (Spearman rank correlation coefficient = 0.38 and 0.53, respectively, both P < 0.001).ConclusionA narrative-based video about opioid tapering enhanced patients' perceptions of the effectiveness of tapering and their tapering self-efficacy.Practice implicationsNarrative-based videos may be effective for changing patient attitudes about opioid tapering.

BackgroundAgenda setting is associated with more efficient care and better patient experience. This study develops a taxonomy of visit opening styles to assess use of agenda and non-agenda setting visit openings and their effects on participant experience.MethodsThis observational study analyzed 83 video recorded US primary care visits at a single academic medical center in California involving family medicine and internal medicine resident physicians (n = 49) and patients (n = 83) with chronic pain on opioids. Using conversation analysis, we developed a coding scheme that assessed the presence of agenda setting, distinct visit opening styles, and the number of total topics, major topics, surprise patient topics, and returns to prior topics discussed. Exploratory quantitative analyses were conducted to assess the relationship of agenda setting and visit opening styles with post-visit measures of both patient experience and physician perception of visit difficulty.ResultsWe identified 2 visit opening styles representing agenda setting (agenda eliciting, agenda reframing) and 3 non-agenda setting opening styles (open-ended question, patient launch, physician launch). Agenda setting was only performed in 11% of visits and was associated with fewer surprise patient topics than visits without agenda setting (mean (SD) 2.67 (1.66) versus 4.28 (3.23), p = 0.03).ConclusionsIn this study of patients with chronic pain, resident physicians rarely performed agenda setting, whether defined in terms of "agenda eliciting" or "agenda re-framing." Agenda setting was associated with fewer surprise topics. Understanding the communication context and outcomes of agenda setting may inform better use of this communication tool in primary care  practice.

BackgroundIn 2016, California updated its prescription drug monitoring program (PDMP), adding two key features: automated proactive reports to prescribers and mandatory registration for prescribers and pharmacists. The effects of these changes on prescribing patterns have not yet been examined. We aimed to evaluate the joint effect of these two PDMP features on county-level prescribing practices in California.MethodsUsing county-level quarterly data from 2012 to 2017, we estimated the absolute change associated with the implementation of these two PDMP features in seven prescribing indicators in California versus a control group comprising counties in Florida and Washington: opioid prescription rate per 1000 residents; patients' mean daily opioid dosage in milligrams of morphine equivalents[MME]; prescribers' mean daily MME prescribed; prescribers' mean number of opioid prescriptions per day; percentage of patients getting >90 MME/day; percentage of days with overlapping prescriptions for opioids and benzodiazepines; multiple opioid provider episodes per 100,000 residents.ResultsProactive reports and mandatory registration were associated with a 7.7 MME decrease in patients' mean daily opioid dose (95 %CI: -11.4, -2.9); a 1.8 decrease in the percentage of patients prescribed high-dose opioids (95 %CI: -2.3, -0.9); and a 6.3 MME decrease in prescribers' mean daily dose prescribed (95 %CI: -10.0, -1.3).ConclusionsCalifornia's implementation of these two PDMP features was associated with decreases in the total quantity of opioid MMEs prescribed, and indicators of patients prescribed high-dose opioids compared to states that had PDMP's without these features. Rates of opioid prescribing and other high-risk prescribing patterns remained unchanged.

Patient-clinician interactions are central to technical and interpersonal processes of medical care. Video recordings of these interactions provide a rich source of data and a stable record that allows for repeated viewing and analysis. Collecting video recordings requires navigating ethical and feasibility constraints; further, realizing the potential of video requires specialized research skills. Interdisciplinary collabo-rations involving practitioners, medical educators, and social scientists are needed to provide the clinical perspectives, methodological expertise, and capacity needed to make collecting video worthwhile. Such collaboration ensures that research questions will be based on scholarship from the social sciences, resonate with practice, and produce results that fit educational needs. However, the literature lacks suggested practices for building and sustaining interdisciplinary research collaborations involving video data. In this paper, we provide concrete advice based on our experience collecting and analyzing a single set of video-recorded clinical encounters and non-video data, which have so far yielded nine distinct studies. We present the research process, timeline, and advice based on our experience with interdisciplinary collaboration. We found that integrating disciplines and traditions required patience, compromise, and mutual respect; learning from each other enhanced our enjoyment of the process, our productivity, and the clinical relevance of our research.

BackgroundPrescription drug monitoring programs (PDMPs) are primary prevention tools to reduce substance use disorders (SUD) and sequelae. Evidence regarding perceptions of PDMPs from different primary care providers, which may impact PDMP utilization for women, is unavailable.ObjectiveTo examine perceived PDMP effectiveness among obstetrician-gynecologists (OB/GYNs) compared to primary care physicians (PCPs).MethodsIndependent surveys of PDMP users in Florida, Kentucky, and California were evaluated based on a Likert-type item to assess perception of PDMP effectiveness in reducing prescription drug abuse and diversion. Response distributions of OB/GYNs versus PCPs were compared using chi-square tests.ResultsIn Florida, there were 41 OB/GYN and 511 PCP respondents; Kentucky, 46 OB/GYNs and 265 PCPs; and California, 41 OB/GYNs and 162 PCPs. In each state OB/GYNs viewed PDMPs as less effective, positive, or useful compared to PCPs (p ≤ 0.01, all states): Florida: 64.1% OB/GYN vs. 83.7% PCP "agree positive impact"; Kentucky: 45.0% OB/GYN vs. 68.5% PCP "effective". California: 73.2% OB/GYN vs. 86.4% PCP "useful".ConclusionsThese results suggest OB/GYNs view their state's PDMP as less effective than do PCPs, which may present barriers to PDMP utilization and decrease opportunities for SUD interventions. Engagement of all healthcare team members is needed to inform future strategies and policies to increase PDMP effectiveness.

BackgroundPhysicians' fear of difficult patient interactions is an important barrier to discontinuing long-term opioid therapy.ObjectiveTo identify patient statements about opioids that indicate potential openness to tapering opioids or trying non-opioid pain treatments DESIGN: This is an observational study of regularly scheduled primary care visits involving discussion of chronic pain management. A coding system to characterize patient assessments about opioids, physician responses to assessments, and patient-endorsed opioid side effects was developed and applied to transcripts of video-recorded visits. All visits were independently coded by 2 authors.ParticipantsEighty-six established adult patients taking opioids for chronic pain; 49 physicians in 2 academic primary care clinics MAIN MEASURES: Frequency and topic of patients' opioid assessments; proportion of opioid assessments classified as clues (assessments indicating potential willingness to consider non-opioid pain treatments or lower opioid doses); physician responses to patient clues; frequency and type of patient-endorsed side effects KEY RESULTS: Patients made a mean of 3.2 opioid assessments (median 2) per visit. The most common assessment topics were pain relief (51%), effect on function (21%), and opioid safety (14%). Forty-seven percent of opioid assessments (mean 1.5 per visit) were classified as clues. Fifty-three percent of visits included ≥ 1 clue; 21% of visits contained ≥ 3 clues. Physicians responded to patient clues with no/minimal response 43% of the time, sympathetic/empathetic statements 14% of the time, and further explored clues 43% of the time. Fifty-eight percent of patients endorsed ≥ 1 opioid-related side effect; 10% endorsed ≥ 3 side effects. The most commonly endorsed side effects were constipation (15% of patients), sedation (15%), withdrawal symptoms (13%), and nausea (12%).ConclusionsPatient statements suggesting openness to non-opioid pain treatments or lower opioid doses are common during routine primary care visits. Listening for and exploring these clues may be a patient-centered strategy for broaching difficult topics with patients on long-term opioid therapy.

In recent years, the opioid crisis in the United States has sparked significant discussion on doctor-patient interactions concerning chronic pain treatments, but little to no attention has been given to investigating the vocal aspects of patient talk. This exploratory sociolinguistic study intends to fill this knowledge gap by employing prosodic discourse analysis to examine context-specific linguistic features used by the interlocutors of two distinct medical interactions. We found that patients employed both low pitch and creak as linguistic resources when describing chronic pain, narrating symptoms, and requesting opioids. The situational use of both features informs us about the linguistic ways in which patients frame fraught issues like chronic pain in light of the current opioid crisis. This study expands the breadth of phonetic analysis within the domain of discourse analysis, serving to illuminate discussions surrounding the illocutionary role of the lower vocal tract in expressing emotions.

ObjectivesOpioids and non-steroidal anti-inflammatory drugs (NSAIDs) are frequently prescribed for chronic musculoskeletal pain, despite limited evidence of effectiveness and well-documented adverse effects. We assessed the effects of participating in a structured, personalized self-experiment ("N-of-1 trial") on analgesic prescribing in patients with chronic musculoskeletal pain.MethodsWe randomized 215 patients with chronic pain to participate in an N-of-1 trial facilitated by a mobile health app or to receive usual care. Medical records of participating patients were reviewed at enrollment and 6 months later to assess analgesic prescribing. We established thresholds of ≥ 50, ≥ 20, and > 0 morphine milligram equivalents (MMEs) per day to capture patients taking relatively high doses only, patients taking low-moderate as well as relatively high doses, and patients taking any dose of opioids, respectively.ResultsThere was no significant difference between the N-of-1 and control groups in the percentage of patients prescribed any opioids (relative odds ratio (ROR) = 1.05; 95% confidence interval [CI] = 0.61 to 1.80, p = 0.87). There was a clinically substantial but statistically not significant reduction of the percentage of patients receiving ≥ 20 MME (ROR = 0.58; 95% CI = 0.33 to 1.04, p = 0.07) and also in the percentage receiving ≥ 50 MME (ROR = 0.50; 95% CI = 0.19 to 1.34, p = 0.17). There was a significant reduction in the proportion of patients in the N-of-1 group prescribed NSAIDs compared with control (relative odds ratio = 0.53; 95% CI = 0.29 to 0.96, p = 0.04), with no concomitant increase in average pain intensity. There was no significant change in use of adjunctive medications (acetaminophen, gabapentenoids, or topicals).DiscussionThese exploratory results suggest that participation in N-of-1 trials may reduce long-term use of NSAIDs; there is also a weak signal for an effect on use of opioids. Additional research is needed to confirm these results and elucidate possible mechanisms.Trial registrationClinicalTrials.gov Identifier: NCT02116621.

BackgroundPrescription drug monitoring programs (PDMPs) that collect and distribute information on dispensed controlled substances have been adopted by nearly all US states. We know little about program characteristics that modify PDMP impact on prescription opioid (PO) overdose deaths.MethodsWe measured associations between adoption of any PDMP and changes in fatal PO overdoses in 2002-2016 across 3109 counties in 49 states and D.C. We then measured changes related to the adoption of "proactive PDMPs," which report outlying prescribing/dispensing patterns and provide broader access to PDMP data by law enforcement. Comparisons were made within 3 time intervals that broadly represent the evolution of PDMPs (2002-2004, 2005-2009, and 2010-2016). We modeled overdoses using Bayesian space-time models.ResultsAdoption of electronic PDMP access was associated with 9% lower rates of fatal PO overdoses after three years (rate ratio [RR] = 0.91, 95% credible interval [CI]: 0.88-0.93) with well-supported effects for methadone (RR = 0.86,95% CI: 0.82-0.90) and other synthetic opioids (RR = 0.82, 95% CI: 0.77-0.86). Compared with states with no/weak PDMPs, proactive PDMPs were associated with fewer deaths attributed to natural/semi-synthetic opioids (2002-2004: RR = 0.72 [0.66-0.78]; 2005-2009: RR = 0.93 [0.90-0.97]; 2010-2016: 0.89 [0.86-0.92]) and methadone (2002-2004: RR = 0.77 [0.69-0.85]; 2010-2016: RR = 0.90 [0.86-0.94]). Unintended effects were observed for synthetic opioids other than methadone (2005-2009: RR = 1.29 [1.21-1.38]; 2010-2016: RR = 1.22 [1.16-1.29]).ConclusionsState adoption of PDMPs was associated with fewer PO deaths overall while proactive PDMPs alone were associated with fewer deaths related to natural/semisynthetic opioids and methadone, the specific targets of these programs. See video abstract at, http://links.lww.com/EDE/B619.

Objective: To describe trends in prevalent and incident stimulant prescribing between 2008 and 2017 in California. Method: Statewide trends were estimated by age and sex category for prevalent (any) and incident (no prescriptions in the preceding 2 years) stimulant prescribing while adjusting for area-level covariates. Results: Prevalent prescribing rates increased by 126%, while incident prescribing increased 23%. Patients aged 25 to 44 years experienced over 200% increases in prevalent prescribing and 34% to 55% increases in incident prescribing. Among patients older than 25, women had consistently higher prescribing rates than men. ZIP code tabulation areas with the largest minority populations had the lowest baseline prescribing rates but experienced the greatest annual prescription rate increases. Conclusion: Adult stimulant prescribing increased substantially for early working aged adults. Prescription rates were greater for women than men.

BACKGROUND:Prescription drug monitoring programs (PDMP), by reducing access to prescribed opioids (POs), may contribute to a policy environment in which some people with opioid dependence are at increased risk for transitioning from POs to heroin/other illegal opioids. This study examines how PDMP adoption and changes in the characteristics of PDMPs over time contribute to changes in fatal heroin poisoning in counties within states from 2002 to 2016. METHODS:Latent transition analysis to classify PDMPs into latent classes (Cooperative, Proactive, and Weak) for each state and year, across three intervals (1999-2004, 2005-2009, 2010-2016). We examined the association between probability of PDMP latent class membership and the rate of county-level heroin poisoning death. RESULTS:After adjustment for potential county-level confounders and co-occurring policy changes, adoption of a PDMP was significantly associated with increased heroin poisoning rates (22% increase by third year post-adoption). Findings varied by PDMP type. From 2010-2016, states with Cooperative PDMPs (those more likely to share data with other states, to require more frequent reporting, and include more drug schedules) had 19% higher heroin poisoning rates than states with Weak PDMPs (adjusted rate ratio [ARR] = 1.19; 95% CI = 1.14, 1.25). States with Proactive PDMPs (those more likely to report outlying prescribing and dispensing and provide broader access to law enforcement) had 6% lower heroin poisoning rates than states with No/Weak PDMPs (ARR = 0.94; 95% CI = 0.90, 0.98). CONCLUSION:There is a consistent, positive association between state PDMP adoption and heroin poisoning mortality. However, this varies by PDMP type, with Proactive PDMPs associated with a small reduction in heroin poisoning deaths. This raises questions about the potential for PDMPs to support efforts to decrease heroin overdose risk, particularly by using proactive alerts to identify patients in need of treatment for opioid use disorder. Future research on mechanisms explaining the reduction in heroin poisonings after enactment of Proactive PDMPs is merited.

BackgroundPain management racial disparities exist, yet it is unclear whether disparities exist in pain management in advanced cancer.ObjectiveTo examine the effect of race on physicians' pain assessment and treatment in advanced lung cancer and the moderating effect of patient activation.DesignRandomized field experiment. Physicians consented to see two unannounced standardized patients (SPs) over 18 months. SPs portrayed 4 identical roles-a 62-year-old man with advanced lung cancer and uncontrolled pain-differing by race (black or white) and role (activated or typical). Activated SPs asked questions, interrupted when necessary, made requests, and expressed opinions.ParticipantsNinety-six primary care physicians (PCPs) and oncologists from small cities, and suburban and rural areas of New York, Indiana, and Michigan. Physicians' mean age was 52 years (SD = 27.17), 59% male, and 64% white.Main measuresOpioids prescribed (or not), total daily opioid doses (in oral morphine equivalents), guideline-concordant pain management, and pain assessment.Key resultsSPs completed 181 covertly audio-recorded visits that had complete data for the model covariates. Physicians detected SPs in 15% of visits. Physicians prescribed opioids in 71% of visits; 38% received guideline-concordant doses. Neither race nor activation was associated with total opioid dose or guideline-concordant pain management, and there were no interaction effects (p > 0.05). Activation, but not race, was associated with improved pain assessment (ẞ, 0.46, 95% CI 0.18, 0.74). In post hoc analyses, oncologists (but not PCPs) were less likely to prescribe opioids to black SPs (OR 0.24, 95% CI 0.07, 0.81).ConclusionsNeither race nor activation was associated with opioid prescribing; activation was associated with better pain assessment. In post hoc analyses, oncologists were less likely to prescribe opioids to black male SPs than white male SPs; PCPs had no racial disparities. In general, physicians may be under-prescribing opioids for cancer pain.Trial registrationNCT01501006.

Background and aimsPrescription drug monitoring programs (PDMP), defined as state-level databases used in the United States that collect prescribing information when controlled substances are dispensed, have varied substantially between states and over time. Little is known about the combinations of PDMP features that, collectively, may produce the greatest impact on prescribing and overdose. We aimed to (1) identify the types of PDMP models that have developed from 1999 to 2016, (2) estimate whether states have transitioned across PDMP models over time and (3) examine whether states have adopted different types of PDMP models in response to the burden of opioid overdose.MethodsA latent transition analysis of PDMP models based on an adaptation of nine PDMP characteristics classified by prescription opioid policy experts as potentially important determinants of prescribing practices and prescription opioid overdose events.ResultsWe divided the time-period into three intervals (1999-2004, 2005-09, 2010-16), and found three distinct PDMP classes in each interval. The classes in the first and second interval can be characterized as 'no/weak', 'proactive' and 'reactive' types of PDMPs, and in the third interval as 'weak', 'cooperative' and 'proactive'. The meaning of these classes changed over time: until 2009, states in the 'no/weak' class had no active PDMP, whereas states in the 'proactive' class were more likely to proactively provide unsolicited information to PDMP users, provide open access to law enforcement, and require more frequent data reporting than states in the 'reactive' class. In 2010-16, the 'weak' class resembled the 'reactive' class in previous intervals. States in the 'cooperative' class in 2010-16 were less likely than states in the 'proactive' class to provide unsolicited reports proactively or to provide open access to law enforcement; however, they were more likely than those in the 'proactive' class to share PDMP data with other states and to report more federal drug schedules.ConclusionsSince 1999, US states have tended to transition to more robust classes of prescription drug monitoring programs. Opioid overdose deaths in prior years predicted the state's prescription drug monitoring program class but did not predict transitions between prescription drug monitoring program classes over time.

Clinical guidelines discourage prescribing opioids for chronic pain, but give minimal advice about how to discuss opioid tapering with patients. We conducted focus groups and interviews involving 21 adults with chronic back or neck pain in different stages of opioid tapering. Transcripts were qualitatively analyzed to characterize patients' tapering experiences, build a conceptual model of these experiences, and identify strategies for promoting productive discussions of opioid tapering. Analyses revealed 3 major themes. First, owing to dynamic changes in patients' social relationships, emotional state, and health status, patients' pain and their perceived need for opioids fluctuate daily; this finding may conflict with recommendations to taper by a certain amount each month. Second, tapering requires substantial patient effort across multiple domains of patients' everyday lives; patients discuss this effort superficially, if at all, with clinicians. Third, patients use a variety of strategies to manage the tapering process (eg, keeping an opioid stash, timing opioid consumption based on planned activities). Recommendations for promoting productive tapering discussions include understanding the social and emotional dynamics likely to impact patients' tapering, addressing patient fears, focusing on patients' best interests, providing anticipatory guidance about tapering, and developing an individualized tapering plan that can be adjusted based on patient response. Perspective: This study used interview and focus group data to characterize patients' experiences with opioid tapering and identify communication strategies that are likely to foster productive, patient-centered discussions of opioid tapering. Findings will inform further research on tapering and help primary care clinicians to address this important, often challenging topic.

ObjectivesTo estimate the effect of California's prescription drug monitoring program's (PDMP) registration mandate on use of the PDMP.MethodsWe evaluated the effect of California's mandatory PDMP registration law by fitting time series models on the percentage of clinicians registered for California's PDMP and the percentage of clinicians who were active PDMP users (users who created ≥ 1 patient prescription reports in a given month) from 2010 through 2017. We also compared PDMP use among early PDMP adopters (clinicians who registered > 8 months before the mandatory registration deadline) versus late adopters (clinicians who registered ≤ 8 months before the deadline).ResultsMandatory registration was associated with increases in active PDMP users: 53.5% increase for prescribers and 17.9% for pharmacists. Early adopters were 4 times more likely to be active PDMP users than were late adopters.ConclusionsMandatory registration was associated with increases in PDMP registration and use, but most new registrants did not become active users. Public Health Implications. Mandatory PDMP registration increases PDMP use but does not result in widespread PDMP usage by all clinicians prescribing controlled substances.

ObjectiveProductive patient-clinician communication is an important component of effective pain management, but we know little about how patients and clinicians actually talk about pain in clinical settings and how it might be improved to produce better patient outcomes. The objective of this review was to create a conceptual model of patient-clinician communication about noncancer pain, review and synthesize empirical research in this area, and identify priorities for future research.MethodsA conceptual model was developed that drew on existing pain and health communication research. CINAHL, EMBASE, and PubMed were searched to find studies reporting empirical data on patient-clinician communication about noncancer pain; results were supplemented with manual searches. Studies were categorized and analyzed to identify crosscutting themes and inform model development.ResultsThe conceptual model comprised the following components: contextual factors, clinical interaction, attitudes and beliefs, and outcomes. Thirty-nine studies met inclusion criteria and were analyzed based on model components. Studies varied widely in quality, methodology, and sample size. Two provisional conclusions were identified: contrary to what is often reported in the literature, discussions about analgesics are most frequently characterized by patient-clinician agreement, and self-presentation during patient-clinician interactions plays an important role in communication about pain and opioids.ConclusionsPublished studies on patient-clinician communication about noncancer pain are few and diverse. The conceptual model presented here can help to identify knowledge gaps and guide future research on communication about pain. Investigating the links between communication and pain-related outcomes is an important priority for future research.

BackgroundPrescription drug monitoring programs (PDMPs) are a key component of the president's Prescription Drug Abuse Prevention Plan to prevent opioid overdoses in the United States.PurposeTo examine whether PDMP implementation is associated with changes in nonfatal and fatal overdoses; identify features of programs differentially associated with those outcomes; and investigate any potential unintended consequences of the programs.Data sourcesEligible publications from MEDLINE, Current Contents Connect (Clarivate Analytics), Science Citation Index (Clarivate Analytics), Social Sciences Citation Index (Clarivate Analytics), and ProQuest Dissertations indexed through 27 December 2017 and additional studies from reference lists.Study selectionObservational studies (published in English) from U.S. states that examined an association between PDMP implementation and nonfatal or fatal overdoses.Data extraction2 investigators independently extracted data from and rated the risk of bias (ROB) of studies by using established criteria. Consensus determinations involving all investigators were used to grade strength of evidence for each intervention.Data synthesisOf 2661 records, 17 articles met the inclusion criteria. These articles examined PDMP implementation only (n = 8), program features only (n = 2), PDMP implementation and program features (n = 5), PDMP implementation with mandated provider review combined with pain clinic laws (n = 1), and PDMP robustness (n = 1). Evidence from 3 studies was insufficient to draw conclusions regarding an association between PDMP implementation and nonfatal overdoses. Low-strength evidence from 10 studies suggested a reduction in fatal overdoses with PDMP implementation. Program features associated with a decrease in overdose deaths included mandatory provider review, provider authorization to access PDMP data, frequency of reports, and monitoring of nonscheduled drugs. Three of 6 studies found an increase in heroin overdoses after PDMP implementation.LimitationFew studies, high ROB, and heterogeneous analytic methods and outcome measurement.ConclusionEvidence that PDMP implementation either increases or decreases nonfatal or fatal overdoses is largely insufficient, as is evidence regarding positive associations between specific administrative features and successful programs. Some evidence showed unintended consequences. Research is needed to identify a set of "best practices" and complementary initiatives to address these consequences.Primary funding sourceNational Institute on Drug Abuse and Bureau of Justice Assistance.

INTRODUCTION:The purpose of this study is to extend prior research on barriers to use of a prescription drug monitoring program by examining psychosocial correlates of intended use among physicians and pharmacists. METHODS:Overall, 1,904 California physicians and pharmacists responded to a statewide survey (24.1% response rate) from August 2016 to January 2017. Participants completed an online survey examining attitudes toward prescription drug misuse and abuse, prescribing practices, prescription drug monitoring program design and ease of use, professional obligations, and normative beliefs regarding prescription drug monitoring program use. Data were analyzed in 2017. RESULTS:Perceived prescription drug monitoring program usefulness and normative beliefs fully mediated the relationship between concern about prescription drug abuse and intentions to use the prescription drug monitoring program. Clinicians' sense of professional and moral obligation to use the prescription drug monitoring program was unrelated to intention to use the prescription drug monitoring program despite a positive relationship with concern about misuse and abuse. Compared with physicians, pharmacists reported greater concern about prescription drug misuse, greater professional and moral obligation to use prescription drug monitoring program, and greater rating of prescription drug monitoring program usefulness. CONCLUSIONS:Interventions that target normative beliefs surrounding prescription drug monitoring program use and how to use prescription drug monitoring programs effectively are likely to be more effective than those that target professional obligations or moralize to the medical community.

BackgroundDecision Aids (DAs) effectively translate medical evidence for patients but are not routinely used in clinical practice. Little is known about how DAs are used during patient-clinician encounters.ObjectiveTo characterize the content and communicative function of high-quality DAs during diagnostic clinic visits for prostate cancer.Participants252 men newly diagnosed with localized prostate cancer who had received a DA, 45 treating physicians at 4 US Veterans Administration urology clinics.MethodsQualitative analysis of transcribed audio recordings was used to inductively develop categories capturing content and function of all direct references to DAs (booklet talk). The presence or absence of any booklet talk per transcript was also calculated.ResultsBooklet talk occurred in 55% of transcripts. Content focused on surgical procedures (36%); treatment choice (22%); and clarifying risk classification (17%). The most common function of booklet talk was patient corroboration of physicians' explanations (42%), followed by either physician or patient acknowledgement that the patient had the booklet. Codes reflected the absence of DA use for shared decision-making. In regression analysis, predictors of booklet talk were fewer years of patient education (P = .027) and more time in the encounter (P = .027). Patient race, DA type, time reading the DA, physician informing quality and physician age did not predict booklet talk.ConclusionsResults show that good decision aids, systematically provided to patients, appeared to function not to open up deliberations about how to balance benefits and harms of competing treatments, but rather to allow patients to ask narrow technical questions about recommended treatments.

Patients and physicians report that communication about chronic pain and opioids is often challenging, but there is little empirical research on whether patient-physician communication about pain affects patient and physician visit experience. This study video recorded 86 primary care visits involving 49 physicians and 86 patients taking long-term opioids for chronic musculoskeletal pain, systematically coded all pain-related utterances during these visits using a custom-designed coding system, and administered previsit and postvisit questionnaires. Multiple regression was used to identify communication behaviors and patient characteristics associated with patients' ratings of their visit experience, physicians' ratings of visit difficulty, or both. After adjusting for covariates, 2 communication variables-patient-physician disagreement and patient requests for opioid dose increases-were each significantly associated with both worse ratings of patient experience and greater physician-reported visit difficulty. Patient desire for increased pain medicine was also significantly positively associated with both worse ratings of patient experience and greater physician-reported visit difficulty. Greater pain severity and more patient questions were each significantly associated with greater physician-reported visit difficulty, but not with patient experience. The association between patient requests for opioids and patient experience ratings was wholly driven by 2 visits involving intense conflict with patients demanding opioids. Patient-physician communication during visits is associated with patient and physician ratings of visit experience. Training programs focused on imparting communication skills that assist physicians in negotiating disagreements about pain management, including responding to patient requests for more opioids, likely have potential to improve visit experience ratings for both patients and physicians.

BackgroundRacial disparities exist in the care provided to advanced cancer patients. This article describes an investigation designed to advance the science of healthcare disparities by isolating the effects of patient race and patient activation on physician behavior using novel standardized patient (SP) methodology.Methods/designThe Social and Behavioral Influences (SBI) Study is a National Cancer Institute sponsored trial conducted in Western New York State, Northern/Central Indiana, and lower Michigan. The trial uses an incomplete randomized block design, randomizing physicians to see patients who are either black or white and who are "typical" or "activated" (e.g., ask questions, express opinions, ask for clarification, etc.). The study will enroll 91 physicians.DiscussionThe SBI study addresses important gaps in our knowledge about racial disparities and methods to reduce them in patients with advanced cancer by using standardized patient methodology. This study is innovative in aims, design, and methodology and will point the way to interventions that can reduce racial disparities and discrimination and draw links between implicit attitudes and physician behaviors.Trial registrationhttps://clinicaltrials.gov/ , #NCT01501006, November 30, 2011.

ObjectiveAssess patient-physician agreement on management goals for chronic musculoskeletal pain and its associations with patient and physician visit experiences.Materials and methodsPre-visit and post-visit questionnaires for 87 primary care visits that involved patients taking opioids for chronic musculoskeletal pain and primary care resident physicians. After each visit, patients and physicians independently ranked 5 pain treatment goals from most to least important.ResultsIn total, 48% of patients ranked reducing pain intensity as their top priority, whereas 22% ranked finding a diagnosis as most important. Physicians ranked improving function as the top priority for 41% of patients, and ranked reducing medication side effects as most important for 26%. The greatest difference between patient and physician rankings was for reducing pain intensity. In regression analyses, neither overall agreement on goals (ie, the physician's first or second priority included the patient's top priority) nor difference in patient versus physician ranking of pain intensity was significantly associated with patient-reported visit experience (β for overall agreement, -0.08; 95% confidence interval [CI], -0.45 to 0.30; P=0.69; β for intensity, -0.06; 95% CI, -0.17 to 0.04; P=0.24) or physician-reported visit difficulty (β for overall agreement, 1.92; 95% CI, -2.70 to 6.55; P=0.41; β for intensity, 0.42; 95% CI, -0.87 to 1.71; P=0.53).DiscussionPatients and physicians prioritize substantially different goals for chronic pain management, but there is no evidence that agreement predicts patient experience or physician-reported visit difficulty. Primary care physicians may have adapted to new recommendations that emphasize functional goals and avoidance of long-term opioid therapy, whereas patients continue to focus on reducing pain intensity.

ObjectiveTo investigate associations between ratings of "thin slices" from recorded clinic visits and perceived patient-centeredness; to compare ratings from video recordings (sound and images) versus audio recordings (sound only).MethodsWe analyzed 133 video-recorded primary care visits and patient perceptions of patient-centeredness. Observers rated thirty-second thin slices on variables assessing patient affect, physician affect, and patient-physician rapport. Video and audio ratings were collected independently.ResultsIn multivariable analyses, ratings of physician positive affect (but not patient positive affect) were significantly positively associated with perceived patient-centeredness using both video and audio thin slices. Patient-physician rapport was significantly positively associated with perceived patient-centeredness using audio, but not video thin slices. Ratings from video and audio thin slices were highly correlated and had similar underlying factor structures.ConclusionPhysician (but not patient) positive affect is significantly associated with perceptions of patient-centeredness and can be measured reliably using either video or audio thin slices. Additional studies are needed to determine whether ratings of patient-physician rapport are associated with perceived patient-centeredness.Practice implicationsObserver ratings of physician positive affect have a meaningful positive association with patients' perceptions of patient-centeredness. Patients appear to be highly attuned to physician positive affect during patient-physician interactions.

ObjectiveTo examine encounter-level factors associated with opioid dose increases during patients' first year on opioid therapy for chronic pain.DesignCase-control study analyzing all opioid prescriptions for patients with chronic pain during their first year after opioid initiation. Cases were patients who experienced an overall dose escalation of ≥ 30 mg morphine equivalents over the 1-year period; controls did not experience overall dose escalation. Main measures were encounter type, opioid dose change, documented prescribing rationale, documentation of guideline-concordant opioid-prescribing practices. Two coders reviewed all encounters associated with opioid prescriptions. Analysis of factors associated with dose increases and provider documentation of prescribing rationale was conducted using multiple logistic regression.ResultsThere were 674 encounters coded for 66 patients (22 cases, 44 controls). Fifty-three percent of opioid prescriptions were associated with telephone encounters; 13% were associated with e-mail encounters. No prescribing rationale was documented for 43% of all opioid prescriptions and 25% of dose increases. Likelihood of dose increase and documentation of prescribing rationale did not significantly differ for cases versus controls. Compared with face-to-face encounters, dose increases were significantly less likely for telephone (OR 0.18, 95% CI 0.11-0.28) and e-mail (OR 0.23, 95% CI 0.12-0.47) encounters; documentation of prescribing rationale was significantly more likely for e-mail (OR 5.06, 95% CI 1.87-13.72) and less likely for telephone (OR 0.30, 95% CI 0.18-0.51) encounters.ConclusionMost opioid prescriptions were written without face-to-face encounters. One quarter of dose increases contained no documented prescribing rationale. Documented encounter-level factors were not significantly associated with overall opioid dose escalation.

Context: Health plan disenrollment has been associated with higher mortality in patients with opioid use disorder. Insurance loss and health plan disenrollment might be downstream social consequences of opioid misuse and overdose that may heighten patient mortality risks during a period of heightened need for professional assistance. Objective: To test hypotheses that: 1) overdose events in patients prescribed long-term opioids are associated with subsequent health plan disenrollment; and 2) buprenorphine initiation after overdose would attenuate this association. Study Design: Retrospective cohort study. Setting and Dataset: Data from the Optum Labs Data Warehouse which includes de-identified medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees. The database contains longitudinal health information on patients, representing a mixture of ages, ethnicities, and geographical regions across the United States. Population studied: Adults (aged [greater than or equal to] 18 years) prescribed stable, opioid therapy for a 6-month baseline period ([greater than or equal to] 90% of days covered,, Presenters Joshua Fenton, MD, MPH, Daniel Tancredi, PhD, Alicia Agnoli, MD, MHS, MPH, Stephen Henry, MD, MSc, Iraklis Erik Tseregounis, PhD, Elizabeth Magnan, MD, [...]