Impact of 30-day prescribed opioid dose trajectory on fatal overdose risk: A population-based, statewide cohort study.

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.

Comparison of record linkage software for deduplicating patient identities in California's Prescription Drug Monitoring Program.

BACKGROUND: To help prevent overdose deaths involving prescription drugs, accurate linkage of prescription drug monitoring program (PDMP) records for individual patients is essential. OBJECTIVES: To compare the accuracy of the linkage program used by California's PDMP against various record linkage programs with respect to accuracy in deduplicating patient identities in the PDMP, with implications for identifying high-risk opioid use and outlier behaviors. RESEARCH DESIGN: We evaluated California's program, Link Plus, LinkSolv, and The Link King on 557 861 PDMP identity records with addresses in two 3-digit zip code areas for patients who filled a controlled substance prescription in 2013. Manual review was performed on a stratified sample of 720 paired records identified as matches by at least one program. MEASURES: We estimated sensitivity and positive predictive value, and computed PDMP patient alerts for the patient entities identified by each program. RESULTS: Sensitivity was 95% for LinkSolv and The Link King, 84% for Link Plus, and 73% for California's program; positive predictive value was ≥93% for all programs. The number of patient entities prompting a PDMP alert was similar among the programs for all alerts except multiple provider episodes (obtaining prescriptions from ≥6 prescribers or ≥6 pharmacies in the last 6 months), which were 10.9%, 26.6%, and 16.9% greater using The Link King, Link Plus, and LinkSolv, respectively, compared to California's program. CONCLUSIONS: PDMPs should assess the accuracy of record linkage algorithms and the impacts of these algorithms on patient safety alerts and develop national best practices for PDMP record linkage.

Communicative Practices Clinicians Use to Correct Patient Misconceptions in Primary Care Visits.

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.

Visit Linearity in Primary Care Visits for Patients with Chronic Pain on Long-term Opioid Therapy.

BACKGROUND: Physicians and patients report frustration after primary care visits for chronic pain. The need to shift between multiple clinical topics to address competing demands during visits may contribute to this frustration. OBJECTIVE: This study creates a novel measure, "visit linearity," to assess visit organization and examines whether visits that require less shifting back and forth between topics are associated with better patient and physician visit experiences. It also explores whether visit linearity differs depending on the following: (1) whether or not pain is a major topic of the visit and (2) whether or not pain is the first topic raised. DESIGN: This study analyzed 41 video-recorded visits using inductive, qualitative analysis informed by conversation analysis. We used linear regression to evaluate associations between visit organization and post-visit measures of participant experience. PARTICIPANTS: Patients were established adult patients planning to discuss pain management during routine primary care. Physicians were internal or family medicine residents. MAIN MEASURES: Visit linearity, total topics, return topics, topic shifts, time per topic, visit duration, pain main topic, pain first topic, patient experience, and physician difficulty. KEY RESULTS: Visits had a mean of 8.1 total topics (standard deviation (SD)=3.46), 14.5 topic shifts (SD=6.28), and 1.9 topic shifts per topic (SD=0.62). Less linear visits (higher topic shifts to topic ratio) were associated with greater physician visit difficulty (ß=7.28, p<0.001) and worse patient experience (ß= -0.62, p=0.03). Visit linearity was not significantly impacted by pain as a major or first topic raised. CONCLUSIONS: In primary care visits for patients with chronic pain taking opioids, more linear visits were associated with better physician and patient experience. Frequent topic shifts may be disruptive. If confirmed in future research, this finding implies that reducing shifts between topics could help decrease mutual frustration related to discussions about pain.

The impact of California wildfires on patient access to prescription opioids.

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 patient's 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.

A Risk Prediction Model for Long-term Prescription Opioid Use.

BACKGROUND: Tools are needed to aid clinicians in estimating their patients' risk of transitioning to long-term opioid use and to inform prescribing decisions. OBJECTIVE: The 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 DESIGN: This was a statewide population-based prognostic study. SUBJECTS: Opioid-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). MEASURES: A 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. RESULTS: Development 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. CONCLUSIONS: A 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.

Using Prescription Drug Monitoring Program Data to Assess Likelihood of Incident Long-Term Opioid Use: a Statewide Cohort Study.

BACKGROUND: Limiting 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. OBJECTIVE: To 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. DESIGN: Statewide 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 MEASURES: Multiple 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 RESULTS: Among 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. CONCLUSIONS: Data 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.

Impacts of prescription drug monitoring program policy changes and county opioid safety coalitions on prescribing and overdose outcomes in California, 2015-2018.

In 2015, California received funding to implement the Prescription Drug Overdose Prevention Initiative, a 4-year program to reduce deaths involving prescription opioids by 1) leveraging improvements to California's prescription drug monitoring program (PDMP) (i.e., mandatory PDMP registration for prescribers and pharmacists), and 2) supporting county opioid safety coalitions. We used statewide data from 2011 to 2018 to evaluate the Initiative's impact on opioid prescribing and overdose rates. Prescribing data were obtained from California's PDMP; fatal and non-fatal overdose data were obtained from the California Department of Public Health. Outcomes were monthly opioid prescribing rates and opioid overdose rates, modeled using generalized linear mixed models. Exposures were mandatory PDMP registration, presence of county coalitions, and Initiative support for county coalitions. Mandatory PDMP registration was associated with a 25% decrease (95%CI, 0.71-0.79) in opioid prescribing rates after 24 months. Having a county coalition was associated with a 2% decrease (95%CI, 0.96-0.99) in the opioid prescribing rate; receiving Initiative support was associated with an additional 2% decrease (95%CI, 0.97-0.98). Mandatory PDMP registration and county coalitions were associated with a 35% decrease (95%CI, 0.43-0.97) and a 21% decrease (95% CI, 0.70-0.90), respectively in prescription opioid overdose deaths. Both interventions were also associated with significantly fewer deaths involving any opioid but had no significant association with non-fatal overdose rates. Findings add to the knowledge available to guide policy to prevent high-risk prescribing and opioid overdoses. While further study is needed, coalitions and mandatory PDMP registration may be important components in such efforts.

Longitudinal Dose Trajectory Among Patients Tapering Long-Term Opioids.

OBJECTIVE: To evaluate the dose trajectory of new opioid tapers and estimate the percentage of patients with sustained tapers at long-term follow-up. DESIGN: Retrospective cohort study. SETTING: Data from the OptumLabs Data Warehouse® which includes de-identified medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees, representing a diverse mixture of ages, ethnicities, and geographical regions across the United States. SUBJECTS: Patients prescribed stable, higher-dose opioids for ≥12 months from 2008 to 2018. METHODS: Tapering was defined as ≥15% relative reduction in average MME/day during any of six overlapping 60-day periods in the initial 7 months of follow-up after the period of stable baseline dosing. Average monthly dose was ascertained during consecutive 60-day periods up to 16 months of follow-up. Linear regression estimated the geometric mean relative dose by tapering status and follow-up duration. Poisson regression estimated the percentage of tapered patients with sustained dose reductions at follow-up and patient-level predictors of failing to sustain tapers. RESULTS: The sample included 113,618 patients with 203,920 periods of stable baseline dosing (mean follow-up = 13.7 months). Tapering was initiated during 37,170 follow-up periods (18.2%). After taper initiation, patients had a substantial initial mean dose reduction (geometric mean relative dose .73 [95% CI: .72-.74]) that was sustained through 16 months of follow-up; at which point, 69.8% (95% CI: 69.1%-70.4%) of patients who initiated tapers had a relative dose reduction ≥15%, and 14.2% (95% CI: 13.7%-14.7%) had discontinued opioids. Failure to sustain tapers was significantly less likely among patients with overdose events during follow-up (adjusted incidence rate ratio [aIRR]: .56 [95% CI: .48-.67]) and during more recent years (aIRR: .93 per year after 2008 [95% CI: .92-.94]). CONCLUSIONS: In an insured and Medicare Advantage population, over two-thirds of patients who initiated opioid dose tapering sustained long-term dose reductions, and the likelihood of sustaining tapers increased substantially from 2008 to 2018.

Responding to the Opioid Epidemic: Educational Competencies for Pain and Substance Use Disorder from the Medical Schools of the University of California.

OBJECTIVE: The 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). METHODS: The 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. RESULTS: The 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. CONCLUSIONS: The 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.

The story vs the storyteller: Factors associated with the effectiveness of brief video-recorded patient stories for promoting opioid tapering.

BACKGROUND: Narrative 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. OBJECTIVE: To examine the relative impacts of patient engagement, age concordance and gender concordance on perceived persuasiveness of video-recorded narrative clips about opioid tapering. METHODS: Patient 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 (<60 vs ≥60). Covariates were rater beliefs about opioids and opioid tapering, clip duration and clip theme. Mixed-effects models accounted for raters viewing multiple clips and clips nested within storytellers. RESULTS: In multivariable models, higher rater engagement with the clip was associated with higher perceived persuasiveness (coefficient = 0.46, 95% CI 0.39-0.53, P < .001). Neither age concordance nor gender concordance significantly predicted perceived persuasiveness. The theme Problems with opioids also predicted perceived persuasiveness. CONCLUSION: Highly engaging, clinically relevant stories are likely persuasive to patients regardless of the match between patient and storyteller age and gender. When using patient stories in tools to promote health behaviour change, stories that are clinically relevant and engaging are likely to be persuasive regardless of storytellers' demographics. PATIENT OR PUBLIC CONTRIBUTION: Patients were involved as storytellers (in each clip) and assessed the key study variables.

Agenda setting and visit openings in primary care visits involving patients taking opioids for chronic pain.

BACKGROUND: Agenda 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. METHODS: This 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. RESULTS: We 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). CONCLUSIONS: In 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.

Measuring Relationships Between Proactive Reporting State-level Prescription Drug Monitoring Programs and County-level Fatal Prescription Opioid Overdoses.

BACKGROUND: Prescription 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. METHODS: We 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. RESULTS: Adoption 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]). CONCLUSIONS: State 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.

"It Sometimes Doesn't Even Work": Patient Opioid Assessments as Clues to Therapeutic Flexibility in Primary Care.

BACKGROUND: Physicians' fear of difficult patient interactions is an important barrier to discontinuing long-term opioid therapy. OBJECTIVE: To 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. PARTICIPANTS: Eighty-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%). CONCLUSIONS: Patient 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.

Effect of Mobile Device-Assisted N-of-1 Trial Participation on Analgesic Prescribing for Chronic Pain: Randomized Controlled Trial.

OBJECTIVES: Opioids 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. METHODS: We 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. RESULTS: There 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). DISCUSSION: These 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 REGISTRATION: ClinicalTrials.gov Identifier: NCT02116621.

The Influence of Patient Race and Activation on Pain Management in Advanced Lung Cancer: a Randomized Field Experiment.

BACKGROUND: Pain management racial disparities exist, yet it is unclear whether disparities exist in pain management in advanced cancer. OBJECTIVE: To examine the effect of race on physicians' pain assessment and treatment in advanced lung cancer and the moderating effect of patient activation. DESIGN: Randomized 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. PARTICIPANTS: Ninety-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 MEASURES: Opioids prescribed (or not), total daily opioid doses (in oral morphine equivalents), guideline-concordant pain management, and pain assessment. KEY RESULTS: SPs 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). CONCLUSIONS: Neither 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 REGISTRATION: NCT01501006.

Association Between Prescription Drug Monitoring Programs and Nonfatal and Fatal Drug Overdoses: A Systematic Review.

Background: Prescription 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. Purpose: To 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 Sources: Eligible 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 Selection: Observational studies (published in English) from U.S. states that examined an association between PDMP implementation and nonfatal or fatal overdoses. Data Extraction: 2 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 Synthesis: Of 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. Limitation: Few studies, high ROB, and heterogeneous analytic methods and outcome measurement. Conclusion: Evidence 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 Source: National Institute on Drug Abuse and Bureau of Justice Assistance.

Prescription Drug Monitoring Program: Registration and Use by Prescribers and Pharmacists Before and After Legal Mandatory Registration, California, 2010-2017.

OBJECTIVES: To estimate the effect of California's prescription drug monitoring program's (PDMP) registration mandate on use of the PDMP. METHODS: We 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). RESULTS: Mandatory 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. CONCLUSIONS: Mandatory 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.

Patient-Clinician Communication About Pain: A Conceptual Model and Narrative Review.

Objective: Productive 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. Methods: A 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. Results: The 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. Conclusions: Published 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.

Decision aid use during post-biopsy consultations for localized prostate cancer.

BACKGROUND: Decision 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. OBJECTIVE: To characterize the content and communicative function of high-quality DAs during diagnostic clinic visits for prostate cancer. PARTICIPANTS: 252 men newly diagnosed with localized prostate cancer who had received a DA, 45 treating physicians at 4 US Veterans Administration urology clinics. METHODS: Qualitative 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. RESULTS: Booklet 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. CONCLUSIONS: Results 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.