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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.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.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.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.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.

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.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.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.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.

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.

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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06555-x.

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.

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.

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.

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.

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.

Background Prescription 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. Objective To examine perceived PDMP effectiveness among obstetrician-gynecologists (OB/GYNs) compared to primary care physicians (PCPs). Methods Independent 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. Results In 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”. Conclusions These 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.

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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-019-05303-0) contains supplementary material, which is available to authorized users.

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.

OBJECTIVE: To compare effectiveness of a narrative-based educational video versus an informational pamphlet for increasing patients’ self-efficacy and intention to taper their opioid use. METHODS: Five 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. RESULTS: Participants’ 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). CONCLUSION: A narrative-based video about opioid tapering enhanced patients’ perceptions of the effectiveness of tapering and their tapering self-efficacy. PRACTICE IMPLICATIONS: Narrative-based videos may be effective for changing patient attitudes about opioid tapering.

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.

OBJECTIVES: Opioid 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. METHODS: Combined 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. RESULTS: From 2012 to 2018, the rate of individuals treated with buprenorphine in Medicaid increased by 657% (1.39 to 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 to 12.7 non-Medicaid individuals per 10,000) with most increases occurring prior to 2014. CONCLUSIONS: California 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.

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.&nbsp

Background and aims Prescription 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. Methods A 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. Results We 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. Conclusions Since 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.

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.

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.

Author(s): Holmes-Rovner, Margaret; Srikanth, Akshay; Henry, Stephen G; Langford, Aisha; Rovner, David R; Fagerlin, Angela | Abstract: 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 (Pn=n.027) and more time in the encounter (Pn=n.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.

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 overdose deaths. METHODS: We measured associations between adoption of any PDMP and changes in fatal prescription opioid overdoses in 2002-2016 across 3,109 counties in 49 states. 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 three time intervals that broadly represent the evolution of PDMPs (2002-2004, 2005-2009, 2010-2016). We modeled overdoses using Bayesian space-time models. RESULTS: Adoption of electronic PDMP access was associated with 9% lower rates of fatal prescription opioid 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, CI: 0.82-0.90) and other synthetic opioids (RR=0.82, CI: 0.77-0.86). Compared to 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 prescription opioid deaths overall while proactive PDMPs alone were associated with fewer deaths related to natural/semi-synthetic opioids and methadone, the specific targets of these programs.

BACKGROUND: In response to adverse outcomes from prescription opioids, the Centers for Disease Control and Prevention (CDC) released the Guideline for Prescribing Opioids for Chronic Pain in March 2016. OBJECTIVE: To test the hypothesis that the CDC guideline release corresponded to declines in specific opioid prescribing practices. DESIGN: Interrupted time series analysis of monthly prescribing measures from the IQVIA transactional data warehouse and Real-World Data Longitudinal Prescriptions population-level estimates based on retail pharmacy data. Population size was determined by U.S. Census monthly estimates. SETTING: United States, 2012 to 2017. PATIENTS: Persons prescribed opioid analgesics. MEASUREMENTS: Outcomes included opioid dosage, days supplied, overlapping benzodiazepine prescriptions, and the overall rate of prescribing. RESULTS: The rate of high-dosage prescriptions (≥90 morphine equivalent milligrams per day) was 683 per 100 000 persons in January 2012 and declined by 3.56 (95% CI, −3.79 to −3.32) per month before March 2016 and by 8.00 (CI, −8.69 to −7.31) afterward. Likewise, the percentage of patients with overlapping opioid and benzodiazepine prescriptions was 21.04% in January 2012 and declined by 0.02% (CI, −0.04% to −0.01%) per month before the CDC guideline release and by 0.08% (CI, −0.08% to −0.07%) per month afterward. The overall opioid prescribing rate was 6577 per 100 000 persons in January 2012 and declined by 23.48 (CI, −26.18 to −20.78) each month before the guideline release and by 56.74 (CI, −65.96 to −47.53) per month afterward. LIMITATION: No control population; inability to determine the appropriateness of opioid prescribing. CONCLUSION: Several opioid prescribing practices were decreasing before the CDC guideline, but the time of its release was associated with a greater decline. Guidelines may be effective in changing prescribing practices. PRIMARY FUNDING SOURCE: CDC.

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.

Background : In 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. Methods : Using 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. Results : Proactive 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). Conclusions : California’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.

Objective. To describe the development and initial application of the Chronic Pain Coding System. Design. Secondary analysis of data from a randomized clinical trial. Setting. Six primary care clinics in northern California. Subjects. Forty-five primary care visits involving 33 clinicians and 45 patients on opioids for chronic noncancer pain. Methods. The authors developed a structured coding system to accurately and objectively characterize discussions about pain and opioids. Two coders applied the final system to visit transcripts. Intercoder agreement for major coding categories was moderate to substantial (kappa = 0.5–0.7). Mixed effects regression was used to test six hypotheses to assess preliminary construct validity. Results. Greater baseline pain interference was associated with longer pain discussions ( P = 0.007) and more patient requests for clinician action ( P = 0.02) but not more frequent negative patient evaluations of pain ( P = 0.15). Greater clinician-reported visit difficulty was associated with more frequent disagreements with clinician recommendations ( P = 0.003) and longer discussions of opioid risks ( P = 0.049) but not more frequent requests for clinician action ( P = 0.11). Rates of agreement versus disagreement with patient requests and clinician recommendations were similar for opioid-related and non-opioid–related utterances. Conclusions. This coding system appears to be a reliable and valid tool for characterizing patient-clinician communication about opioids and chronic pain during clinic visits. Objective data on how patients and clinicians discuss chronic pain and opioids are necessary to identify communication patterns and strategies for improving the quality and productivity of discussions about chronic pain that may lead to more effective pain management and reduce inappropriate opioid prescribing.

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

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.

Objective To 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). Methods We 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. Results In 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. Conclusion Physician (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 implications Observer 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.

Background We know little about patient–physician communication during visits to discuss diagnosis and treatment of prostate cancer. Objective To examine the overall visit structure and how patients and physicians transition between communication activities during visits in which patients received new prostate cancer diagnoses. Participants Forty veterans and 18 urologists at one VA medical centre. Methods We coded 40 transcripts to identify major communication activities during visits and used empiric discourse analysis to analyse transitions between activities. Results We identified five communication activities that occurred in the following typical sequence: ‘diagnosis delivery’, ‘risk classification’, ‘options talk’, ‘decision talk’ and ‘next steps’. The first two activities were typically brief and involved minimal patient participation. Options talk was typically the longest activity; physicians explicitly announced the beginning of options talk and framed it as their professional responsibility. Some patients were unsure of the purpose of visit and/or who should make treatment decisions. Conclusion Visits to deliver the diagnosis of early stage prostate cancer follow a regular sequence of communication activities. Physicians focus on discussing treatment options and devote comparatively little time and attention to discussing the new cancer diagnosis. Towards the goal of promoting patient-centred communication, physicians should consider eliciting patient reactions after diagnosis delivery and explaining the decision-making process before describing treatment options.

Patients and physicians report that discussions about pain are frequently frustrating and unproductive. However, the relationship between discussions about pain and patient-physician communication is poorly understood. We analyzed 133 video-recorded visits and patient self-report data collected at a clinic providing primary care to a low-income, black patient population. We used "thin slice" methods to rate two or three 30-second video segments from each visit on variables related to patient and physician affect (ie, displayed emotion) and patient-physician rapport. Discussions about pain were associated with a .32 increase in patient unease (P .001) and a .21 increase in patient positive engagement (P = .004; standardized coefficients) compared to discussions about other topics during the same visit. Discussions about pain were not significantly associated with patient-physician rapport, physician unease, or physician positive engagement. Patient pain severity was significantly associated with greater physician and patient unease (P = .01), but not with other variables. Findings suggest that primary care patients, but not their physicians, display significantly greater emotional intensity during discussions about pain compared to discussions about other topics.This study used direct observation of video-recorded primary care visits to show that discussions about pain are associated with heightened displays of both positive and negative patient emotions. These displays of emotion could potentially influence pain-related outcomes.

We know little about how much time low-income patients and physicians spend discussing pain during primary care visits.To measure the frequency and duration of pain-related discussions at a primary care clinic serving mostly low-income black patients; to investigate variables associated with these discussions.We measured the frequency and duration of pain-related discussions using video-recorded primary care visits; we used multiple regression to evaluate associations between discussions and patient self-report variables.A total of 133 patients presenting to a primary care clinic for any reason; 17 family medicine residents.Independent variables were pain severity, health status, physical function, chief complaint, and whether the patient and physician had met previously. Dependent variables were presence of pain-related discussions and percent of total visit time spent discussing pain.Sixty-nine percent of visits included pain-related discussions with a mean duration of 5.9 min (34% of total visit time). Increasing pain severity [OR 1.69, 95% CI (1.18, 2.41)] and pain-related chief complaints [OR 4.10, 95% CI (1.39, 12.12)] were positively associated with the probability of discussing pain. When patients discussed pain, they spent 4.5% more [95% CI (0.60, 8.37)] total visit time discussing pain for every one-point increase in pain severity. Better physical function was negatively associated with the probability of discussing pain [OR 0.65, 95% CI (0.48, 0.86)], but positively associated with the percent of total visit time spent discussing pain [3% increase; 95% CI (0.32, 5.75)] for every one-point increase in physical function). Patients and physicians who had met previously spent 11% less [95% CI (-21.65, -0.55)] total visit time discussing pain. Pain severity was positively associated with time spent discussing pain only when patients and physicians had not met previously.Pain-related discussions comprise a substantial proportion of time during primary care visits. Future research should evaluate the relationship between time spent discussing pain and the quality of primary care pain management.

Rationale and objectives Theory suggests that tacit clues inform clinical judgements, but the prevalence and role of tacit clues during clinical interactions is unknown. This study explored whether doctors and patients identify information likely to be tacit clues or judgements based on tacit clues during health maintenance examinations. Methods Qualitative analysis of video elicitation interview transcripts involving 18 community-based primary care doctors and 36 patients. Outcomes were description and analysis of tacit clues and judgements based on tacit clues mentioned by participants. Results A total of 57 references to tacit clues and 53 references to judgements based on tacit clues were identified from patient and doctor transcripts. Non-verbal behaviours comprised the most common category of tacit clues (53% of doctor comments; 42% of patient comments). Patients mostly discussed judgements based on tacit clues that related to the doctor–patient relationship. Doctors discussed actively using non-verbal behaviours to provide patients with tacit clues about the doctor–patient relationship. They also mentioned tacit clues that informed medical judgements and decision making. Gestalt judgements based on tacit clues were common (33% of doctor comments). Several participants identified instances in which they had difficulty articulating their rationale for specific judgements. Doctors varied widely in how frequently they mentioned tacit clues. Conclusion During video elicitation interviews, patients and doctors identified tacit clues and judgements based on these clues as playing a role during health maintenance examinations. Future research should further elucidate the role of tacit clues in medical judgements and doctor–patient relationships.

Most clinicians take for granted a simple, reductionist understanding of medical knowledge that is at odds with how they actually practice medicine; routine medical decisions incorporate more complicated kinds of information than most standard accounts of medical reasoning suggest. A better understanding of the structure and function of knowledge in medicine can lead to practical improvements in clinical medicine. This understanding requires some familiarity with epistemology, the study of knowledge and its structure, in medicine. Michael Polanyi's theory of tacit knowing is advanced as the basis for developing a more accurate understanding of medical knowledge. Tacit knowing, which explores the taken-for-granted background knowledge that underlies all human knowing, is explained in detail with a focus on its relevance for clinical medicine. The implications of recognizing tacit knowing in medicine and medical decisions are discussed. These include the ability to explain the importance of the clinical encounter in medical practice, mechanisms for analysing patient and doctor as persons, and the need for humility given the uncertainty that the tacit dimension injects into all medical decisions. This more robust medical epistemology allows clinicians to better articulate the nature and importance of patient-centred care, to avoid pitfalls inherent in reductionist approaches to medical knowledge, and to think more clearly about the relationships between medicine and health care at the individual and population levels.

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient–clinician interactions. Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P = 0.003) and having worked longer at their current practice (P = 0.02) were associated with increased likelihood of consent. For patients, white race (P = 0.002) and diabetes (P = 0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any of the 6 dependent variables examined. Practice implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting.

Background"Difficult visits" are common in primary care and may contribute to primary care provider (PCP) career dissatisfaction and burnout. Patient requests occur in approximately half of primary care visits and may be a source of clinician-patient miscommunication or conflict, contributing to perceived visit difficulty.ObjectiveWe aimed to determine associations between types of patient requests and PCP-perceived visit difficulty.DesignThis was an observational study, nested in a multicenter randomized trial of depression engagement interventions.SubjectsWe included 824 patient visits within 135 PCP practices in Northern California occurring from June 2010 to March 2012.Main measuresPCP-perceived visit difficulty was quantified using a three-item scale (relative visit difficulty, amount of effort required, and amount of time required; Cronbach's α = 0.81). Using linear regression, the difficulty scale (score range 0-2 from least to most difficult) was modeled as a function of: patient requests for diagnostics tests, pain medications, and specialist referrals; PCP perception of likely depression or likely substance abuse; patient sociodemographics, comorbidity, depression; PCP characteristics and practice setting.ResultsPatients requested diagnostic tests, pain medications, and specialist referrals in 37.2, 20.0 and 30.0% of visits, respectively. After adjustment for patient medical and psychiatric complexity, perceived difficulty was significantly higher when patients requested diagnostic tests [parameter estimate (PE) 0.11, (95% CI: 0.03, 0.20)] but not when patients requested pain medications [PE -0.04 (95% CI: -0.15, 0.08)] or referrals [PE 0.04 (95% CI: -0.07, 0.25)].ConclusionsPCP-perceived visit difficulty is associated with patient requests for diagnostic tests, but not requests for pain medications or specialist referrals. In this era of "choosing wisely," PCPs may be challenged to respond to diagnostic test requests in an evidence-based manner, while maintaining the provider-patient relationship and PCP career satisfaction.

The increasing amount of data produced by large-scale biological experiments has highlighted the inadequacies of traditional scientific data management methods such as laboratory notebooks. Databases designed to store biological information are becoming increasingly common, but there is little guidance in the literature about the best practices of biological database design. This paper suggests best practices, and provides examples for the implementation of these practices.

ObjectiveTo advance research on depression communication and treatment by comparing assessments of communication about depression from patient report, clinician report, and chart review to assessments from transcripts.DataOne hundred sixty-four primary care visits from seven health care systems (2010-2011).Study designPresence or absence of discussion about depressive symptoms, treatment recommendations, and follow-up was measured using patient and clinician postvisit questionnaires, chart review, and coding of audio transcripts. Sensitivity and specificity of indirect measures compared to transcripts were calculated.Principal findingsPatient report was sensitive for mood (83 percent) and sleep (83 percent) but not suicide (55 percent). Patient report was specific for suicide (86 percent) but not for other symptoms (44-75 percent). Clinician report was sensitive for all symptoms (83-98 percent) and specific for sleep, memory, and suicide (80-87 percent), but not for other symptoms (45-48 percent). Chart review was not sensitive for symptoms (50-73 percent), but it was specific for sleep, memory, and suicide (88-96 percent). All indirect measures had low sensitivity for treatment recommendations (patient report: 24-42 percent, clinician report 38-50 percent, chart review 49-67 percent) but high specificity (89-96 percent). For definite follow-up plans, all three indirect measures were sensitive (82-96 percent) but not specific (40-57 percent).ConclusionsClinician report and chart review generally had the most favorable sensitivity and specificity for measuring discussion of depressive symptoms and treatment recommendations, respectively.

Communicating with patients is arguably the most common and important activity in medical practice, but this activity receives relatively little emphasis in graduate medical education. We propose 12 evidence-based communication competencies that program directors can adopt as a framework for teaching and evaluating residents' communication skills. We review supporting evidence for these competencies and argue that communication should be treated like a procedural skill that must be taught and evaluated by observing real resident-patient interactions. We make practical suggestions for implementing these competencies by addressing three critical components of a competency-based approach to communication skills: patient safety, faculty development, and direct observation of residents. This approach to teaching and assessing communication skills provides a rationale for incorporating routine direct observation into graduate medical education programs and also for designing communication skills training that ensures graduating residents develop the skills needed to provide safe, effective patient care.

Objective. To examine encounter-level factors associated with opioid dose increases during patients’ first year on opioid therapy for chronic pain. Design. Case-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. Results. There 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. Conclusion. Most 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.

To conduct a systematic review and meta-analysis of studies reporting associations between patients' and clinicians' nonverbal communication during real clinical interactions and clinically relevant outcomes.We searched 10 electronic databases, reference lists, and expert contacts for English-language studies examining associations between nonverbal communication measured through direct observation and either clinician or patient outcomes in adults. Data were systematically extracted and random effects meta-analyses were performed.26 observational studies met inclusion criteria. Meta-analysis was performed for patient satisfaction, which was assessed in 65% of studies. Mental and physical health status were evaluated in 23% and 19% of included studies, respectively. Both clinician warmth and clinician listening were associated with greater patient satisfaction (p0.001 both). Physician negativity was not related to patient satisfaction (p=0.505), but greater nurse negativity was associated with less patient satisfaction (p0.001). Substantial differences in study design and nonverbal measures existed across studies.Greater clinician warmth, less nurse negativity, and greater clinician listening were associated with greater patient satisfaction. Additional studies are needed to evaluate the impact of nonverbal communication on patients' mental and physical health.Communication-based interventions that target clinician warmth and listening and nurse negativity may lead to greater patient satisfaction.

Theory suggests that tacit clues inform clinical judgements, but the prevalence and role of tacit clues during clinical interactions is unknown. This study explored whether doctors and patients identify information likely to be tacit clues or judgements based on tacit clues during health maintenance examinations.Qualitative analysis of video elicitation interview transcripts involving 18 community-based primary care doctors and 36 patients. Outcomes were description and analysis of tacit clues and judgements based on tacit clues mentioned by participants.A total of 57 references to tacit clues and 53 references to judgements based on tacit clues were identified from patient and doctor transcripts. Non-verbal behaviours comprised the most common category of tacit clues (53% of doctor comments; 42% of patient comments). Patients mostly discussed judgements based on tacit clues that related to the doctor-patient relationship. Doctors discussed actively using non-verbal behaviours to provide patients with tacit clues about the doctor-patient relationship. They also mentioned tacit clues that informed medical judgements and decision making. Gestalt judgements based on tacit clues were common (33% of doctor comments). Several participants identified instances in which they had difficulty articulating their rationale for specific judgements. Doctors varied widely in how frequently they mentioned tacit clues.During video elicitation interviews, patients and doctors identified tacit clues and judgements based on these clues as playing a role during health maintenance examinations. Future research should further elucidate the role of tacit clues in medical judgements and doctor-patient relationships.

Most clinicians take for granted a simple, reductionist understanding of medical knowledge that is at odds with how they actually practice medicine; routine medical decisions incorporate more complicated kinds of information than most standard accounts of medical reasoning suggest. A better understanding of the structure and function of knowledge in medicine can lead to practical improvements in clinical medicine. This understanding requires some familiarity with epistemology, the study of knowledge and its structure, in medicine. Michael Polanyi's theory of tacit knowing is advanced as the basis for developing a more accurate understanding of medical knowledge. Tacit knowing, which explores the taken-for-granted background knowledge that underlies all human knowing, is explained in detail with a focus on its relevance for clinical medicine. The implications of recognizing tacit knowing in medicine and medical decisions are discussed. These include the ability to explain the importance of the clinical encounter in medical practice, mechanisms for analysing patient and doctor as persons, and the need for humility given the uncertainty that the tacit dimension injects into all medical decisions. This more robust medical epistemology allows clinicians to better articulate the nature and importance of patient-centred care, to avoid pitfalls inherent in reductionist approaches to medical knowledge, and to think more clearly about the relationships between medicine and health care at the individual and population levels.

The evidence-based medicine movement has remained both well known and controversial since its inception. The authors reframe the evidence-based medicine debate by pointing out an underappreciated epistemological deficiency: evidence-based medicine as currently conceptualized cannot accommodate concepts that resist quantitative analysis and therefore cannot logically differentiate human beings from complex machines. The authors use Michael Polanyi's philosophy of tacit knowing (which refers to the taken-for-granted knowledge at the periphery of attention that allows persons to understand the world and discern meaning in it) as a starting point for rectifying this deficiency and for working towards an improved, person-centered epistemology of medical practice. The authors demonstrate that not only evidence-based medicine but also most traditional theories of medical practice need a concept such as tacit knowing to account for the kinds of knowledge human beings actually use. Polanyi's philosophy of tacit knowing is defined and briefly explained. A medical epistemology that can account for the tacit dimension of human knowledge and recognize physicians and patients as persons requires a revised conception of medical uncertainty and a recognition that clinician-patient interactions are central to medicine. The authors discuss practical implications of tacit knowing for medical practice, education, research, and health care policy and suggest ways for moving beyond evidence-based medicine towards a comprehensive epistemology of medical practice.