The social and behavioral influences (SBI) study: study design and rationale for studying the effects of race and activation on cancer pain management

Examining the effects of physician burnout on pain management for patients with advanced lung cancer

PURPOSE

Physician burnout is generally associated with worse clinical outcomes. The purpose of this study is to examine the effects of physician burnout on the quality of physicians' pain assessment and opioid prescribing for patients with advanced lung cancer. Moreover, we test whether these relationships are moderated by patient-level factors, such as patient race and activation level, that have a demonstrated impact on clinical encounters.

METHODS

We conducted a secondary analysis of data from a multisite randomized field experiment. From 2012 to 2016, 96 primary care physicians and oncologists who treated solid tumors were recruited from hospitals and medical sites in three small metropolitan and rural areas in the USA. Physicians saw two unannounced standardized patients who presented with advanced lung cancer. Standardized patients varied across race (Black or White) and activation level (activated, typical). Visits were audio recorded and transcribed. Pain management was evaluated by the quality of pain assessment and opioid prescribing during these visits.

RESULTS

Mixed-effects linear regression and generalized mixed-effects modeling showed that higher levels of burnout were associated with a greater likelihood of prescribing an opioid and prescribing stronger opioid doses for patients. These effects were not moderated by patient race or activation level.

CONCLUSION

Findings from this work inform our understanding of physician-level factors that impact clinical decision-making in the context of cancer pain management. Specifically, this study identifies the role of physician burnout on the quality of prescribing for patients with advanced lung cancer.

Examining how physician factors influence patient satisfaction during clinical consultations about cancer prognosis and pain

Objective

Patient-physician communication affects cancer patients' satisfaction, health outcomes, and reimbursement for physician services. Our objective is to use machine learning to comprehensively examine the association between patient satisfaction and physician factors in clinical consultations about cancer prognosis and pain.

Methods

We used data from audio-recorded, transcribed communications between physicians and standardized patients (SPs). We analyzed the data using logistic regression (LR) and random forests (RF).

Results

The LR models suggested that lower patient satisfaction was associated with more in-depth prognosis discussion; and higher patient satisfaction was associated with a greater extent of shared decision making, patient being black, and doctor being young. Conversely, the RF models suggested the opposite association with the same set of variables.

Conclusion

Somewhat contradicting results from distinct machine learning models suggested possible confounding factors (hidden variables) in prognosis discussion, shared decision-making, and doctor age, on the modeling of patient satisfaction. Practitioners should not make inferences with one single data-modeling method and enlarge the study cohort to help deal with population heterogeneity.

Innovation

Comparing diverse machine learning models (both parametric and non-parametric types) and carefully applying variable selection methods prior to regression modeling, can enrich the examination of physician factors in characterizing patient-physician communication outcomes.

"Do You Smoke?" Physician-Patient Conversations About Smoking and Lung Cancer

This study examined how physicians initiated and navigated conversations about smoking with patients with lung cancer. While there are numerous health benefits associated with smoking cessation in patients with advanced lung cancer, conversations about smoking cessation are infrequent and often lack tangible cessation support. We conducted a qualitative inductive content analysis on transcripts of conversations (n = 58) recorded during an initial appointment between a physician and a standardized patient (SP). SPs portrayed a 62-year-old male with lung cancer completing an initial visit with a new physician. Qualitative analysis focused on examining how physicians discussed smoking with a new patient. We found that a majority of physicians initiated conversations about smoking, often during the medical history charting process or during conversations about the lung cancer diagnosis. The content of conversations about smoking generally fits within six categories: assesses smoking status, builds smoking history profile, praises smoking cessation, connects smoking behaviors to diagnosis or treatment, provides empathy or understanding, and presents a negative bias about smoking. We found that while a majority of physicians asked patients about smoking, most physicians aimed for these conversations to be short, routine, and medically driven. Conversations about smoking were not tailored to meet the specific needs of patients with lung cancer, which might include additional provision of support for smoking cessation and recognition of smoking-related stigma.

Patient activation reduces effects of implicit bias on doctor-patient interactions

Disparities between Black and White Americans persist in medical treatment and health outcomes. One reason is that physicians sometimes hold implicit racial biases that favor White (over Black) patients. Thus, disrupting the effects of physicians' implicit bias is one route to promoting equitable health outcomes. In the present research, we tested a potential mechanism to short-circuit the effects of doctors' implicit bias: patient activation, i.e., having patients ask questions and advocate for themselves. Specifically, we trained Black and White standardized patients (SPs) to be "activated" or "typical" during appointments with unsuspecting oncologists and primary care physicians in which SPs claimed to have stage IV lung cancer. Supporting the idea that patient activation can promote equitable doctor-patient interactions, results showed that physicians' implicit racial bias (as measured by an implicit association test) predicted racially biased interpersonal treatment among typical SPs (but not among activated SPs) across SP ratings of interaction quality and ratings from independent coders who read the interaction transcripts. This research supports prior work showing that implicit attitudes can undermine interpersonal treatment in medical settings and provides a strategy for ensuring equitable doctor-patient interactions.

Is physician implicit bias associated with differences in care by patient race for metastatic cancer-related pain?

Rationale

Implicit racial bias affects many human interactions including patient-physician encounters. Its impact, however, varies between studies. We assessed the effects of physician implicit, racial bias on their management of cancer-related pain using a randomized field experiment.

Methods

We conducted an analysis of a randomized field experiment between 2012 and 2016 with 96 primary care physicians and oncologists using unannounced, Black and White standardized patients (SPs)who reported uncontrolled bone pain from metastatic lung cancer. We assessed implicit bias using a pain-adaptation of the race Implicit Association Test. We assessed clinical care by reviewing medical records and prescriptions, and we assessed communication from coded transcripts and covert audiotapes of the unannounced standardized patient office visits. We assessed effects of interactions of physicians’ implicit bias and SP race with clinical care and communication outcomes. We conducted a slopes analysis to examine the nature of significant interactions.

Results

As hypothesized, physicians with greater implicit bias provided lower quality care to Black SPs, including fewer renewals for an indicated opioid prescription and less patient-centered pain communication, but similar routine pain assessment. In contrast to our other hypotheses, physician implicit bias did not interact with SP race for prognostic communication or verbal dominance. Analysis of the slopes for the cross-over interactions showed that greater physician bias was manifested by more frequent opioid prescribing and greater discussion of pain for White SPs and slightly less frequent prescribing and pain talk for Black SPs with the opposite effect among physicians with lower implicit bias. Findings are limited by use of an unvalidated, pain-adapted IAT.

Conclusion

Using SP methodology, physicians’ implicit bias was associated with clinically meaningful, racial differences in management of uncontrolled pain related to metastatic lung cancer. There is favorable treatment of White or Black SPs, depending on the level of implicit bias.

Dialysis Regret: Prevalence and Correlates

BACKGROUND AND OBJECTIVES

Although some patients regret the decision to start dialysis, modifiable factors associated with regret have rarely been studied. We aimed to identify factors associated with patients' regret to initiate dialysis.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A 41-item questionnaire was administered to adult patients receiving maintenance dialysis in seven dialysis units located in Cleveland, Ohio, and its suburbs. Of the 450 patients asked to participate in the study, 423 agreed and 397 provided data on decisional regret. We used multivariable logistic regression to identify predictors of regret, which was assessed using a single item, "Do you regret your decision to start dialysis?" We report adjusted odd ratios (ORs) and 95% confidence intervals (95% CIs) for the following candidate predictors: knowledge of CKD, attitudes toward CKD treatment, and preference for end-of-life care.

RESULTS

Eighty-two of 397 respondents (21%) reported decisional regret. There were no significant demographic correlates of regret. Regret was more common when patients reported choosing dialysis to please doctors or family members (OR, 2.34; 95% CI, 1.27 to 4.31; P<0.001). Patients who reported having a prognostic discussion about life expectancy with their doctors (OR, 0.42; 95% CI, 0.18 to 0.98; P=0.03) and those who had completed a living will (OR, 0.48; 95% CI, 0.25 to 0.95; P=0.03) were less likely to report regret with dialysis initiation.

CONCLUSIONS

Dialysis regret was common in this sample. Demographic factors (age, sex, marital status, race, or educational attainment) were not significantly associated with regret, but modifiable care processes were.

PODCAST

This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2020_06_09_CJN13781119.mp3.

Patient and provider characteristics associated with communication about opioids: An observational study

OBJECTIVE

Our objective is to examine the relationship of patient and provider characteristics and communication with chronic non-cancer pain and opioid management in primary care.

METHOD

We conducted an observational study using audio-recorded primary care appointments (up to 3/patient) and self-reported assessments of primary care providers (PCPs) and patients. We coded visit transcripts for 1) opioid and pain management talk and 2) mental health and opioid safety talk.

RESULTS

Eight PCPs and 30 patients had complete data for 78 clinic visits. PCPs and patients engaged in more opioid and pain management talk when patients reported greater pain catastrophizing and PCPs reported higher psychosocial orientation. PCPs and patients engaged in talk about mental health and opioid safety when patients reported greater anxiety, higher working alliance with their PCP, and when PCPs reported higher burnout. PCPs' negative attitudes about opioids were associated with fewer discussions about mental health and opioid safety.

CONCLUSIONS

Our results should facilitate design of interventions that improve communication and, ultimately, pain outcomes for patients.

PRACTICE IMPLICATIONS

Clinicians can use our results to increase patient engagement in discussions about opioid use and pain management or mental health and safety discussions.

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.