Assessment of the Influence of Demographic and Professional Characteristics on Health Care Providers' Pain Management Decisions Using Virtual Humans

Disparities in health care associated with patients’ gender, race, and age are well documented. Previous studies using virtual human (VH) technology have demonstrated that provider characteristics may play an important role in pain management decisions. However, these studies have largely emphasized group differences. The aims of this study were to examine dentists’ and physicians’ use of VH characteristics when making clinical judgments (i.e., cue use) and to identify provider characteristics associated with the magnitude of the impact of these cues (β-weights). Providers (N=152; 76 physicians, 76 dentists) viewed video vignettes of VH patients varying in gender (male/female), race (white/black), and age (younger/older). Participants rated VH patients’ pain intensity and unpleasantness and then rated their own likelihood of administering non-opioid and opioid analgesics. Compared to physicians, dentists had significantly lower β-weights associated with VH age cues for all ratings (p0.69). These effects varied by provider race and gender. For pain intensity, professional differences were present only among non-white providers. White providers had greater β-weights than non-white providers for pain unpleasantness but only among men. Provider differences regarding the use of VH age cues in non-opioid analgesic administration were present among all providers except non-white males. These findings highlight the interaction of patient and provider factors in driving clinical decision making. Although profession was related to use of VH age cues in pain-related clinical judgments, this relationship was modified by providers’ personal characteristics. Additional research is needed to understand what aspects of professional training or practice may account for differences between physicians and dentists and what forms of continuing education may help to mitigate the disparities

The Influence of Health Care Professional Characteristics on Pain Management Decisions

Objective Evidence suggests that patient characteristics such as sex, race, and age influence the pain management decisions of health care providers. Although this signifies that patient demographics may be important determinants of health care decisions, pain-related care also may be impacted by the personal characteristics of the health care practitioner. However, the extent to which health care provider characteristics affect pain management decisions is unclear, underscoring the need for further research in this area. Methods A total of 154 health care providers (77 physicians, 77 dentists) viewed video vignettes of virtual human (VH) patients varying in sex, race, and age. Practitioners provided computerized ratings of VH patients’ pain intensity and unpleasantness, and also reported their willingness to prescribe non-opioid and opioid analgesics for each patient. Practitioner sex, race, age, and duration of professional experience were included as predictors to determine their impact on pain management decisions. Results When assessing and treating pain, practitioner sex, race, age, and duration of experience were all significantly associated with pain management decisions. Further, the role of these characteristics differed across VH patient sex, race, and age. Conclusions These findings suggest that pain assessment and treatment decisions may be impacted by the health care providers’ demographic characteristics, effects which may contribute to pain management disparities. Future research is warranted to determine whether findings replicate in other health care disciplines and medical conditions, and identify other practitioner characteristics (e.g., culture) that may affect pain management decisions

Racial and Ethnic Differences in Total Knee Arthroplasty in the Veterans Affairs Health Care System, 2001-2013

OBJECTIVE: To examine black-white and Hispanic-white differences in total knee arthroplasty from 2001 to 2013 in a large cohort of patients diagnosed with osteoarthritis (OA) in the Veterans Affairs (VA) health care system. METHODS: Data were from the VA Musculoskeletal Disorders cohort, which includes data from electronic health records of more than 5.4 million veterans with musculoskeletal disorders diagnoses. We included white (non-Hispanic), black (non-Hispanic), and Hispanic (any race) veterans, age ≥50 years, with an OA diagnosis from 2001-2011 (n = 539,841). Veterans were followed from their first OA diagnosis until September 30, 2013. As a proxy for increased clinical severity, analyses were also conducted for a subsample restricted to those who saw an orthopedic or rheumatology specialist (n = 148,844). We used Cox proportional hazards regression to examine racial and ethnic differences in total knee arthroplasty by year of OA diagnosis, adjusting for age, sex, body mass index, physical and mental diagnoses, and pain intensity scores. RESULTS: We identified 12,087 total knee arthroplasty procedures in a sample of 473,170 white, 50,172 black, and 16,499 Hispanic veterans. In adjusted models examining black-white and Hispanic-white differences by year of OA diagnosis, total knee arthroplasty rates were lower for black than for white veterans diagnosed in all but 2 years. There were no Hispanic-white differences regardless of when diagnosis occurred. These patterns held in the specialty clinic subsample. CONCLUSION: Black-white differences in total knee arthroplasty appear to be persistent in the VA, even after controlling for potential clinical confounders

Treatment of a Large Cohort of Veterans Experiencing Musculoskeletal Disorders with Spinal Cord Stimulation in the Veterans Health Administration: Veteran Characteristics and Outcomes

Objective Spinal cord stimulator (SCS) implantation is used to treat chronic pain, including painful musculoskeletal disorders (MSDs). This study examined the characteristics and outcomes of veterans receiving SCSs in Veterans Health Administration (VHA) facilities. Methods The sample was drawn from the MSD Cohort and limited to three MSDs with the highest number of implants (N=815,475). There were 1490 veterans with these conditions who received SCS implants from 2000 to 2012, of which 95% (n=1414) had pain intensity numeric rating scale (NRS) data both pre- and post-implant. Results Veterans who were 35–44 years old, White, and married reported higher pain NRS ratings, had comorbid inclusion diagnoses, had no medical comorbidities, had a BMI 25–29.9, or had a depressive disorder diagnosis were more likely to receive an SCS. Veterans 55+ years old or with an alcohol or substance use disorder were less likely to receive an SCS. Over 90% of those receiving an SCS were prescribed opioids in the year prior to implant. Veterans who had a presurgical pain score ≥4 had a clinically meaningful decrease in their pain score in the year following their 90-day recovery period (Day 91–456) greater than expected by chance alone. Similarly, there was a significant decrease in the percent of veterans receiving opioid therapy (92.4% vs 86.6%, p<0.0001) and a significant overall decrease in opioid dose [morphine equivalent dose per day (MEDD) =26.48 vs MEDD=22.59, p<0.0003]. Conclusion Results offer evidence of benefit for some veterans with the examined conditions. Given known risks of opioid therapy, the reduction is an important potential benefit of SCS implants

The Relationship Between Body Mass Index and Pain Intensity Among Veterans with Musculoskeletal Disorders: Findings from the MSD Cohort Study

Objective: To examine the relationship between body mass index (BMI) and pain intensity among veterans with musculoskeletal disorder diagnoses (MSDs; nontraumatic joint disorder; osteoarthritis; low back, back, and neck pain). Setting: Administrative and electronic health record data from the Veterans Health Administration (VHA). Subjects: A national cohort of US military veterans with MSDs in VHA care during 2001-2012 (N = 1,759,338). Methods: These cross-sectional data were analyzed using hurdle negative binomial models of pain intensity as a function of BMI, adjusted for comorbidities and demographics. Results: The sample had a mean age of 59.4, 95% were male, 77% were white/Non-Hispanic, 79% were overweight or obese, and 42% reported no pain at index MSD diagnosis. Overall, there was a J-shaped relationship between BMI and pain (nadir = 27 kg/m2), with the severely obese (BMI ≥ 40 kg/m2) being most likely to report any pain (OR vs normal weight = 1.23, 95% confidence interval = 1.21-1.26). The association between BMI and pain varied by MSD, with a stronger relationship in the osteoarthritis group and a less pronounced relationship in the back and low back pain groups. Conclusions: There was a high prevalence of overweight/obesity among veterans with MSD. High levels of BMI (>27 kg/m2) were associated with increased odds of pain, most markedly among veterans with osteoarthritis

Should UI Eligibility Be Expanded to Low-Earning Workers? Evidence on Employment, Transfer Receipt, and Income from Administrative Data

Recent efforts to expand unemployment insurance (UI) eligibility are expected to increase low-earning workers’ access to UI. Although the expansion’s aim is to smooth the income and consumption of previously ineligible workers, it is possible that UI benefits simply displace other sources of income. Standard economic models predict that UI delays reemployment, thereby reducing wage income. Additionally, low-earning workers are often eligible for benefits from means-tested programs, which may decrease with UI benefits. In this paper, we estimate the impact of UI eligibility on employment, means-tested program participation, and income after job loss using a unique individual-level administrative data set from the state of Michigan. To identify a causal effect, we implement a fuzzy regression discontinuity design around the minimum earnings threshold for UI eligibility. Our main finding is that while UI eligibility increases jobless durations by up to 25 percent and temporarily lowers receipt of cash assistance (TANF) by 63 percent, the net impact on total income is still positive and large. In the quarter immediately following job loss, UI-eligible workers have 46-61 percent higher incomes than ineligibles