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Association of Physician Peer Influence With Subsequent Physician Adoption and Use of Bevacizumab.

ABSTRACT: Importance:Understanding adoption of new cancer therapies may help identify opportunities to increase use for high-value indications. Objective:To determine whether use of bevacizumab in 2005 to 2006 by oncologists' peers was associated with greater bevacizumab use among oncologists in 2007 to 2010. Design, Setting, and Participants:This cohort study of physicians and their patients took place in 51 randomly selected hospital referral regions in the United States. Participants were 44 012 fee-for-service Medicare beneficiaries aged 65 years or older with cancers of the colorectum, lung, breast, kidney, brain, or ovary treated by 3261 oncologists in 2005 to 2010 and assigned to one of 252 communities. Data were analyzed in 2017 to 2018. Exposures:Among patients treated with chemotherapy during 2007 to 2010 by an oncologist who had not treated patients with bevacizumab in 2005 to 2006, models assessed the association of bevacizumab use with rates of bevacizumab use in their physician's community of connected physicians in 2005 to 2006. Models adjusted for patient and physician characteristics and physician, practice, and community random effects. Main Outcomes and Measures:Receipt of bevacizumab. Results:A total of 34 750 patients (14 126 [40.6%] aged ≥75 years; 21 321 [61.4%] female) with cancers of the colorectum, lung, breast, kidney, brain, and ovary were treated with chemotherapy in 2005 to 2006 in the 51 hospital referral regions. Among 9262 patients treated in 2007 to 2010 by 829 physicians whose patients did not use bevacizumab in 2005 to 2006, 3654 (39.5%) were aged 75 years or older and 6227 (67.2%) were female. The rate of bevacizumab use relative to other chemotherapy in 2007 to 2010 by tertile of use (bevacizumab for <4.4%, 4.4%-6.2%, and >6.2% of all patients receiving chemotherapy) among their physician's peers in 2005 to 2006 was 10.0%, 9.5%, and 13.6%, respectively. After adjustment, use of bevacizumab in 2007 to 2010 was greater among physicians in communities with the highest rates of bevacizumab use in 2005 to 2006 compared with those whose peers were in the lowest tertile of bevacizumab use in 2005 to 2006 (adjusted odds ratio, 1.64; 95% CI, 1.20-2.25). Conclusions and Relevance:This study found that an increase in oncologists' adoption and use of bevacizumab in the years after its approval was associated with their peer physicians being earlier adopters. As organizations seek to provide better care at lower costs, interventions that leverage physician ties may help to promote adoption of high-value use of new cancer treatments and deimplementation of low-value therapies.

SUBMITTER: Keating NL

PROVIDER: S-EPMC6991243 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Although physicians learn about new medical technologies from their peers, the magnitude and source of peer influence is unknown. We estimate the effect of peer adoption of three first-in-class medications (dabigatran, sitigliptin, and aliskiren) on physicians' own adoption of those medications. We included 11,958 physicians in Pennsylvania prescribing anticoagulant, antidiabetic, and antihypertensive medications. We constructed 4 types of peer networks based on shared Medicare and Medicaid patients, medical group affiliation, hospital affiliation, and medical school/residency training. Instrumental variables analysis was used to estimate the causal effect of peer adoption (fraction of peers in each network adopting the new drug) on physician adoption (prescribing at least the median number prescriptions within 15 months of the new drug's introduction). We illustrate how physician network position can inform targeting of interventions to physicians by computing a social multiplier. Dabigatran was adopted by 25.2%, sitagliptin by 24.5% and aliskiren by 8.3% of physicians. A 10-percentage point increase in peer adoption in the patient-sharing network led to a 5.90% (SE = 1.50%, p<0.001) increase in physician adoption of dabigatran, 8.32% (SE = 1.51%, p<0.001) increase in sitagliptin, and 7.84% increase in aliskiren adoption (SE = 2.93%, p<0.001). Peer effects through shared hospital affiliation were positive but not significant, and medical group and training network effects were not reliably estimated. Physicians in the top decile of patient-sharing network peers were estimated to have nearly 2-fold stronger influence on their peers' adoption compared to physicians in the top decile of prescribing volume. Limitations include lack of detailed clinical information and pharmaceutical promotion, variables which may influence physician adoption but which are unlikely to bias our peer effect estimates. Peer adoption, especially by those with whom physicians share patients, strongly influenced physician adoption of new drugs. Our study shows the potential for using information on physician peer networks to improve technology diffusion.

Project description:ImportanceThe rapid transition to virtual health care has depended on physician and patient abilities to adopt new technology and workflows. Physicians transitioning more slowly or not at all could result in access challenges for their patients.ObjectiveTo identify physician characteristics associated with the transition to virtual health care in a large regional health care system.Design, setting, and participantsThis retrospective cross-sectional study uses administrative health system databases to analyze data from all 3473 physicians providing ambulatory care through a large New England health care system, which includes 12 hospitals and their ambulatory practices, from October 1, 2019, through December 31, 2020.ExposuresPhysicians characterized based on gender, popularized generational demographic cohort (Silent Generation, born 1928-1945; Baby Boomers, born 1946-1964; Generation X, born 1965-1980; and Millennials, born 1981-1996), specialty (behavioral health, primary care, medical, and surgical), and hospital affiliation as well as selected patient characteristics (number of visits and proportion of patients with self-pay or Medicaid insurance, aged 65 years or older, preference for speaking a language other than English, from a racial or ethnic minority group, and with an active patient portal).Main outcomes and measuresEarly adoption of virtual health care. Bivariate comparisons were made, and regression modeling was used to examine characteristics associated with the likelihood of early adoption of virtual health care.ResultsOf 3473 physicians conducting ambulatory visits during the study period, 1624 (46.8%) were women, 83 (2.4%) were in the Silent Generation, 994 (28.6%) were Baby Boomers, 1637 (47.1%) were in Generation X, and 759 (21.9%) were Millennials. There were 1649 physicians (47.5%) in medical specialties, 749 physicians (21.6%) in surgical specialties, and 248 physicians (7.1%) in behavioral health. After accounting for other characteristics, female (odds ratio [OR], 1.23; 95% CI, 1.06-1.44), behavioral health (OR, 2.92; 95% CI, 2.11-4.04), and primary care (OR, 1.69; 95% CI, 1.36-2.09) physicians had greater odds of being early adopters, and physicians in the Silent Generation (OR, 0.39, 95% CI, 0.24-0.65) and in surgical specialties (OR, 0.46; 95% CI, 0.38-0.57) were less likely to be early adopters. Patient characteristics were less strongly associated with physician adoption.Conclusions and relevanceIn this cross-sectional study, there was physician-level variation in the adoption of virtual health care, with female, primary care, and behavioral health physicians in this system most likely to lead the transformation to virtual health care.

Project description:Variation in emergency physician computed tomography (CT) imaging utilization is well described, but little is known about what drives it. Physician empathy has been proposed as a potential characteristic affecting CT utilization.The objective was to describe empathy in a cohort of emergency physicians and evaluate its association with CT utilization. We also sought to compare emergency physician performance on an empathy psychometric test with performance on other psychometric tests previously proposed as predictors of CT utilization.This cross-sectional study included two parts: 1) a secondary analysis of emergency department (ED) CT imaging utilization data in a large health system from July 2013 to June 2014 and 2) a survey study of the cohort of physicians responsible for this imaging using four psychometric scales: the Jefferson Scale of Empathy (JSE), a risk-taking subset of the Jackson Personality Index (RTS), the Stress from Uncertainty Scale (SUS), and the Malpractice Fear Scale (MFS). The study included data and physicians from four EDs: one urban, academic ED, two community, and one free-standing. A hierarchical, mixed-effects regression model was used to evaluate the association between emergency physician performance on the four scales and risk-adjusted CT imaging utilization. The model incorporated physician-specific CT utilization rates adjusted for propensity scores that were calculated using over 500 patient-level variables via random forest methods, physician demographics, and a random provider effect to account for the clustering of observations.CT variation analysis included 113,517 patients seen during the study period by the 74 eligible emergency physician survey respondents; 20,972 (18.5%) of these patients had at least one CT. The survey response rate was 74 of 82 (90.2%). Correlation coefficients between JSE and the other scales were not statistically significant. In subset analysis, there was a trend toward a physician's number of years in practice and RTS score contributing to CT utilization for traumatic head CT. There were no significant associations between performance on any of the psychometric scales and CT utilization.Performance on the JSE, RTS, SUS, or MFS was not predictive of risk-adjusted CT utilization in the ED. The underlying physician-based factors that mediate interphysician variation remain to be clearly identified.

Project description:BackgroundPhysician burnout has a direct impact on the delivery of high-quality health care, with health information technology tools such as electronic health records (EHRs) adding to the burden of practice inefficiencies.ObjectiveThe aim of this study was to determine the extent of burnout among physicians and learners (residents and fellows); identify significant EHR-related contributors of physician burnout; and explore the differences between physicians and learners with regard to EHR-related factors such as time spent in EHR, documentation styles, proficiency, training, and perceived usefulness. In addition, the study aimed to address gaps in the EHR-related burnout research methodologies by determining physicians' patterns of EHR use through usage logs.MethodsThis study used a cross-sectional survey methodology and a review of administrative data for back-end log measures of survey respondents' EHR use, which was conducted at a large Canadian academic mental health hospital. Chi-square and Fisher exact tests were used to examine the association of EHR-related factors with general physician burnout. The survey was sent out to 474 individuals between May and June 2019, including physicians (n=407), residents (n=53), and fellows (n=14), and we measured physician burnout and perceptions of EHR stressors (along with demographic and practice characteristics).ResultsOur survey included 208 respondents, including physicians (n=176) and learners (n=32). The response rate was 43.2% for physicians (full-time: 156/208, 75.0%; part-time: 20/199, 10.1%), and 48% (32/67) for learners. A total of 25.6% (45/176) of practicing physicians and 19% (6/32) of learners reported having one or more symptoms of burnout, and 74.5% (155/208) of all respondents who reported burnout symptoms identified the EHR as a contributor. Lower satisfaction and higher frustration with the EHRs were significantly associated with perceptions of EHR contributing toward burnout. Physicians' and learners' experiences with the EHR, gathered through open-ended survey responses, identified challenges around the intuitiveness and usability of the technology as well as workflow issues. Metrics gathered from back-end usage logs demonstrated a 13.6-min overestimation in time spent on EHRs per patient and a 5.63-hour overestimation of after-hours EHR time, when compared with self-reported survey data.ConclusionsThis study suggests that the use of EHRs is a perceived contributor to physician burnout. There should be a focus on combating physician burnout by reducing the unnecessary administrative burdens of EHRs through efficient implementation of systems and effective postimplementation strategies.

Project description:ImportanceThere is concern that nonmedical prescription opioid use is associated with an increased risk of later heroin use initiation in adolescents, but to our knowledge, longitudinal data addressing this topic are lacking.ObjectiveTo determine whether nonmedical prescription opioid use is associated with subsequent initiation of heroin use in adolescents.Design, setting, and participantsThis prospective longitudinal cohort study conducted in 10 high schools in Los Angeles, California, administered 8 semiannual surveys from 9th through 12th grade that assessed nonmedical prescription opioid use, heroin use, and other factors from October 2013 to July 2017. Students were baseline never users of heroin recruited through convenience sampling. Cox regression models tested nonmedical prescription opioid use statuses at survey waves 1 through 7 as a time-varying and time-lagged regressor and subsequent heroin use initiation across waves 2 to 8 as the outcome.ExposuresSelf-reported nonmedical prescription opioid use (past 30-day [current] use vs past 6-month [prior] use without past 30-day use vs no past 6-month use) at each wave from 1 to 7.Main outcomes and measuresSelf-reported heroin use initiation (yes/no) during waves 2 to 8.ResultsOf 3298 participants, 1775 (53.9%) were adolescent girls, 1563 (48.3%) were Hispanic, 548 (17.0%) were Asian, 155 (4.8%) were African American, 529 (16.4%) were non-Hispanic white, and 220 (6.8%) were multiracial. Among baseline never users of heroin in ninth grade with valid data (3298 [97% of cohort enrollees]; mean [SD] age, 14.6 [0.4] years), the number of individuals with outcome data available at each follow-up ranged from 2987 (90.6%) to 3200 (97.0%). The mean per-wave prevalence of prior and current nonmedical prescription opioid use from waves 1 to 7 was 1.9% and 2.7%, respectively. Seventy students (2.1%) initiated heroin use during waves 2 to 8. Prior vs no (hazard ratio, 3.59; 95% CI, 2.14-6.01; P < .001) and current vs no (hazard ratio, 4.37; 95% CI, 2.80-6.81; P < .001) nonmedical prescription opioid use were positively associated with subsequent heroin use initiation. For no, prior, and current nonmedical prescription opioid use statuses at waves 1 to 7, the estimated cumulative probabilities of subsequent heroin use initiation by wave 8 (42-month follow-up) were 1.7%, 10.7%, and 13.1%, respectively. In covariate-adjusted models, associations were attenuated but remained statistically significant and current nonmedical prescription opioid use risk estimates were stronger than corresponding associations of nonopioid substance use with subsequent heroin use initiation.Conclusions and relevanceNonmedical prescription opioid use was prospectively associated with subsequent heroin use initiation during 4 years of adolescence among Los Angeles youth. Further research is needed to understand whether this association is causal.

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Association of Physician Peer Influence With Subsequent Physician Adoption and Use of Bevacizumab.

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