BACKGROUND Primary care clinicians write 45% of all opioid prescriptions in the United States, but little is known about the characteristics of patients who receive them and the clinicians who prescribe opioids in primary care settings. Our study aimed to describe the patient and clinician characteristics and clinicians' perspectives of chronic opioid prescribing in primary care.METHODS Using a mixed methods approach, we completed an analysis of 2016 electronic health records from 21 primary care practices to identify patients who had received chronic opioids, which we defined as in receipt of an opioid prescription for at least 3 consecutive months. We compared those receiving chronic opioids with those not in terms of their demographics, prescribing clinician characteristics, and risk factors for opioid-related harms, as identified by the Centers for Disease Control and Prevention Guideline on Opioid Prescribing for Chronic Pain. We then interviewed 16 primary care clinicians about their perspectives on chronic opioid prescribing. RESULTSOf 84,029 patients, 1.1% (902/84,929) received chronic opioid prescriptions. Characteristics associated with being prescribed chronic opioids include being female, being of black or African American race, and having risks for opioid-related harms, such as mental health diagnoses, substance use disorder, and concurrent benzodiazepine use. Clinicians report multiple difficulties in weaning patients from chronic opioids, including medical contraindications of nonopioid alternatives and difficulty justifying weaning by stable long-term patients.CONCLUSION Although patients prescribed opioids in primary care have higher risks of opioid-related harms, clinicians report multiple barriers in deprescribing chronic opioids. Future studies should examine strategies to mitigate these harms and engage patients in shared decision making about their chronic opioid use.

BackgroundElectronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether.ObjectiveTo propose a conceptual framework that analyzes respondent attrition and demonstrates the utility of these methods with existing survey data.MethodsFirst, we suggest visualization of attrition trends using bar charts and survival curves. Next, we propose a generalized linear mixed model (GLMM) to detect or confirm significant attrition points. Finally, we suggest applications of existing statistical methods to investigate the effect of internal survey characteristics and patient characteristics on dropout. In order to apply this framework, we conducted a case study; a seventeen-item Informed Decision-Making (IDM) module addressing how and why patients make decisions about cancer screening.ResultsUsing the framework, we were able to find significant attrition points at Questions 4, 6, 7, and 9, and were also able to identify participant responses and characteristics associated with dropout at these points and overall.ConclusionsWhen these methods were applied to survey data, significant attrition trends were revealed, both visually and empirically, that can inspire researchers to investigate the factors associated with survey dropout, address whether survey completion is associated with health outcomes, and compare attrition patterns between groups. The framework can be used to extract information beyond simple responses, can be useful during survey development, and can help determine the external validity of survey results.

Purpose:Little is known about incorporating community data into clinical care. This study sought to understand the clinical associations of cold spots (census tracts with worse income, education, and composite deprivation).Methods: Across 12 practices, we assessed the relationship between cold spots and clinical outcomes (obesity, uncontrolled diabetes, pneumonia vaccination, cancer screening-colon, cervical, and prostate-and aspirin chemoprophylaxis) for 152,962 patients. We geocoded and linked addresses to census tracts and assessed, at the census tract level, the percentage earning less than 200% of the Federal Poverty Level, without high school diplomas, and the social deprivation index (SDI). We labeled those census tracts in the worst quartiles as cold spots and conducted bivariate and logistic regression.Results: There was a 10-fold difference in the proportion of patients in cold spots between the highest (29.1%) and lowest practices (2.6%). Except for aspirin, all outcomes were influenced by cold spots. Fifteen percent of low-education cold-spot patients had uncontrolled diabetes compared with 13% of noncold-spot patients (P < .05). In regression, those in poverty, low education, and SDI cold spots were less likely to receive colon cancer screening (odds ratio [

BACKGROUND AND OBJECTIVES:It is unclear which specific well-child visits (WCVs) are most frequently missed and whether age-specific patterns of attendance differ by race or insurance type. METHODS:We conducted a retrospective cohort study of children 0 to 6 years old between 2011 and 2016 within 2 health networks spanning 20 states. WCVs were identified by using International Classification of Diseases, Ninth and 10th Revisions and Current Procedural Terminology codes. We calculated adherence to the 13 American Academy of Pediatricsrecommended WCVs from birth to age 6 years. To address data completeness, we made 2 adherence calculations after a child's last recorded WCV: 1 in which we assumed all subsequent WCVs were attended outside the network and 1 in which we assumed none were. RESULTS:We included 152 418 children in our analysis. Most children were either publicly insured (77%) or uninsured (14%). The 2-, 4-, and 6-month visits were the most frequently attended (63% [assuming no outside care after the last recorded WCV] to 90% [assuming outside care]), whereas the 15-and 18-months visits (41%-75%) and 4-year visit (19%-49%) were the least frequently attended. Patients who were publicly insured and uninsured (versus privately insured) had higher odds of missing WCVs. Hispanic and Asian American (versus non-Hispanic white) patients had higher odds of attending WCVs. DISCUSSIONThe 15-and 18-month WCVs as well as the 4-year WCV are the least frequently attended WCVs. The former represent opportunities to identify developmental delays, and the latter represents an opportunity to assess school readiness.

Many patients face decisions that can be anticipated and proactively facilitated through technology. Although use of technology has the potential to make visits more efficient and effective, cultural, workflow, and technical changes are needed before it could be widely disseminated.

Buprenorphine can be used in primary care to treat opioid use disorder, but many family physicians feel unprepared to care for patients with opioid addiction. We sought to describe preparedness to provide and current provision of buprenorphine treatment by early career family physicians using data from the 2016 National Family Medicine Graduate Survey. Of 1,979 respondents, 10.0% reported preparedness to provide buprenorphine treatment, and 7.0% reported current buprenorphine provision. Residency preparation to provide buprenorphine treatment was most highly associated with current provision (odds ratio = 13.50; 95% CI, 7.59-24.03). Efforts to increase buprenorphine training may alleviate the workforce shortage to treat opioid use disorder.

Glioblastoma (GBM) is an aggressive central nervous system tumor with a poor prognosis. This study was conducted to determine any comorbid medical conditions that are associated with survival in GBM. Data were collected from medical records of all patients who presented to VCU Medical Center with GBM between January 2005 and February 2015. Patients who underwent surgery/biopsy were considered for inclusion. Cox proportional hazards regression modeling was performed to assess the relationship between survival and sex, race, and comorbid medical conditions. 163 patients met inclusion criteria. Comorbidities associated with survival on individual-characteristic analysis included: history of asthma (Hazard Ratio [HR]: 2.63; 95% Confidence Interval [CI]: 1.24–5.58; p = 0.01), hypercholesterolemia (HR: 1.95; 95% CI: 1.09–3.50; p = 0.02), and incontinence (HR: 2.29; 95% CI: 0.95–5.57; p = 0.07). History of asthma (HR: 2.22; 95% CI: 1.02–4.83; p = 0.04) and hypercholesterolemia (HR: 1.99; 95% CI: 1.11–3.56; p = 0.02) were associated with shorter survival on multivariable analysis. Surgical patients with GBM who had a prior history of asthma or hypercholesterolemia had significantly higher relative risk for mortality on individual-characteristic and multivariable analyses.

Loneliness is associated with poor health outcomes, and there is growing attention on loneliness as a social determinant of health. Our study sought to determine the associations between community factors and loneliness. The Three-Item Loneliness Scale and zip codes of residence were collected in primary care practices in Colorado and Virginia. Living in zip codes with higher unemployment, poor access to health care, lower income, higher proportions of blacks, and poor transportation was associated with higher mean loneliness scores. Future studies that examine interventions addressing loneliness may be more effective if they consider social context and community characteristics.