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Our objective was to externally validate 2 simple risk scores for mortality among a mostly inpatient population with COVID-19 in Canada (588 patients for COVID-NoLab and 479 patients for COVID-SimpleLab). The mortality rates in the low-, moderate-, and high-risk groups for COVID-NoLab were 1.1%, 9.6%, and 21.2%, respectively. The mortality rates for COVID-SimpleLab were 0.0%, 9.8%, and 20.0%, respectively. These values were similar to those in the original derivation cohort. The 2 simple risk scores, now successfully externally validated, offer clinicians a reliable way to quickly identify low-risk inpatients who could potentially be managed as outpatients in the event of a bed shortage. Both are available online (https://ebell-projects.shinyapps.io/covid_nolab/ and https://ebell-projects.shinyapps.io/COVID-SimpleLab/).

Background: Electronic health records (EHRs) have been connected to excessive workload and physician burnout. Little is known about variation in physician experience with different EHRs, however. Objective: To analyze variation in reported usability and satisfaction across EHRs. Design: Internet-based survey available between December 2021 and October 2022 integrated into American Board of Family Medicine (ABFM) certification process. Participants: ABFM-certified family physicians who use an EHR with at least 50 total responding physicians. Measurements: Self-reported experience of EHR usability and satisfaction. Key Results: We analyzed the responses of 3358 physicians who used one of nine EHRs. Epic, athenahealth, and Practice Fusion were rated significantly higher across six measures of usability. Overall, between 10 and 30% reported being very satisfied with their EHR, and another 32 to 40% report being somewhat satisfied. Physicians who use athenahealth or Epic were most likely to be very satisfied, while physicians using Allscripts, Cerner, or Greenway were the least likely to be very satisfied. EHR-specific factors were the greatest overall influence on variation in satisfaction: they explained 48% of variation in the probability of being very satisfied with Epic, 46% with eClinical Works, 14% with athenahealth, and 49% with Cerner. Conclusions: Meaningful differences exist in physician-reported usability and overall satisfaction with EHRs, largely explained by EHR-specific factors. User-centric design and implementation, and robust ongoing evaluation are needed to reduce physician burden and ensure excellent experience with EHRs.

Introduction Clinical preventive services can reduce mortality and morbidity, but Americans receive only half of the recommended care. Although wellness visits protect time for clinicians to review needs and discuss care with patients, studies have not shown that having a wellness visit improves health outcomes. This study seeks to understand the types of discussions and volume of care delivered during wellness visits. Methods Using a sample of 1,008 patients scheduled for a wellness visit from 22 primary care clinicians across 3 states from 2018 to 2019, electronic health records were reviewed, and a subset of visits was audio recorded. The discussion and delivery of clinical preventive services, as recommended by the U.S. Preventive Services Task Force, were measured, and new diagnoses were identified from the clinical preventive services. Analyses were completed in 2020. Results Even though patients were up to date with 80% of the recommended clinical preventive services 3 months after the visit, only 0.5% of patients were up to date with all the recommended clinical preventive services. On average, 6.9 clinical preventive service discussions occurred during each wellness visit on the basis of electronic health records review, and 7.7 clinical preventive services discussions occurred on the basis of audio recordings. An average of 0.4 new diagnoses was identified, including cancer diagnoses, cardiovascular risks, and infections. Conclusions Wellness visits are an important time for patients and clinicians to discuss prevention strategies and to deliver recommended clinical preventive services, leading to the identification of previously unrecognized diagnoses. This will improve patients’ health. Policies and incentives that promote wellness visits are important, and efforts are needed to deliver them to those most in need.

A National Academies of Sciences, Engineering, and Medicine committee developed a plan to implement high-quality primary care. One of the 5 key objectives was designing information technology that serves the patient, family, and interprofessional care team. The committee defined high-quality primary care as the provision of whole person, integrated, accessible, and equitable healthcare by interprofessional teams who are accountable for addressing most of an individual’s health across settings and through sustained relationships. The committee recommended 2 essential actions for digital health. The first action is developing the next phase of digital health certification standards that support relationship-based, continuous, person-centered care; simplify user experience; ensure equitable access; and hold vendors accountable. Second, the committee recommended adopting a comprehensive aggregate patient data system usable by any certified digital health tool. This article reviews primary care’s digital health needs and describes successful digital health for primary care.

Objective Prenatal care (PNC) and well child visit (WCV) attendance are associated with improved health outcomes. We aimed to determine if the factors affecting maternal and child attendance are similar or different. Methods We conducted a retrospective case control study at Virginia Commonwealth University Health System. We used the Adequacy of Prenatal Care Utilization Index and the American Academy of Pediatrics recommendations to assess the adequacy of PNC and WCV attendance, respectively. Mothers with less than 50% visit adherence or initiation after 5 months gestation were eligible as cases and those with 80% or more adherence and initiation before 5 months were eligible as controls. Children in the lowest quintile of adherence were eligible as cases and those with 80% or more adherence were eligible as controls. Cases and controls were randomly selected at a 1:2 ratio from the eligible subjects and frequency matched on birth month. Results In adjusted analyses, mothers and children who were publicly insured or who were uninsured had higher odds of poor preventive visit attendance. Mothers who experienced intimate partner violence and had more living children were more likely to have poor attendance. Children whose mothers had younger age, greater number of pregnancies and transportation difficulties had poorer attendance. Conclusions While lack of insurance and public insurance remained significantly associated with both poor PNC and WCV attendance, other factors varied between groups. Expanding eligibility requirements and streamlining enrollment and renewal processes may improve two generations of preventive visit attendance.

This Viewpoint discusses the Whole Health System of care led by the US Department of Veterans Affairs.

INTRODUCTION: In December 2013, cholesterol treatment guidelines changed the approach to statin therapy by recommending fixed doses of low-, medium-, or high-intensity statins based on cardiovascular risk. We sought to evaluate the guideline’s adoption in a diverse group of practices. METHODS: Using a mixed-methods approach, we analyzed electronic health record data the year before and 2 years following guideline publication in 45 practices across 8 states. We examined associations based on patient, clinician, and practice characteristics and interviewed 24 clinicians and practice leaders to inform findings. RESULTS: The proportion of patients adherent with all recommendations 2 years after the guideline only increased from 18.5% to 20.3% (P

Impairment of visual acuity is a serious public health problem in older adults. The number of persons 60 years or older with impaired visual acuity (defined as best corrected visual acuity worse than 20/40 but better than 20/200) was estimated at 2.91 million in 2015, and the number who are blind (defined as best corrected visual acuity of 20/200 or worse) was estimated at 760 000. Impaired visual acuity is consistently associated with decreased quality of life in older persons, including reduced ability to perform activities of daily living, work, and drive safely, as well as increased risk of falls and other unintentional injuries.To update its 2016 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a systematic review to evaluate the benefits and harms of screening for impaired visual acuity in older adults.Asymptomatic adults 65 years or older who present in primary care without known impaired visual acuity and are not seeking care for vision problems.The USPSTF concludes that the evidence is insufficient to assess the balance of benefits and harms of screening for impaired visual acuity in asymptomatic older adults. The evidence is lacking, and the balance of benefits and harms cannot be determined. More research is needed.The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for impaired visual acuity in older adults. (I statement).

Cardiovascular disease (CVD) is the leading cause of mortality in the US, accounting for more than 1 in 4 deaths. Each year, an estimated 605 000 people in the US have a first myocardial infarction and an estimated 610 000 experience a first stroke.To update its 2016 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a systematic review on the effectiveness of aspirin to reduce the risk of CVD events (myocardial infarction and stroke), cardiovascular mortality, and all-cause mortality in persons without a history of CVD. The systematic review also investigated the effect of aspirin use on colorectal cancer (CRC) incidence and mortality in primary CVD prevention populations, as well as the harms (particularly bleeding) associated with aspirin use. The USPSTF also commissioned a microsimulation modeling study to assess the net balance of benefits and harms from aspirin use for primary prevention of CVD and CRC, stratified by age, sex, and CVD risk level.Adults 40 years or older without signs or symptoms of CVD or known CVD (including history of myocardial infarction or stroke) who are not at increased risk for bleeding (eg, no history of gastrointestinal ulcers, recent bleeding, other medical conditions, or use of medications that increase bleeding risk).The USPSTF concludes with moderate certainty that aspirin use for the primary prevention of CVD events in adults aged 40 to 59 years who have a 10% or greater 10-year CVD risk has a small net benefit. The USPSTF concludes with moderate certainty that initiating aspirin use for the primary prevention of CVD events in adults 60 years or older has no net benefit.The decision to initiate low-dose aspirin use for the primary prevention of CVD in adults aged 40 to 59 years who have a 10% or greater 10-year CVD risk should be an individual one. Evidence indicates that the net benefit of aspirin use in this group is small. Persons who are not at increased risk for bleeding and are willing to take low-dose aspirin daily are more likely to benefit. (C recommendation) The USPSTF recommends against initiating low-dose aspirin use for the primary prevention of CVD in adults 60 years or older. (D recommendation).

The purpose of the U.S. Preventive Services Task Force (USPSTF) is to provide evidence-based recommendations on primary care screening, behavioral counseling, and preventive medications. A person's health is strongly influenced by social determinants of health, such as economic and social conditions; therefore, preventive recommendations that address these determinants would be ideal. However, differing social determinants have been proposed by a wide range of agencies and organizations, little prevention evidence is available, and responsible parties are in competition, all of which make the creation of evidence-based prevention recommendations for social determinants of health challenging. This article highlights social determinants already included in USPSTF recommendations and proposes a process by which others may be considered for primary care preventive recommendations. In many ways, incorporating social determinants of health into evidence-based recommendations is an evolving area. By reviewing the evidence on the effects of screening and interventions on social determinants relevant to primary care, the USPSTF will continue to provide recommendations on clinical preventive services to improve the health of all Americans.

During a pandemic, primary care is the first line of defense. It is able to reinforce public health messages, help patients manage at home, and identify those in need of hospital care. In response to the COVID-19 pandemic, primary care scrambled to rapidly transform itself and protect clinicians, staff, and patients while remaining connected to patients. Using the established public health framework for addressing a pandemic, we describe the actions primary care needs to take in a pandemic. Recommended actions are based on observed experiences of the authors' primary care practices and networks. Early in the COVID-19 pandemic, tasks focused on promoting physical distancing and encouraging patients with suspected illness or exposure to self-quarantine. Testing was not available and contract tracing was not possible. As the pandemic spread, in-person care was converted to virtual care using telehealth. Practices remained connected to patients using registries to reach out to those at risk for infection, with uncontrolled chronic conditions, or were socially vulnerable. Practices managed most patients with suspected COVID-19 at home. As the pandemic decelerates, practices are now preparing to address the direct and indirect consequences-complications from COVID-19 infections, missed treatment for acute problems, inadequate prevention, uncontrolled chronic disease, mental illness, and greater social needs. Throughout, practices bore tremendous financial burden, laying off staff or even closing at a time when most needed. Primary care must learn from this experience and be ready for the next pandemic. Policymakers and payers cannot fail primary care during their next time of need.

Background: Despite widespread recognition that adherence to clinical preventive guidelines improves patient outcomes, clinicians struggle to implement guideline changes in a timely manner. Multiple factors influence guideline adoption and effective implementation. However, few studies evaluate their collective and inter-related effects. This qualitative study provides a comprehensive picture of the interplay between multiple factors on uptake of new or changed preventive guidelines. Methods: Semistructured interviews conducted in 2018 with a diverse sample of clinicians and practice leaders sought to understand patient, clinician, practice, health system, environment, and guideline factors of influence. An immersion-crystallization approach was used to identify emergent themes. Results: Interviewees expressed motivation to adhere to guidelines but also valued sharing decisions with patients. Personal biases and fears affected both clinician and patient guideline adoption. Practices facilitated implementation through workflow optimization and encouraging a culture of evidence-based practice while a key health system function was to maintain electronic health record alerts. More traditional environmental factors, such as insurance coverage or transportation, were less of a barrier to guideline adoption and implementation than the influence of media and specialists. Various specific guideline characteristics also affected ease of adoption and implementation. Different settings expressed greater health system, practice, or clinician-centric approaches to guideline implementation. Conclusions: Guideline uptake is influenced by a complex interplay of multiple levels of factors including the patient, clinician, practice, health system, environment, and guideline levels. Comprehensively understanding all levels of influence for each specific clinical setting may help to determine the optimal intervention(s) for improving uptake of evidence-based guidelines.

PURPOSE: Primary care is the foundation of the health care workforce and the only part that extends life and improves health equity. Previous research on the geographic and specialty distribution of physicians has relied on the American Medical Association’s Masterfile, but these data have limitations that overestimate the workforce. METHODS: We present a pragmatic, systematic, and more accurate method for identifying primary care physicians using the National Plan and Provider Enumeration System (NPPES) and the Virginia All-Payer Claims Database (VA-APCD). Between 2015 and 2019, we identified all Virginia physicians and their specialty through the NPPES. Active physicians were defined by at least 1 claim in the VA-APCD. Specialty was determined hierarchically by the NPPES. Wellness visits were used to identify non–family medicine physicians who were providing primary care. RESULTS: In 2019, there were 20,976 active physicians in Virginia, of whom 5,899 (28.1%) were classified as providing primary care. Of this primary care physician workforce, 52.4% were family medicine physicians; the remaining were internal medicine physicians (18.5%), pediatricians (16.8%), obstetricians and gynecologists (11.8%), and other specialists (0.5%). Over 5 years, the counts and relative percentages of the workforce made up by primary care physicians remained relatively stable. CONCLUSIONS: Our novel method of identifying active physicians with a primary care scope provides a realistic size of the primary care workforce in Virginia, smaller than some previous estimates. Although the method should be expanded to include advanced practice clinicians and to further delineate the scope of practice, this simple approach can be used by policy makers, payers, and planners to ensure adequate primary care capacity.

ObjectivesAn accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information.DesignMulticenter retrospective observational cohort study.SettingFour health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles.PatientsCoronavirus Disease 2019-confirmed and hospitalized adult patients.Measurements and Main ResultsWe included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate ≥30 breaths/min, and SpO2 2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79–0.88) and external validation at the other three health systems (range, 0.79–0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score.ConclusionsThe two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice.

BACKGROUND AND OBJECTIVES The American Academy of Pediatrics recommends against the routine use of β-agonists, corticosteroids, antibiotics, chest radiographs, and viral testing in bronchiolitis, but use of these modalities continues. Our objective for this study was to determine the patient, provider, and health care system characteristics that are associated with receipt of low-value services. METHODS Using the Virginia All-Payers Claims Database, we conducted a retrospective cross-sectional study of children aged 0 to 23 months with bronchiolitis (code J21, International Classification of Diseases, 10th Revision) in 2018. We recorded medications within 3 days and chest radiography or viral testing within 1 day of diagnosis. Using Poisson regression, we identified characteristics associated with each type of overuse. RESULTS Fifty-six percent of children with bronchiolitis received ≥1 form of overuse, including 9% corticosteroids, 17% antibiotics, 20% β-agonists, 26% respiratory syncytial virus testing, and 18% chest radiographs. Commercially insured children were more likely than publicly insured children to receive a low-value service (adjusted prevalence ratio [aPR] 1.21; 95% confidence interval [CI]: 1.15–1.30; P < .0001). Children in emergency settings were more likely to receive a low-value service (aPR 1.24; 95% CI: 1.15–1.33; P < .0001) compared with children in inpatient settings. Children seen in rural locations were more likely than children seen in cities to receive a low-value service (aPR 1.19; 95% CI: 1.11–1.29; P < .0001). CONCLUSIONS Overuse in bronchiolitis remains common and occurs frequently in emergency and outpatient settings and rural locations. Quality improvement initiatives aimed at reducing overuse should include these clinical environments.

BACKGROUND Community-Engaged Research (CEnR) is a research approach in which scholars partner with community organizations or individuals with whom they share an interest in the study topic, typically with the goal of supporting that community’s wellbeing. CEnR is well-established in numerous disciplines including the clinical and social sciences. However, universities experience challenges reporting comprehensive CEnR metrics, limiting development of appropriate CEnR infrastructure and advancement of relationships with communities, funders, and stakeholders. OBJECTIVE n/a METHODS We propose a novel approach to identifying and categorizing community-engaged studies by applying attention-based deep learning models to human subjects protocols that have been submitted to the university’s Institutional Review Board (IRB). We manually classified a sample of protocols submitted to the IRB using a 3 and 6-level CEnR heuristic. We then trained an attention-based Bidirectional-LSTM on the classified protocols and compared it to transformer models such as BERT, Bio+ClinicalBERT, and XLM-RoBERTa. We applied the best performing models to the full sample of unlabeled IRB protocols submitted in the years 2013-2019 (n > 6000). RESULTS Transfer learning appears to be superior, receiving a .9952 testing F1 Score for all transformer models implemented compared to the attention-based Bi-LSTM model. This finding is consistent across several methodological adjustments: an augmented dataset with and without cross-validation, an unaugmented dataset with and without cross-validation, a 6 class CEnR spectrum, and a 3 class one. BERT and the transformer models showed an understanding of our data unlike the attention-based model, promising usability for real-world application. CONCLUSIONS Transfer learning is a viable method for differentiating small datasets characterized by the idiosyncrasies and errors of CEnR descriptions used by principal investigators in research protocols.

Background Community-engaged research (CEnR) is a research approach in which scholars partner with community organizations or individuals with whom they share an interest in the study topic, typically with the goal of supporting that community’s well-being. CEnR is well-established in numerous disciplines including the clinical and social sciences. However, universities experience challenges reporting comprehensive CEnR metrics, limiting the development of appropriate CEnR infrastructure and the advancement of relationships with communities, funders, and stakeholders. Objective We propose a novel approach to identifying and categorizing community-engaged studies by applying attention-based deep learning models to human participants protocols that have been submitted to the university’s institutional review board (IRB). Methods We manually classified a sample of 280 protocols submitted to the IRB using a 3- and 6-level CEnR heuristic. We then trained an attention-based bidirectional long short-term memory unit (Bi-LSTM) on the classified protocols and compared it to transformer models such as Bidirectional Encoder Representations From Transformers (BERT), Bio + Clinical BERT, and Cross-lingual Language Model–Robustly Optimized BERT Pre-training Approach (XLM-RoBERTa). We applied the best-performing models to the full sample of unlabeled IRB protocols submitted in the years 2013-2019 (n>6000). Results Although transfer learning is superior, receiving a 0.9952 evaluation F1 score for all transformer models implemented compared to the attention-based Bi-LSTM (between 48%-80%), there were key issues with overfitting. This finding is consistent across several methodological adjustments: an augmented data set with and without cross-validation, an unaugmented data set with and without cross-validation, a 6-class CEnR spectrum, and a 3-class one. Conclusions Transfer learning is a more viable method than the attention-based bidirectional-LSTM for differentiating small data sets characterized by the idiosyncrasies and variability of CEnR descriptions used by principal investigators in research protocols. Despite these issues involving overfitting, BERT and the other transformer models remarkably showed an understanding of our data unlike the attention-based Bi-LSTM model, promising a more realistic path toward solving this real-world application.

To contribute to the national effort to combat the opioid crisis, the United States Preventive Services Task Force (USPSTF) commissioned a scoping review to describe the state of evidence for the primary prevention of opioid misuse or use disorder in persons not yet prescribed opioids or not yet misusing opioids. Patnode CD et al., 2021 As found by the scoping review, sparse direct evidence focusing on primary care-relevant prevention interventions exists. The purpose of the current commentary is to describe the relevant research needed to effectively inform primary care providers and patients about how to reduce the risk for future opioid use disorder and opioid misuse and improve health outcomes in those not yet exposed to or misusing opioid medications.

Community-engaged research (CEnR) is now an established research approach. The current research seeks to pilot the systematic and automated identification and categorization of CEnR to facilitate longitudinal tracking using administrative data. We inductively analyzed and manually coded a sample of Institutional Review Board (IRB) protocols. Comparing the variety of partnered relationships in practice with established conceptual classification systems, we developed five categories of partnership:Non-CEnR, Instrumental, Academic-led, Cooperative, and Reciprocal.The coded protocols were used to train a deep-learning algorithm using natural language processing to categorize research. We compared the results to data from three questions added to the IRB application to identify whether studies had a community partner and the type of engagement planned. The preliminary results show that the algorithm is potentially more likely to categorize studies as CEnR compared to investigator-recorded data and to categorize studies at a higher level of engagement. With this approach, universities could use administrative data to inform strategic planning, address progress in meeting community needs, and coordinate efforts across programs and departments. As scholars and technical experts improve the algorithm’s accuracy, universities and research institutions could implement standardized reporting features to track broader trends and accomplishments.

INTRODUCTION: Health behaviors, mental health, and social needs impact health, but addressing these needs is difficult. Clinicians can partner with community programs to provide patients support. The relationship between program location and community need is uncertain. METHODS: We identified and geolocated community programs in Richmond, Virginia, that aid with 9 domains of needs (mental health, smoking, unhealthy alcohol use, nutrition, physical activity, transportation, financial, housing, food insecurity). For each census tract, we identified needs from public data sources. We used 2 methods to compare program location and need: (1) hotspot analysis and (2) a negative binomial regression model. RESULTS: We identified 280 community programs that provide aid for the 9 domains. Programs most often provided financial assistance (n = 121) and housing support (n = 73). The regression analysis showed no relationship between the number of community programs and the level of need in census tracts, with 2 exceptions. There was a positive association between financial programs and financial need and a negative association between housing programs and housing need. CONCLUSIONS: Community programs are generally not colocated with need. This poses a barrier for people who need help addressing these domains.

Gun violence is a growing public health epidemic that disproportionately affects underserved and minority communities. Our study sought to document patient experiences of community gun violence as a theme that emerged in the context of interviews exploring community-level factors influencing patients' engagement in primary care within the context of a larger study on cardiovascular health.We completed semistructured qualitative interviews of individuals with uncontrolled hypertension recruited from primary care practices serving underserved communities in metro Richmond, Virginia that were participating in a larger study on improving cardiovascular health.Of 19 individuals interviewed, 11 discussed without prompting the negative effects of gun violence in their community. Themes that emerged included both the acute and chronic traumatic experience, the physiologic and cognitive effects of gun violence and the negative effects on ability to manage heart health.The effects of gun violence on not only cardiovascular health but also all aspects of health emerged unprompted in qualitative interviews about community level factors influencing management of cardiovascular health. Given the widespread negative effects of experiencing gun violence on health, family physicians could play an important role in identifying and managing the effects of gun violence. Future studies on how primary care clinicians can address gun violence in the caring for their patients comprehensively are needed.

The body of research on social determinants of health is rapidly accumulating. The U.S. Preventive Services Task Force is conducting evaluations to consider the inclusion of screening and counseling for social risks as a clinical preventive service. Yet, for many social risks, evidence is still likely needed before the U.S. Preventive Services Task Force can recommend universal screening or counseling. This manuscript offers a brief review of the social determinants of health that may be germane to the U.S. Preventive Services Task Force, the methods the U.S. Preventive Services Task Force uses to evaluate relevant evidence, and current evidence gaps for social risks. Key methods for making clinical preventive service recommendations are applied for considering the integration of social and clinical care. These methods include determining the certainty of the evidence, assessing the net benefit, defining appropriate prevention frameworks, defining health outcomes versus intermediate outcomes, fully assessing the harms, and defining to what populations and care contexts the evidence applies. This road map for research is intended to spark ingenuity and purpose in the next generation of research studies, thereby ensuring that future recommendations to address and prevent social risks in primary care are informed by high-quality evidence. Supplement information This article is part of a supplement entitled Identifying and Intervening on Social Needs in Clinical Settings: Evidence and Evidence Gaps, which is sponsored by the Agency for Healthcare Research and Quality of the U.S. Department of Health and Human Services, Kaiser Permanente, and the Robert Wood Johnson Foundation.

In this study, we evaluated family physicians’ ability to estimate the service area of their patient panel—a critical first step in contextual population-based primary care. We surveyed 14 clinicians and administrators from 6 practices. Participants circled their estimated service area on county maps that were compared with the actual service area containing 70% of the practice’s patients. Accuracy was ascertained from overlap and the amount of estimated census tracts that were not part of the actual service area. Average overlap was 75%, but participants overestimated their service area by an average of 166 square miles. Service area overestimation impedes implementation of targeted community interventions by practices.

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. RESULTS Of 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.

* Abbreviation: USPSTF — : US Preventive Services Task Force In this issue of Pediatrics , Smith et al1 describe the challenges with implementing the US Preventive Services Task Force (USPSTF) recommendation for obesity screening in children and adolescents and offering or referring patients and families to behavioral interventions to promote weight improvement. The authors posit that effective behavioral interventions are not feasible to routinely deliver, and this challenge further exacerbates existing health inequities. The mission of the USPSTF is to make recommendations about clinical preventive services using a transparent, rigorous, and objective methodology. This approach ensures that clinicians and patients understand the evidence. On the basis of the certainty of the evidence and the magnitude of net benefits (eg, benefits minus harms), the USPSTF issues an A, B, C, or D grade or I statement. For clinicians, A and B grades mean to offer routinely, C means to selectively offer, D means to not routinely offer, and I is insufficient evidence to recommend … Address correspondence to Alex H. Krist, MD, MPH, 3825 Charles Stewart Dr, Fairfax, VA 22033. E-mail: alexander.krist{at}vcuhealth.org, 703-391-2020