Underlying Reasons for Primary Care Visits Where Chlamydia Testing Was Performed in the United States, 2019 to 2022.

BACKGROUND: In the United States, most chlamydia cases are reported from non-sexually transmitted disease clinics, and there is limited information focusing on the reasons for chlamydia testing in private settings. These analyses describe clinical visits to primary care providers where chlamydia testing was performed to help discern between screening and diagnostic testing for chlamydia. METHODS: Using the largest primary care clinical registry in the United States, the PRIME registry, chlamydia tests were identified using Current Procedural Terminology procedure codes and categorized as diagnostic testing for sexually transmitted infection (STI)-related symptoms, screening for chlamydia, or "other," based on Classification of Diseases, Tenth Revision Evaluation and Management codes selected for visits. RESULTS: Of 120,013 clinical visits with chlamydia testing between January 1, 2019, and December 31, 2022, 70.4% were women; 20.6% were with STI-related symptoms, 59.9% were for screening, and 19.5% for "other" reasons. Of those 120,013 clinical visits with chlamydia testing, the logit model showed that patients were significantly more likely to have STI-related symptoms if they were female than male, non-Hispanic Black than non-Hispanic White, aged 15 to 24 years than aged ≥45 years, and resided in the South than in the Northeast. CONCLUSION: It is important to know what proportion of chlamydial infections is identified through screening programs and to have this information stratified by demographics. The inclusion of laboratory results could further facilitate a better understanding of the impact of chlamydia screening programs on the identification and treatment of chlamydia in private office settings in the United States.

The Disproportionate Impact of Primary Care Disruption and Telehealth Utilization During COVID-19.

PURPOSE: The COVID-19 pandemic not only exacerbated existing disparities in health care in general but likely worsened disparities in access to primary care. Our objective was to quantify the nationwide decrease in primary care visits and increase in telehealth utilization during the pandemic and explore whether certain groups of patients were disproportionately affected. METHODS: We used a geographically diverse primary care electronic health record data set to examine the following 3 outcomes: (1) change in total visit volume, (2) change in in-person visit volume, and (3) the telehealth conversion ratio defined as the number of pandemic telehealth visits divided by the total number of prepandemic visits. We assessed whether these outcomes were associated with patient characteristics including age, gender, race, ethnicity, comorbidities, rurality, and area-level social deprivation. RESULTS: Our primary sample included 1,652,871 patients from 408 practices. During the pandemic we observed decreases of 7% and 17% in total and in-person visit volume and a 10% telehealth conversion ratio. The greatest decreases in visit volume were observed among pediatric patients (-24%), Asian patients (-11%), and those with more comorbidities (-9%). Telehealth usage was greatest among Hispanic or Latino patients (17%) and those living in urban areas (12%). CONCLUSIONS: Decreases in primary care visit volume were partially offset by increasing telehealth use for all patients during the COVID-19 pandemic, but the magnitude of these changes varied significantly across all patient characteristics. These variations have implications not only for the long-term consequences of the COVID-19 pandemic, but also for planners seeking to ready the primary care delivery system for any future systematic disruptions.

Post-COVID Conditions in US Primary Care: A PRIME Registry Comparison of Patients With COVID-19, Influenza-Like Illness, and Wellness Visits.

PURPOSE: COVID-19 is a condition that can lead to other chronic conditions. These conditions are frequently diagnosed in the primary care setting. We used a novel primary care registry to quantify the burden of post-COVID conditions among adult patients with a COVID-19 diagnosis across the United States. METHODS: We used the American Family Cohort, a national primary care registry, to identify study patients. After propensity score matching, we assessed the prevalence of 17 condition categories individually and cumulatively, comparing patients having COVID-19 in 2020-2021 with (1) historical control patients having influenza-like illness in 2018 and (2) contemporaneous control patients seen for wellness or preventive visits in 2020-2021. RESULTS: We identified 28,215 patients with a COVID-19 diagnosis and 235,953 historical control patients with influenza-like illness. The COVID-19 group had higher prevalences of breathing difficulties (4.2% vs 1.9%), type 2 diabetes (12.0% vs 10.2%), fatigue (3.9% vs 2.2%), and sleep disturbances (3.5% vs 2.4%). There were no differences, however, in the postdiagnosis monthly trend in cumulative morbidity between the COVID-19 patients (trend = 0.026; 95% CI, 0.025-0.027) and the patients with influenza-like illness (trend = 0.026; 95% CI, 0.023-0.027). Relative to contemporaneous wellness control patients, COVID-19 patients had higher prevalences of breathing difficulties and type 2 diabetes. CONCLUSIONS: Our findings show a moderate burden of post-COVID conditions in primary care, including breathing difficulties, fatigue, and sleep disturbances. Based on clinical registry data, the prevalence of post-COVID conditions in primary care practices is lower than that reported in subspecialty and hospital settings.

Foundational Collective Actions for Achieving Agile High-Quality Primary Care in the United States.

In 2021, the National Academy of Science, Engineering, and Medicine Committee on Implementing High-Quality Primary Care published its recommendations to expand the provision of high-quality primary care in the USA. These include paying for primary care teams to care for people, ensuring that high-quality primary care is available, training primary care teams where people live and work, and designing information technology that serves the patient, family, and care team. Many of these recommendations echo those of prior calls for action, including the Institute of Medicine's 1996 report. However, the 2021 report recognizes the importance of implementation in its final recommendation of ensuring that high-quality primary care is implemented in the USA. We consider the NASEM recommendations in terms of the complexity of the task of supporting interconnected implementation activities that occur in local contexts. With this vantage point, we identify foundational collective actions, including the creation of an accountable leadership entity, payment reform, and community networks. We then discuss the creation of a monitoring mechanism to assess and support sustained action.

Variation in Family Physicians' Experiences Across Different Electronic Health Record Platforms: a Descriptive Study.

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.

Measuring Trust in Primary Care.

Policy Points Trust in primary care clinicians is essential for effective patient care and is associated with better health outcomes, but it is rarely assessed, and existing measures have not been thoroughly evaluated. This scoping review reveals that research assessing patients' trust in primary care clinicians largely stopped more than a decade ago but offers candidate measures for future testing, implementation, and policy applications. CONTEXT: Trust is a fundamental aspect of any human relationship, and medical care is no exception. An ongoing, trusting relationship between clinicians and patients has shown demonstrable value to primary care. However, there is currently no measure of trust in general use, and none endorsed for use by most value-based payment programs. This review searched the literature for any existing measures of patient trust in primary care clinicians and assessed their potential to be implemented as a patient-reported outcome measure. METHODS: A keyword search on PubMed along with scanning references was conducted to find any trust measures in health care. Measures that did not address primary care clinicians were eliminated and the remaining measures were then assessed for their utility to primary care. RESULTS: This purposeful, scoping review found four tested measures for assessing patients' trust in primary care clinicians that are candidates for general use. Of these four, the revised Trust in Physicians Scale and Wake Forest Physician Trust Scale are the most tested and viable options. CONCLUSION: Renewed national interest in trust in health care should focus on the capacity to measure it. This review informs the effort to test trust measures for use in research, practice improvement, and value-based payment. Measuring trust, how it relates to outcomes, and learning how it is produced or lost are key to assisting practices and health systems toward earning it.

How the Gender Wage Gap for Primary Care Physicians Differs by Compensation Approach : A Microsimulation Study.

BACKGROUND: The physician gender wage gap may be due, in part, to productivity-based compensation models that undervalue female practice patterns. OBJECTIVE: To determine how primary care physician (PCP) compensation by gender differs when applying existing productivity-based and alternative compensation models. DESIGN: Microsimulation. SETTING: 2016 to 2019 national clinical registry of 1222 primary care practices. PARTICIPANTS: Male and female PCPs matched on specialty, years since medical school graduation, practice site, and sessions worked. MEASUREMENTS: Net annual, full-time-equivalent compensation for male versus female PCPs, under productivity-based fee-for-service, panel size-based capitation without or with risk adjustment, and hybrid payment models. Microsimulation inputs included patient and visit characteristics and overhead expenses. RESULTS: Among 1435 matched male (n = 881) and female (n = 554) PCPs, female PCP panels included patients who were, on average, younger, had lower diagnosis-based risk scores, were more often female, and were more often uninsured or insured by Medicaid rather than by Medicare. Under productivity-based payment, female PCPs earned a median of $58 829 (interquartile range [IQR], $39 553 to $120 353; 21%) less than male PCPs. This gap was similar under capitation ($58 723 [IQR, $42 141 to $140 192]). It was larger under capitation risk-adjusted for age alone ($74 695 [IQR, $42 884 to $152 423]), for diagnosis-based scores alone ($114 792 [IQR, $49 080 to $215 326] and $89 974 [IQR, $26 175 to $173 760]), and for age-, sex-, and diagnosis-based scores ($83 438 [IQR, $28 927 to $129 414] and $66 195 [IQR, $11 899 to $96 566]). The gap was smaller and nonsignificant under capitation risk-adjusted for age and sex ($36 631 [IQR, $12 743 to $73 898]). LIMITATION: Panel attribution based on office visits. CONCLUSION: The gender wage gap varied by compensation model, with capitation risk-adjusted for patient age and sex resulting in a smaller gap. Future models might better align with primary care effort and outcomes. PRIMARY FUNDING SOURCE: None.

Family Practices in Transforming Clinical Practice Initiative Showed No Changes in Medicare Costs or Utilization.

BACKGROUND: The Centers for Medicare and Medicaid Services proposed that the Transforming Clinical Practice Initiative (TCPI) would improve health outcomes for patients, reduce utilization of institutional services, and generate significant savings for payers by the end of September 2019. OBJECTIVE: The objective of this study was to investigate whether participation in TCPI's Practice Transformation Networks (PTNs) was associated with improved cost and utilization outcomes for Medicare patients of family medicine-based practices in the first 2 years, that is, 2016-2017, of the Initiative. STUDY DESIGN: A quasi-experimental design with a longitudinal cohort of family medicine-based practices and a propensity-matched comparison sample. SUBJECTS: A total of 761 PTN practices and 3451 non-PTN practices. MEASURES: To measure practice-level patient outcomes, we attributed patients to practice based on the plurality of office visits. We obtained Medicare claims from 2011 to 2017 to assess PTN participation effects for Medicare Part A and B costs, hospital admission, and emergency department visit rates using a Difference-in-Differences design, adjusting for baseline characteristics. RESULTS: The differences in Medicare Part A and B costs (-1.71%, P=0.25), annual rates of hospitalization (-0.59%, P=0.12) and emergency department visit (-0.29%, P=0.46) were not significantly lower among PTN practices (N=761) than among propensity score-matched non-PTN practices (N=3541). CONCLUSIONS: TCPI's transforming efforts, such as the outcomes examined in the study, might need a longer time frame to manifest and require evaluation after the full 4-year participation period. The indistinguishable effect of PTN participation may also be attributed to the fact that non-PTN practices might have participated in other initiatives that changed their care and curbed health care utilization and costs consequently.

Physicians' Choice of Board Certification Activity Is Unaffected by Baseline Quality of Care: The TRADEMaRQ Study.

PURPOSE: Physicians' use of self-assessment to guide quality improvement or board certification activities often does not correlate with more objective measures, and they may spend valuable time on activities that support their strengths instead of addressing gaps. Our objective was to study whether viewing quality measures, with peer comparisons, would affect the selection of certification activities. METHODS: We conducted a cluster-randomized controlled trial-the Trial of Data Exchange for Maintenance of certification and Raising Quality (TRADEMaRQ)-with 4 partner organizations during 2015-2017. Physicians were presented their quality data within their online certification portfolios before (intervention) vs after (control) they chose board certification activities. The primary outcome was whether the selected activity addressed a quality gap (a quality area in which the physician scored below the mean for the study population). RESULTS: Of 2,570 invited physicians, 254 physicians completed the study: 130 in the intervention group and 124 in the control group. Nearly one-fifth of participating physicians did not complete any certification activities during the study. A sizable minority of those in the intervention group, 18.4%, never reviewed their quality dashboard. Overall, just 27.2% of completed certification activities addressed a quality gap, and there was no significant difference in this outcome in the intervention group vs the control group in either bivariate or adjusted analyses (odds ratio = 1.28; 95% CI, 0.90-1.82). CONCLUSIONS: Physicians did not use quality performance data in choosing certification activities. Certification boards are being pressed to make their programs relevant to practice, less burdensome, and supportive of quality improvement in alignment with value-based payment models. Using practice data to drive certification choices would meet these goals.

Measuring the Value Functions of Primary Care: Physician-Level Continuity of Care Quality Measure.

PURPOSE: Care continuity is foundational to the clinician/patient relationship; however, little has been done to operationalize continuity of care (CoC) as a clinical quality measure. The American Board of Family Medicine developed the Primary Care CoC clinical quality measure as part of the Measures That Matter to Primary Care initiative. METHODS: Using 12-month Optum Clinformatics Data Mart claims data, we calculated the Bice-Boxerman Continuity of Care Index for each patient, which we rolled up to create an aggregate, physician-level CoC score. The physician quality score is the percent of patients with a Bice-Boxerman Index ≥0.7 (70%). We tested validity in 2 ways. First, we explored the validity of using 0.7 as a threshold for patient CoC within the Optum claims database to validate its use for reflecting patient-level continuity. Second, we explored the validity of the physician CoC measure by examining its association with patient outcomes. We assessed reliability using signal-to-noise methodology. RESULTS: Mean performance on the measure was 27.6%; performance ranged from 0% to 100% (n = 555,213 primary care physicians). Higher levels of CoC were associated with lower levels of care utilization. The measure indicated acceptable levels of validity and reliability. CONCLUSIONS: Continuity is associated with desirable health and cost outcomes as well as patient preference. The CoC clinical quality measure meets validity and reliability requirements for implementation in primary care payment and accountability. Care continuity is important and complementary to access to care, and prioritizing this measure could help shift physician and health system behavior to support continuity.

Estimated Effect on Life Expectancy of Alleviating Primary Care Shortages in the United States.

BACKGROUND: Prior studies have reported that greater numbers of primary care physicians (PCPs) per population are associated with reduced population mortality, but the effect of increasing PCP density in areas of low density is poorly understood. OBJECTIVE: To estimate how alleviating PCP shortages might change life expectancy and mortality. DESIGN: Generalized additive models, mixed-effects models, and generalized estimating equations. SETTING: 3104 U.S. counties from 2010 to 2017. PARTICIPANTS: Children and adults. MEASUREMENTS: Age-adjusted life expectancy; all-cause mortality; and mortality due to cardiovascular disease, cancer, infectious disease, respiratory disease, and substance use or injury. RESULTS: Persons living in counties with less than 1 physician per 3500 persons in 2017 had a mean life expectancy that was 310.9 days shorter than for persons living in counties above that threshold. In the low-density counties (n = 1218), increasing the density of PCPs above the 1:3500 threshold would be expected to increase mean life expectancy by 22.4 days (median, 19.4 days [95% CI, 0.9 to 45.6 days]), and all such counties would require 17 651 more physicians, or about 14.5 more physicians per shortage county. If counties with less than 1 physician per 1500 persons (n = 2636) were to reach the 1:1500 threshold, life expectancy would be expected to increase by 56.3 days (median, 55.6 days [CI, 4.2 to 105.6 days]), and all such counties would require 95 754 more physicians, or about 36.3 more physicians per shortage county. LIMITATION: Some projections are based on extrapolations of the actual data. CONCLUSION: In counties with fewer PCPs per population, increases in PCP density would be expected to substantially improve life expectancy. PRIMARY FUNDING SOURCE: None.

Rebuilding a US Federal Data Strategy After the End of the "Community Health Status Indicators".

For nearly 2 decades, the Community Health Status Indicators tool reliably supplied communities with standardized, local health data and the capacity for peer-community comparisons. At the same time, it created a large community of users who shared learning in addressing local health needs. The tool survived a transition from the Health Resources and Services Administration to the Centers for Disease Control and Prevention before being shuttered in 2017. While new community data tools have come online, nothing has replaced Community Health Status Indicators, and many stakeholders continue to clamor for something new that will enable local health needs assessments, peer comparisons, and creation of a community of solutions. The National Committee on Vital and Health Statistics heard from many stakeholders that they still need a replacement data source. (Am J Public Health. 2021;111(10):1865-1873. https://doi.org/10.2105/AJPH.2021.306437).

Clinical Quality Measure Exchange is Not Easy.

PURPOSE: The Trial of Aggregate Data Exchange for Maintenance of Certification and Raising Quality was a randomized controlled trial which first had to test whether quality reporting could be a by-product of clinical care. We report on the initial descriptive study of the capacity for and quality of exchange of whole-panel, standardized quality measures from health systems. METHODS: Family physicians were recruited from 4 health systems with mature quality measurement programs and agreed to submit standardized, physician-level quality measures for consenting physicians. Identified measure or transfer errors were captured and evaluated for root-cause problems. RESULTS: The health systems varied considerably by patient demographics and payer mix. From the 4 systems, 256 family physicians elected to participate. Of 19 measures negotiated for use, 5 were used by all systems. There were more than 15 types of identified errors including breaks in data delivery, changes in measures, and nonsensical measure results. Only 1 system had no identified errors. CONCLUSIONS: The secure transfer of standardized, physician-level quality measures from 4 health systems with mature measure processes proved difficult. There were many errors that required human intervention and manual repair, precluding full automation. This study reconfirms an important problem, namely, that despite widespread health information technology adoption and federal meaningful use policies, we remain far from goals to make clinical quality reporting a reliable by-product of care.

Maternity Care and Buprenorphine Prescribing in New Family Physicians.

The American Board of Family Medicine routinely surveys its Diplomates in each national graduating cohort 3 years out of training. These data were used to characterize early career family physicians whose services include management of pregnancy and prescribing buprenorphine. A total of 261 (5.1%) respondents both provide maternity care and prescribe buprenorphine. Family physicians who care for pregnant women and also prescribe buprenorphine represented 50.4% of all buprenorphine prescribers. The family physicians in this group were trained in a small number of residency programs, with only 15 programs producing at least 25% of graduates who do this work.

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.

BACKGROUND: Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine learning (ML) and inclusion of social determinants of health (SDH) indicators improve prospective risk adjustment for health plan payments. METHODS: We employed a 2-by-2 factorial design comparing: (i) linear regression versus ML (gradient boosting) and (ii) demographics and diagnostic codes alone, versus additional ZIP code-level SDH indicators. Healthcare claims from privately-insured US adults (2016-2017), and Census data were used for analysis. Data from 1.02 million adults were used for derivation, and data from 0.26 million to assess performance. Model performance was measured using coefficient of determination (R2), discrimination (C-statistic), and mean absolute error (MAE) for the overall population, and predictive ratio and net compensation for vulnerable subgroups. We provide 95% confidence intervals (CI) around each performance measure. RESULTS: Linear regression without SDH indicators achieved moderate determination (R2 0.327, 95% CI: 0.300, 0.353), error ($6992; 95% CI: $6889, $7094), and discrimination (C-statistic 0.703; 95% CI: 0.701, 0.705). ML without SDH indicators improved all metrics (R2 0.388; 95% CI: 0.357, 0.420; error $6637; 95% CI: $6539, $6735; C-statistic 0.717; 95% CI: 0.715, 0.718), reducing misestimation of cost by $3.5 M per 10,000 members. Among people living in areas with high poverty, high wealth inequality, or high prevalence of uninsured, SDH indicators reduced underestimation of cost, improving the predictive ratio by 3% (~$200/person/year). CONCLUSIONS: ML improved risk adjustment models and the incorporation of SDH indicators reduced underpayment in several vulnerable populations.

Primary Care Research Priorities in Low-and Middle-Income Countries.

PURPOSE: To identify and prioritize the needs for new research evidence for primary health care (PHC) in low-and middle-income countries (LMICs) about organization, models of care, and financing of PHC. METHODS: Three-round expert panel consultation of LMIC PHC practitioners and academics sampled from global networks, via web-based surveys. Iterative literature review conducted in parallel. Round 1 (pre-Delphi survey) elicited possible research questions to address knowledge gaps about organization and models of care and about financing. Round 2 invited panelists to rate the importance of each question, and in round 3 panelists provided priority ranking. RESULTS: One hundred forty-one practitioners and academics from 50 LMICs from all global regions participated and identified 744 knowledge gaps critical to improving PHC organization and 479 for financing. Four priority areas emerged: effective transition of primary and secondary services, horizontal integration within a multidisciplinary team and intersectoral referral, integration of private and public sectors, and ways to support successfully functioning PHC professionals. Financial evidence priorities were mechanisms to drive investment into PHC, redress inequities, increase service quality, and determine the minimum necessary budget for good PHC. CONCLUSIONS: This novel approach toward PHC needs in LMICs, informed by local academics and professionals, created an expansive and prioritized list of critical knowledge gaps in PHC organization and financing. It resulted in research questions, offering valuable guidance to global supporters of primary care evaluation and implementation. Its source and context specificity, informed by LMIC practitioners and academics, should increase the likelihood of local relevance and eventual success in implementing research findings.

Higher Primary Care Physician Continuity is Associated With Lower Costs and Hospitalizations.

PURPOSE: Continuity of care is a defining characteristic of primary care associated with lower costs and improved health equity and care quality. However, we lack provider-level measures of primary care continuity amenable to value-based payment, including the Medicare Quality Payment Program (QPP). We created 4 physician-level, claims-based continuity measures and tested their associations with health care expenditures and hospitalizations. METHODS: We used Medicare claims data for 1,448,952 beneficiaries obtaining care from a nationally representative sample of 6,551 primary care physicians to calculate continuity scores by 4 established methods. Patient-level continuity scores attributed to a single physician were averaged to create physician-level scores. We used beneficiary multilevel models, including beneficiary controls, physician characteristics, and practice rurality to estimate associations with total Medicare Part A & B expenditures (allowed charges, logged), and any hospitalization. RESULTS: Our continuity measures were highly correlated (correlation coefficients ranged from 0.86 to 0.99), with greater continuity associated with similar outcomes for each. Adjusted expenditures for beneficiaries cared for by physicians in the highest Bice-Boxerman continuity score quintile were 14.1% lower than for those in the lowest quintile ($8,092 vs $6,958; ß = -0.151; 95% CI, -0.186 to -0.116), and the odds of hospitalization were 16.1% lower between the highest and lowest continuity quintiles (OR = 0.839; 95% CI, 0.787 to 0.893). CONCLUSIONS: All 4 continuity scores tested were significantly associated with lower total expenditures and hospitalization rates. Such indices are potentially useful as QPP measures, and may also serve as proxy resource-use measures, given the strength of association with lower costs and utilization.

Burnout and Scope of Practice in New Family Physicians.

PURPOSE: Family physicians report some of the highest levels of burnout, but no published work has considered whether burnout is correlated with the broad scope of care that family physicians may provide. We examined the associations between family physician scope of practice and self-reported burnout. METHODS: Secondary analysis of the 2016 National Family Medicine Graduate Survey respondents who provided outpatient continuity care (N = 1,617). We used bivariate analyses and logistic regression to compare self-report of burnout and measures of scope of practice including: inpatient medicine, obstetrics, pediatric ambulatory care, number of procedures and/or clinical content areas, and providing care outside the principal practice site. RESULTS: Forty-two percent of respondents reported feeling burned out from their work once a week or more. In bivariate analysis, elements of scope of practice associated with lower burnout rates included providing more procedures/clinical content areas (mean procedures/clinical areas: 7.49 vs 7.02; P = .02) and working in more settings than the principal practice site (1+ additional settings: 57.6% vs 48.4%: P = .001); specifically in the hospital (31.4% vs 24.2%; P = .002) and patient homes (3.3% vs 1.5%; P = .02). In adjusted analysis, practice characteristics significantly associated with lower odds of burnout were practicing inpatient medicine (OR = 0.70; 95% CI, 0.56-0.87; P = .0017) and obstetrics (OR = 0.64; 95% CI, 0.47-0.88; P = .0058). CONCLUSIONS: Early career family physicians who provide a broader scope of practice, specifically, inpatient medicine, obstetrics, or home visits, reported significantly lower rates of burnout. Our findings suggest that comprehensiveness is associated with less burnout, which is critical in the context of improving access to good quality, affordable care while maintaining physician wellness.